diff --git a/.quarto/_freeze/SOFTWARE_READY/execute-results/docx.json b/.quarto/_freeze/SOFTWARE_READY/execute-results/docx.json index dbd65ad..e91287a 100644 --- a/.quarto/_freeze/SOFTWARE_READY/execute-results/docx.json +++ b/.quarto/_freeze/SOFTWARE_READY/execute-results/docx.json @@ -1,7 +1,7 @@ { - "hash": "f7618691fb5182b0a3a787b81d883471", + "hash": "0668efee2c4de4b6e1303759e17ba606", "result": { - "markdown": "# Make Your Data Software Ready {.unnumbered}\n\n## Use non-proprietary formats\n\n### Why?\n\n- Allows data to be useful in perpetuity by ensuring data readability and reusability across multiple platforms.\n- To align better with the FAIR principles (findability, accessibility, interoperability, reusability)\n- Makes data more socially equitable, supporting open science. Proprietary formats can depend on software that require licenses, which not everyone can afford/has access to.\n\n### Key Information\n\n- *Non-proprietary formats* are supported by more than one developer and can be accessed with different software systems. For example, comma separated values (CSV) format is becoming an increasingly popular non-proprietary format.\n- A [*proprietary file format*](https://en.wikipedia.org/wiki/Proprietary_file_format) is a file format of a company, organization, or individual that contains data that is ordered and stored according to a particular encoding-scheme, designed by the company or organization to be secret or with restricted access, such that the decoding and interpretation of this stored data is easily accomplished only with particular software or hardware that the company itself has developed. There may also be costs associated with it and access may be limited. Examples include `Microsoft Excel (xlsx)` and `ESRI shapefiles (shp)`.\n- Many applications (e.g. Microsoft Office) allow exporting in multiple formats.\n\n### Top References\n\n- Table of commonly used formats for common data types\\\n \n \n- A more detailed table that is specific to US Federal records management\\\n \n\n## Structure tabular data in tidy/long format\n\n### Why?\n\n*This is specifically intended for tabular data*\n\n- There is a clear and easy to understand structure that can make your data more machine readable and easier to analyze/visualize\n - Clear structure: one observation per row\n - Data are as atomic as possible (e.g., don't mix types in field)\n- In the biological data community, tidy formats are more likely to work with commonly-used software\n- Easier to aggregate data across multiple files\n\n### Key Information\n\nExample of Wide Format\n\n\n\n\n::: {.cell}\n::: {.cell-output-display}\n``````{=openxml}\n\nheader1speciessite_01site_02site_03body1Tilia americana044body2Pinus strobus410\n``````\n:::\n:::\n\n\n\n\nExample of Long Format\n\n\n\n\n::: {.cell}\n::: {.cell-output-display}\n``````{=openxml}\n\nheader1speciessitecountbody1Tilia americanasite_015body2Tilia americanasite_025body3Tilia americanasite_032body4Pinus strobussite_012body5Pinus strobussite_020body6Pinus strobussite_035\n``````\n:::\n:::\n\n\n\n\n- Can be tricky working with multiple column datatypes\n- Don't use colors or text formatting in tabular data, and only include column names as metadata. All other notes, definitions, etc. should be in an external metadata file (e.g. data dictionary)\n\n### Top References\n\n- Wickham, H. (2014). Tidy Data. Journal of Statistical Software, 59(10), 1--23.\\\n \n- Data Sharing and Management Snafu in 3 Short Acts (video)\\\n \n- Tips for working with data in BASH\\\n \n- Data Organization in Spreadsheets for Ecologists\\\n \n- Cleaning Data and Quality Control\\\n \n\n## Follow ISO 8601 for dates\n\n\n\n\n::: {.cell layout-align=\"center\"}\n::: {.cell-output-display}\n![https://imgs.xkcd.com/comics/iso_8601.png](https://imgs.xkcd.com/comics/iso_8601.png){fig-align='center' width=40%}\n:::\n:::\n\n\n\n\n### Why?\n\n- Internationally accepted format used across multiple schemas (e.g. `Darwin Core`, `EML`, `ISO 19115`)\n- Removes ambiguity related to timezone, daylight savings time changes, and time of day\n- Better software integration of time date/time elements\n\n### Key Information\n\n- UTC (AKA `Zulu` or `GMT`): Coordinated Universal Time (UTC) is the primary time standard by which the world regulates clocks and time. It is time relative to `0°` longitude and is not adjusted for daylight saving time. ([from Wikipedia](https://en.wikipedia.org/wiki/ISO_8601)).\n- Conversion to UTC, or between time zones, may depend on daylight savings\n\n*Examples: April 3, 2023 standardized to ISO 8601*\n\n\n\n\n::: {.cell}\n::: {.cell-output-display}\n``````{=openxml}\n\nheader1DescriptionWritten in ISO 8601body1Date2023-04-03body2Date and Time with timezone offset2023-04-03T18:29:38+00:00body3Date and Time in UTC2023-04-03T18:29:38Zbody4Time Interval in UTC (April 3 - 5, 2023)2023-04-03T18:29:38Z/2023-04-05T00:29:38Z\n``````\n:::\n:::\n\n\n\n\n*Examples: different styles of timezone annotation*\n\n\n\n\n::: {.cell}\n::: {.cell-output-display}\n``````{=openxml}\n\nheader1DescriptionWritten in ISO 8601body1Date2023-04-03body2Date and Time with timezone offset2023-04-03T18:29:38+00:00body3Date and Time in UTC2023-04-03T18:29:38Zbody4Time Interval in UTC (April 3 - 5, 2023)2023-04-03T18:29:38Z/2023-04-05T00:29:38Z\n``````\n:::\n:::\n\n\n\n\n### Top References\n\n- ISO 8601 wiki: \n- R package lubridate, OlsonNames()\n- Python go-to package, datetime \n- Article on datetime uncertainty: \n- Map of offset from UTC: \n- Nice time converter: \n\n## Match scientific names to a taxonomic authority\n\n### Why?\n\n- To integrate or aggregate datasets, we need a common frame of reference for taxonomic name\n- Provides an anchor for the taxonomy as scientific understanding evolves.\n\n### Key Information\n\n- Definition: As used here, a taxonomic authority is an online resource that maintains up-to-date species-level classification information and provides persistent identifiers for taxonomic classifications. Example: For the species *Balaenoptera borealis* (Lesson, 1828), the WoRMS taxonomic authority ID link is and the LSID is `urn:lsid:marinespecies.org:taxname:137088`.\n- Use an existing taxonomic authority (e.g. [World Register of Marine Species](https://www.marinespecies.org) , [Integrated Taxonomic Information System](https://itis.gov/) , [NCBI taxonomy](https://www.ncbi.nlm.nih.gov/taxonomy)) and include the authority who manages said information in your metadata\n- List of many authorities can be found here: \n- Make yourself aware of the structure, limits, and history of the authority you are using.\n- Adopt standard binomial nomenclature, when possible\n- When possible, reference the unique identifier in addition to the nomenclature.\n- Always save and document the originally recorded name.\n- Put notes about identification uncertainty in a separate column.\n- Many authorities have APIs through which you can match names to identifiers.\n\n### Top References\n\n- R packages\n - taxize is a taxonomic toolbelt for R. taxize wraps APIs for a large suite of taxonomic databases available on the web\\\n \n - worrms is an API client for [World Register of Marine Species](http://www.marinespecies.org/)\\\n \n - worms: another API client for WoRMS\\\n \n - Ritis: API client for ITIS \\\n- Python packages\n - WoRMS API client\\\n \n- Global Names Resolver to compare taxonomic concepts across authorities\\\n \n- Article: Recommendations for the Standardisation of Open Taxonomic Nomenclature for Image-Based Identifications\\\n \n- TDWG 2022 Keynote: Richard Pyle, \"An Introduction to the Scientific Names of Organisms and the Taxon Concepts they Represent\"\\\n \n\n## Record latitude and longitude in decimal degrees in WGS84\n\n\n\n\n::: {.cell layout-align=\"center\"}\n::: {.cell-output-display}\n![https://imgs.xkcd.com/comics/coordinate_precision.png](https://imgs.xkcd.com/comics/coordinate_precision.png){fig-align='center' width=40%}\n:::\n:::\n\n\n\n\n### Why?\n\n- Users have to know where you collected this data, which requires a latitude, longitude, reference system and uncertainty.\n- Decimal-degrees avoids special symbols (`°` or `‘`) which is preferable for machine readable formats\n- `WGS84` is a reference coordinate system that is widely used and incorporated in many GPS units and tools, and recognized as a standard by many government agencies.\n\n### Key Information\n\n- If possible, encourage data providers to confirm, and record, the WGS84 datum prior to data collection.\n- Understand and report the device/instrument uncertainty associated with your coordinates because it affects the usability of your data.\n- Consider including the vertical component (altitude, depth, height off bottom, elevation, etc)\n- Generally speaking, `degrees-minutes-seconds (DMS)` can be converted to `decimal-degrees (DD)` by:\n - `DD = d + (min/60) + (sec/3600)`\n - Watch out for mixed formats, like degrees, `decimal-minutes (DDM)`.\n- Degrees West and South become negative in DD.\n - Values for longitude range from `-180` to `180`, inclusive.\n - Values for latitude range from `-90` to `90`, inclusive.\n\n*Example Coordinates*\n\n\n\n\n::: {.cell}\n::: {.cell-output-display}\n``````{=openxml}\n\nheader1FormatExamplebody1Decimal Degrees (DD)30.50833333body2Degrees Minutes Seconds (DMS)30° 15' 10 Nbody3Degrees Decimal Minutes (DM or DDM)30° 15.1667 N\n``````\n:::\n:::\n\n\n\n\n### Top References\n\n- Existing R/python/ESRI packages/functions\n - R - measurements \n - EML (find \"bounding Coordinates)\n - CF \n- Getting lat/lon to decimal degrees\\\n \n- Some background on precision\n - \n - \n- DMS to DD calculator\\\n -- The three most commonly used datums are WGS84, NAD83, and NAD27. A more complete list can be found here: \n\n## Use persistent unique identifiers\n\n### Why?\n\n- It can be useful to have unique identifiers to unambiguously identify granules of information, e.g. dataset, collection, database, taxonomic concept, etc. This will allow users to precisely refer to the data and allow your data to remain identifiable when aggregated with other datasets.\n- To be able to uniquely identify a record in your data system or across data systems. Useful to create relational databases or merge records.\n- Although it increases workload, it safeguards against confusion and inefficiency in the future.\n\n### Key Information\n\n- There are good reasons to keep an identifier opaque, i.e. it does not indicate anything about the content of information it points to. However, there are also transparent, or semi-opaque identifiers in use that take advantage of semantics to guide humans as well as machines.\n- One way to create a unique identifier is concatenation of sampling event, location, time, enumeration of unique observation or event. (e.g. `Station_95_Date_09JAN1997:14:35:00.000`)\n- Some prefer using opaque identifiers. (e.g. `10FC9784-B30F-48ED-8DB5-FF65A2A9934E`)\n- If there is an existing persistent unique identifier, it's usually a good idea to use it (i.e. when using a taxonomic authority like WoRMS and applying their LSID).\n- It is important to manage any identifiers you create, if they are not managed by an authority (e.g. DOIs).\n- Important that it be persistent (consider samples possibly moving between institutions)\n\n*Examples of PIDs*\n\n\n\n\n::: {.cell}\n::: {.cell-output-display}\n``````{=openxml}\n\nheader1Type of PIDUse CaseExamplebody1Digital Object Identifier (DOI)Actionable persistent link for papers, data, and other digital objectshttps://doi.org/10.6084/m9.figshare.16806712.v2body2International Geo Sample Number (IGSN)Persistent identifier for physical sampleshttp://igsn.org/AU1243>body3Life Science Identifier (LSID)Persistent structured method for biologically significant dataurn:lsid:marinespecies.org:taxname:218214body4Open Researcher and Contributor ID (ORCID)Persistent actionable link for individualshttps://orcid.org/0000-0002-4391-107X\n``````\n:::\n:::\n\n\n\n\n### Top References\n\n- Software and Packages to generate uuids:\n - R - uuid \n - python - uuid \n - \n - \n- Guidance on how to use GUIDs (Globally Unique Identifiers) to meet specific requirements of the biodiversity information community\\\n \n- Use of globally unique identifiers (GUIDs) to link herbarium specimen records to physical specimens\\\n \n- A Beginner's Guide to Persistent Identifiers\\\n \n", + "markdown": "# Make Your Data Software Ready\n\n## Use non-proprietary formats\n\n### Why?\n\n- Allows data to be useful in perpetuity by ensuring data readability and reusability across multiple platforms.\n- To align better with the FAIR principles (findability, accessibility, interoperability, reusability)\n- Makes data more socially equitable, supporting open science. Proprietary formats can depend on software that require licenses, which not everyone can afford/has access to.\n\n### Key Information\n\n- *Non-proprietary formats* are supported by more than one developer and can be accessed with different software systems. For example, comma separated values (CSV) format is becoming an increasingly popular non-proprietary format.\n- A [*proprietary file format*](https://en.wikipedia.org/wiki/Proprietary_file_format) is a file format of a company, organization, or individual that contains data that is ordered and stored according to a particular encoding-scheme, designed by the company or organization to be secret or with restricted access, such that the decoding and interpretation of this stored data is easily accomplished only with particular software or hardware that the company itself has developed. There may also be costs associated with it and access may be limited. Examples include `Microsoft Excel (xlsx)` and `ESRI shapefiles (shp)`.\n- Many applications (e.g. Microsoft Office) allow exporting in multiple formats.\n\n### Top References\n\n- Table of commonly used formats for common data types\\\n \n\n- A more detailed table that is specific to US Federal records management\\\n \n\n## Structure tabular data in tidy/long format\n\n### Why?\n\n*This is specifically intended for tabular data*\n\n- There is a clear and easy to understand structure that can make your data more machine readable and easier to analyze/visualize\n - Clear structure: one observation per row\n - Data are as atomic as possible (e.g., don't mix types in field)\n- In the biological data community, tidy formats are more likely to work with commonly-used software\n- Easier to aggregate data across multiple files\n\n### Key Information\n\nExample of Wide Format\n\n\n\n\n::: {.cell}\n::: {.cell-output-display}\n``````{=openxml}\n\nheader1speciessite_01site_02site_03body1Tilia americana440body2Pinus strobus151\n``````\n:::\n:::\n\n\n\n\nExample of Long Format\n\n\n\n\n::: {.cell}\n::: {.cell-output-display}\n``````{=openxml}\n\nheader1speciessitecountbody1Tilia americanasite_014body2Tilia americanasite_020body3Tilia americanasite_031body4Pinus strobussite_013body5Pinus strobussite_024body6Pinus strobussite_034\n``````\n:::\n:::\n\n\n\n\n- Can be tricky working with multiple column datatypes\n- Don't use colors or text formatting in tabular data, and only include column names as metadata. All other notes, definitions, etc. should be in an external metadata file (e.g. data dictionary)\n\n### Top References\n\n- Wickham, H. (2014). Tidy Data. Journal of Statistical Software, 59(10), 1--23.\\\n \n- Data Sharing and Management Snafu in 3 Short Acts (video)\\\n \n- Tips for working with data in BASH\\\n \n- Data Organization in Spreadsheets for Ecologists\\\n \n- Cleaning Data and Quality Control\\\n \n\n## Follow ISO 8601 for dates\n\n\n\n\n::: {.cell layout-align=\"center\"}\n::: {.cell-output-display}\n![https://imgs.xkcd.com/comics/iso_8601.png](https://imgs.xkcd.com/comics/iso_8601.png){fig-align='center' width=40%}\n:::\n:::\n\n\n\n\n### Why?\n\n- Internationally accepted format used across multiple schemas (e.g. `Darwin Core`, `EML`, `ISO 19115`)\n- Removes ambiguity related to timezone, daylight savings time changes, and time of day\n- Better software integration of time date/time elements\n\n### Key Information\n\n- UTC (AKA `Zulu` or `GMT`): Coordinated Universal Time (UTC) is the primary time standard by which the world regulates clocks and time. It is time relative to `0°` longitude and is not adjusted for daylight saving time. ([from Wikipedia](https://en.wikipedia.org/wiki/ISO_8601)).\n- Conversion to UTC, or between time zones, may depend on daylight savings\n\n*Examples: April 3, 2023 standardized to ISO 8601*\n\n\n\n\n::: {.cell}\n::: {.cell-output-display}\n``````{=openxml}\n\nheader1DescriptionWritten in ISO 8601body1Date2023-04-03body2Date and Time with timezone offset2023-04-03T18:29:38+00:00body3Date and Time in UTC2023-04-03T18:29:38Zbody4Time Interval in UTC (April 3 - 5, 2023)2023-04-03T18:29:38Z/2023-04-05T00:29:38Z\n``````\n:::\n:::\n\n\n\n\n*Examples: different styles of timezone annotation*\n\n\n\n\n::: {.cell}\n::: {.cell-output-display}\n``````{=openxml}\n\nheader1DescriptionWritten in ISO 8601body1Date2023-04-03body2Date and Time with timezone offset2023-04-03T18:29:38+00:00body3Date and Time in UTC2023-04-03T18:29:38Zbody4Time Interval in UTC (April 3 - 5, 2023)2023-04-03T18:29:38Z/2023-04-05T00:29:38Z\n``````\n:::\n:::\n\n\n\n\n### Top References\n\n- ISO 8601 wiki: \n- R package lubridate, OlsonNames()\n- Python go-to package, datetime \n- Article on datetime uncertainty: \n- Map of offset from UTC: \n- Nice time converter: \n\n## Match scientific names to a taxonomic authority\n\n### Why?\n\n- To integrate or aggregate datasets, we need a common frame of reference for taxonomic name\n- Provides an anchor for the taxonomy as scientific understanding evolves.\n\n### Key Information\n\n- Definition: As used here, a taxonomic authority is an online resource that maintains up-to-date species-level classification information and provides persistent identifiers for taxonomic classifications. Example: For the species *Balaenoptera borealis* (Lesson, 1828), the WoRMS taxonomic authority ID link is and the LSID is `urn:lsid:marinespecies.org:taxname:137088`.\n- Use an existing taxonomic authority (e.g. [World Register of Marine Species](https://www.marinespecies.org) , [Integrated Taxonomic Information System](https://itis.gov/) , [NCBI taxonomy](https://www.ncbi.nlm.nih.gov/taxonomy)) and include the authority who manages said information in your metadata\n- List of many authorities can be found here: \n- Make yourself aware of the structure, limits, and history of the authority you are using.\n- Adopt standard binomial nomenclature, when possible\n- When possible, reference the unique identifier in addition to the nomenclature.\n- Always save and document the originally recorded name.\n- Put notes about identification uncertainty in a separate column.\n- Many authorities have APIs through which you can match names to identifiers.\n\n### Top References\n\n- R packages\n - taxize is a taxonomic toolbelt for R. taxize wraps APIs for a large suite of taxonomic databases available on the web\\\n \n - worrms is an API client for [World Register of Marine Species](http://www.marinespecies.org/)\\\n \n - worms: another API client for WoRMS\\\n \n - Ritis: API client for ITIS \\\n- Python packages\n - WoRMS API client\\\n \n- Global Names Resolver to compare taxonomic concepts across authorities\\\n \n- Article: Recommendations for the Standardisation of Open Taxonomic Nomenclature for Image-Based Identifications\\\n \n- TDWG 2022 Keynote: Richard Pyle, \"An Introduction to the Scientific Names of Organisms and the Taxon Concepts they Represent\"\\\n \n\n## Record latitude and longitude in decimal degrees in WGS84\n\n\n\n\n::: {.cell layout-align=\"center\"}\n::: {.cell-output-display}\n![https://imgs.xkcd.com/comics/coordinate_precision.png](https://imgs.xkcd.com/comics/coordinate_precision.png){fig-align='center' width=40%}\n:::\n:::\n\n\n\n\n### Why?\n\n- Users have to know where you collected this data, which requires a latitude, longitude, reference system and uncertainty.\n- Decimal-degrees avoids special symbols (`°` or `‘`) which is preferable for machine readable formats\n- `WGS84` is a reference coordinate system that is widely used and incorporated in many GPS units and tools, and recognized as a standard by many government agencies.\n\n### Key Information\n\n- If possible, encourage data providers to confirm, and record, the WGS84 datum prior to data collection.\n- Understand and report the device/instrument uncertainty associated with your coordinates because it affects the usability of your data.\n- Consider including the vertical component (altitude, depth, height off bottom, elevation, etc)\n- Generally speaking, `degrees-minutes-seconds (DMS)` can be converted to `decimal-degrees (DD)` by:\n - `DD = d + (min/60) + (sec/3600)`\n - Watch out for mixed formats, like degrees, `decimal-minutes (DDM)`.\n- Degrees West and South become negative in DD.\n - Values for longitude range from `-180` to `180`, inclusive.\n - Values for latitude range from `-90` to `90`, inclusive.\n\n*Example Coordinates*\n\n\n\n\n::: {.cell}\n::: {.cell-output-display}\n``````{=openxml}\n\nheader1FormatExamplebody1Decimal Degrees (DD)30.50833333body2Degrees Minutes Seconds (DMS)30° 15' 10 Nbody3Degrees Decimal Minutes (DM or DDM)30° 15.1667 N\n``````\n:::\n:::\n\n\n\n\n### Top References\n\n- Existing R/python/ESRI packages/functions\n - R - measurements \n - EML (find \"bounding Coordinates)\n - CF \n- Getting lat/lon to decimal degrees\\\n \n- Some background on precision\n - \n - \n- DMS to DD calculator\\\n -- The three most commonly used datums are WGS84, NAD83, and NAD27. A more complete list can be found here: \n\n## Use persistent unique identifiers\n\n### Why?\n\n- It can be useful to have unique identifiers to unambiguously identify granules of information, e.g. dataset, collection, database, taxonomic concept, etc. This will allow users to precisely refer to the data and allow your data to remain identifiable when aggregated with other datasets.\n- To be able to uniquely identify a record in your data system or across data systems. Useful to create relational databases or merge records.\n- Although it increases workload, it safeguards against confusion and inefficiency in the future.\n\n### Key Information\n\n- There are good reasons to keep an identifier opaque, i.e. it does not indicate anything about the content of information it points to. However, there are also transparent, or semi-opaque identifiers in use that take advantage of semantics to guide humans as well as machines.\n- One way to create a unique identifier is concatenation of sampling event, location, time, enumeration of unique observation or event. (e.g. `Station_95_Date_09JAN1997:14:35:00.000`)\n- Some prefer using opaque identifiers. (e.g. `10FC9784-B30F-48ED-8DB5-FF65A2A9934E`)\n- If there is an existing persistent unique identifier, it's usually a good idea to use it (i.e. when using a taxonomic authority like WoRMS and applying their LSID).\n- It is important to manage any identifiers you create, if they are not managed by an authority (e.g. DOIs).\n- Important that it be persistent (consider samples possibly moving between institutions)\n\n*Examples of PIDs*\n\n\n\n\n::: {.cell}\n::: {.cell-output-display}\n``````{=openxml}\n\nheader1Type of PIDUse CaseExamplebody1Digital Object Identifier (DOI)Actionable persistent link for papers, data, and other digital objectshttps://doi.org/10.6084/m9.figshare.16806712.v2body2International Geo Sample Number (IGSN)Persistent identifier for physical sampleshttp://igsn.org/AU1243>body3Life Science Identifier (LSID)Persistent structured method for biologically significant dataurn:lsid:marinespecies.org:taxname:218214body4Open Researcher and Contributor ID (ORCID)Persistent actionable link for individualshttps://orcid.org/0000-0002-4391-107X\n``````\n:::\n:::\n\n\n\n\n### Top References\n\n- Software and Packages to generate uuids:\n - R - uuid \n - python - uuid \n - \n - \n- Guidance on how to use GUIDs (Globally Unique Identifiers) to meet specific requirements of the biodiversity information community\\\n \n- Use of globally unique identifiers (GUIDs) to link herbarium specimen records to physical specimens\\\n \n- A Beginner's Guide to Persistent Identifiers\\\n \n", "supporting": [ "SOFTWARE_READY_files" ], diff --git a/.quarto/_freeze/SOFTWARE_READY/execute-results/html.json b/.quarto/_freeze/SOFTWARE_READY/execute-results/html.json index df761b9..283dfdd 100644 --- a/.quarto/_freeze/SOFTWARE_READY/execute-results/html.json +++ b/.quarto/_freeze/SOFTWARE_READY/execute-results/html.json @@ -1,7 +1,7 @@ { - "hash": "f7618691fb5182b0a3a787b81d883471", + "hash": "0668efee2c4de4b6e1303759e17ba606", "result": { - "markdown": "# Make Your Data Software Ready {.unnumbered}\n\n## Use non-proprietary formats\n\n### Why?\n\n- Allows data to be useful in perpetuity by ensuring data readability and reusability across multiple platforms.\n- To align better with the FAIR principles (findability, accessibility, interoperability, reusability)\n- Makes data more socially equitable, supporting open science. Proprietary formats can depend on software that require licenses, which not everyone can afford/has access to.\n\n### Key Information\n\n- *Non-proprietary formats* are supported by more than one developer and can be accessed with different software systems. For example, comma separated values (CSV) format is becoming an increasingly popular non-proprietary format.\n- A [*proprietary file format*](https://en.wikipedia.org/wiki/Proprietary_file_format) is a file format of a company, organization, or individual that contains data that is ordered and stored according to a particular encoding-scheme, designed by the company or organization to be secret or with restricted access, such that the decoding and interpretation of this stored data is easily accomplished only with particular software or hardware that the company itself has developed. There may also be costs associated with it and access may be limited. Examples include `Microsoft Excel (xlsx)` and `ESRI shapefiles (shp)`.\n- Many applications (e.g. Microsoft Office) allow exporting in multiple formats.\n\n### Top References\n\n- Table of commonly used formats for common data types\\\n \n \n- A more detailed table that is specific to US Federal records management\\\n \n\n## Structure tabular data in tidy/long format\n\n### Why?\n\n*This is specifically intended for tabular data*\n\n- There is a clear and easy to understand structure that can make your data more machine readable and easier to analyze/visualize\n - Clear structure: one observation per row\n - Data are as atomic as possible (e.g., don't mix types in field)\n- In the biological data community, tidy formats are more likely to work with commonly-used software\n- Easier to aggregate data across multiple files\n\n### Key Information\n\nExample of Wide Format\n\n\n::: {.cell}\n::: {.cell-output-display}\n```{=html}\n

species

site_01

site_02

site_03

Tilia americana

1

0

2

Pinus strobus

2

1

1

\n```\n:::\n:::\n\n\nExample of Long Format\n\n\n::: {.cell}\n::: {.cell-output-display}\n```{=html}\n

species

site

count

Tilia americana

site_01

3

Tilia americana

site_02

3

Tilia americana

site_03

4

Pinus strobus

site_01

2

Pinus strobus

site_02

2

Pinus strobus

site_03

1

\n```\n:::\n:::\n\n\n- Can be tricky working with multiple column datatypes\n- Don't use colors or text formatting in tabular data, and only include column names as metadata. All other notes, definitions, etc. should be in an external metadata file (e.g. data dictionary)\n\n### Top References\n\n- Wickham, H. (2014). Tidy Data. Journal of Statistical Software, 59(10), 1--23.\\\n \n- Data Sharing and Management Snafu in 3 Short Acts (video)\\\n \n- Tips for working with data in BASH\\\n \n- Data Organization in Spreadsheets for Ecologists\\\n \n- Cleaning Data and Quality Control\\\n \n\n## Follow ISO 8601 for dates\n\n\n::: {.cell layout-align=\"center\"}\n::: {.cell-output-display}\n![https://imgs.xkcd.com/comics/iso_8601.png](https://imgs.xkcd.com/comics/iso_8601.png){fig-align='center' width=40%}\n:::\n:::\n\n\n### Why?\n\n- Internationally accepted format used across multiple schemas (e.g. `Darwin Core`, `EML`, `ISO 19115`)\n- Removes ambiguity related to timezone, daylight savings time changes, and time of day\n- Better software integration of time date/time elements\n\n### Key Information\n\n- UTC (AKA `Zulu` or `GMT`): Coordinated Universal Time (UTC) is the primary time standard by which the world regulates clocks and time. It is time relative to `0°` longitude and is not adjusted for daylight saving time. ([from Wikipedia](https://en.wikipedia.org/wiki/ISO_8601)).\n- Conversion to UTC, or between time zones, may depend on daylight savings\n\n*Examples: April 3, 2023 standardized to ISO 8601*\n\n\n::: {.cell}\n::: {.cell-output-display}\n```{=html}\n

Description

Written in ISO 8601

Date

2023-04-03

Date and Time with timezone offset

2023-04-03T18:29:38+00:00

Date and Time in UTC

2023-04-03T18:29:38Z

Time Interval in UTC (April 3 - 5, 2023)

2023-04-03T18:29:38Z/2023-04-05T00:29:38Z

\n```\n:::\n:::\n\n\n*Examples: different styles of timezone annotation*\n\n\n::: {.cell}\n::: {.cell-output-display}\n```{=html}\n

Description

Written in ISO 8601

Date

2023-04-03

Date and Time with timezone offset

2023-04-03T18:29:38+00:00

Date and Time in UTC

2023-04-03T18:29:38Z

Time Interval in UTC (April 3 - 5, 2023)

2023-04-03T18:29:38Z/2023-04-05T00:29:38Z

\n```\n:::\n:::\n\n\n### Top References\n\n- ISO 8601 wiki: \n- R package lubridate, OlsonNames()\n- Python go-to package, datetime \n- Article on datetime uncertainty: \n- Map of offset from UTC: \n- Nice time converter: \n\n## Match scientific names to a taxonomic authority\n\n### Why?\n\n- To integrate or aggregate datasets, we need a common frame of reference for taxonomic name\n- Provides an anchor for the taxonomy as scientific understanding evolves.\n\n### Key Information\n\n- Definition: As used here, a taxonomic authority is an online resource that maintains up-to-date species-level classification information and provides persistent identifiers for taxonomic classifications. Example: For the species *Balaenoptera borealis* (Lesson, 1828), the WoRMS taxonomic authority ID link is and the LSID is `urn:lsid:marinespecies.org:taxname:137088`.\n- Use an existing taxonomic authority (e.g. [World Register of Marine Species](https://www.marinespecies.org) , [Integrated Taxonomic Information System](https://itis.gov/) , [NCBI taxonomy](https://www.ncbi.nlm.nih.gov/taxonomy)) and include the authority who manages said information in your metadata\n- List of many authorities can be found here: \n- Make yourself aware of the structure, limits, and history of the authority you are using.\n- Adopt standard binomial nomenclature, when possible\n- When possible, reference the unique identifier in addition to the nomenclature.\n- Always save and document the originally recorded name.\n- Put notes about identification uncertainty in a separate column.\n- Many authorities have APIs through which you can match names to identifiers.\n\n### Top References\n\n- R packages\n - taxize is a taxonomic toolbelt for R. taxize wraps APIs for a large suite of taxonomic databases available on the web\\\n \n - worrms is an API client for [World Register of Marine Species](http://www.marinespecies.org/)\\\n \n - worms: another API client for WoRMS\\\n \n - Ritis: API client for ITIS \\\n- Python packages\n - WoRMS API client\\\n \n- Global Names Resolver to compare taxonomic concepts across authorities\\\n \n- Article: Recommendations for the Standardisation of Open Taxonomic Nomenclature for Image-Based Identifications\\\n \n- TDWG 2022 Keynote: Richard Pyle, \"An Introduction to the Scientific Names of Organisms and the Taxon Concepts they Represent\"\\\n \n\n## Record latitude and longitude in decimal degrees in WGS84\n\n\n::: {.cell layout-align=\"center\"}\n::: {.cell-output-display}\n![https://imgs.xkcd.com/comics/coordinate_precision.png](https://imgs.xkcd.com/comics/coordinate_precision.png){fig-align='center' width=40%}\n:::\n:::\n\n\n### Why?\n\n- Users have to know where you collected this data, which requires a latitude, longitude, reference system and uncertainty.\n- Decimal-degrees avoids special symbols (`°` or `‘`) which is preferable for machine readable formats\n- `WGS84` is a reference coordinate system that is widely used and incorporated in many GPS units and tools, and recognized as a standard by many government agencies.\n\n### Key Information\n\n- If possible, encourage data providers to confirm, and record, the WGS84 datum prior to data collection.\n- Understand and report the device/instrument uncertainty associated with your coordinates because it affects the usability of your data.\n- Consider including the vertical component (altitude, depth, height off bottom, elevation, etc)\n- Generally speaking, `degrees-minutes-seconds (DMS)` can be converted to `decimal-degrees (DD)` by:\n - `DD = d + (min/60) + (sec/3600)`\n - Watch out for mixed formats, like degrees, `decimal-minutes (DDM)`.\n- Degrees West and South become negative in DD.\n - Values for longitude range from `-180` to `180`, inclusive.\n - Values for latitude range from `-90` to `90`, inclusive.\n\n*Example Coordinates*\n\n\n::: {.cell}\n::: {.cell-output-display}\n```{=html}\n

Format

Example

Decimal Degrees (DD)

30.50833333

Degrees Minutes Seconds (DMS)

30° 15' 10 N

Degrees Decimal Minutes (DM or DDM)

30° 15.1667 N

\n```\n:::\n:::\n\n\n### Top References\n\n- Existing R/python/ESRI packages/functions\n - R - measurements \n - EML (find \"bounding Coordinates)\n - CF \n- Getting lat/lon to decimal degrees\\\n \n- Some background on precision\n - \n - \n- DMS to DD calculator\\\n -- The three most commonly used datums are WGS84, NAD83, and NAD27. A more complete list can be found here: \n\n## Use persistent unique identifiers\n\n### Why?\n\n- It can be useful to have unique identifiers to unambiguously identify granules of information, e.g. dataset, collection, database, taxonomic concept, etc. This will allow users to precisely refer to the data and allow your data to remain identifiable when aggregated with other datasets.\n- To be able to uniquely identify a record in your data system or across data systems. Useful to create relational databases or merge records.\n- Although it increases workload, it safeguards against confusion and inefficiency in the future.\n\n### Key Information\n\n- There are good reasons to keep an identifier opaque, i.e. it does not indicate anything about the content of information it points to. However, there are also transparent, or semi-opaque identifiers in use that take advantage of semantics to guide humans as well as machines.\n- One way to create a unique identifier is concatenation of sampling event, location, time, enumeration of unique observation or event. (e.g. `Station_95_Date_09JAN1997:14:35:00.000`)\n- Some prefer using opaque identifiers. (e.g. `10FC9784-B30F-48ED-8DB5-FF65A2A9934E`)\n- If there is an existing persistent unique identifier, it's usually a good idea to use it (i.e. when using a taxonomic authority like WoRMS and applying their LSID).\n- It is important to manage any identifiers you create, if they are not managed by an authority (e.g. DOIs).\n- Important that it be persistent (consider samples possibly moving between institutions)\n\n*Examples of PIDs*\n\n\n::: {.cell}\n::: {.cell-output-display}\n```{=html}\n

Type of PID

Use Case

Example

Digital Object Identifier (DOI)

Actionable persistent link for papers, data, and other digital objects

https://doi.org/10.6084/m9.figshare.16806712.v2

International Geo Sample Number (IGSN)

Persistent identifier for physical samples

http://igsn.org/AU1243>

Life Science Identifier (LSID)

Persistent structured method for biologically significant data

urn:lsid:marinespecies.org:taxname:218214

Open Researcher and Contributor ID (ORCID)

Persistent actionable link for individuals

https://orcid.org/0000-0002-4391-107X

\n```\n:::\n:::\n\n\n### Top References\n\n- Software and Packages to generate uuids:\n - R - uuid \n - python - uuid \n - \n - \n- Guidance on how to use GUIDs (Globally Unique Identifiers) to meet specific requirements of the biodiversity information community\\\n \n- Use of globally unique identifiers (GUIDs) to link herbarium specimen records to physical specimens\\\n \n- A Beginner's Guide to Persistent Identifiers\\\n \n", + "markdown": "# Make Your Data Software Ready\n\n## Use non-proprietary formats\n\n### Why?\n\n- Allows data to be useful in perpetuity by ensuring data readability and reusability across multiple platforms.\n- To align better with the FAIR principles (findability, accessibility, interoperability, reusability)\n- Makes data more socially equitable, supporting open science. Proprietary formats can depend on software that require licenses, which not everyone can afford/has access to.\n\n### Key Information\n\n- *Non-proprietary formats* are supported by more than one developer and can be accessed with different software systems. For example, comma separated values (CSV) format is becoming an increasingly popular non-proprietary format.\n- A [*proprietary file format*](https://en.wikipedia.org/wiki/Proprietary_file_format) is a file format of a company, organization, or individual that contains data that is ordered and stored according to a particular encoding-scheme, designed by the company or organization to be secret or with restricted access, such that the decoding and interpretation of this stored data is easily accomplished only with particular software or hardware that the company itself has developed. There may also be costs associated with it and access may be limited. Examples include `Microsoft Excel (xlsx)` and `ESRI shapefiles (shp)`.\n- Many applications (e.g. Microsoft Office) allow exporting in multiple formats.\n\n### Top References\n\n- Table of commonly used formats for common data types\\\n \n\n- A more detailed table that is specific to US Federal records management\\\n \n\n## Structure tabular data in tidy/long format\n\n### Why?\n\n*This is specifically intended for tabular data*\n\n- There is a clear and easy to understand structure that can make your data more machine readable and easier to analyze/visualize\n - Clear structure: one observation per row\n - Data are as atomic as possible (e.g., don't mix types in field)\n- In the biological data community, tidy formats are more likely to work with commonly-used software\n- Easier to aggregate data across multiple files\n\n### Key Information\n\nExample of Wide Format\n\n\n::: {.cell}\n::: {.cell-output-display}\n```{=html}\n

species

site_01

site_02

site_03

Tilia americana

5

4

5

Pinus strobus

4

2

0

\n```\n:::\n:::\n\n\nExample of Long Format\n\n\n::: {.cell}\n::: {.cell-output-display}\n```{=html}\n

species

site

count

Tilia americana

site_01

3

Tilia americana

site_02

3

Tilia americana

site_03

0

Pinus strobus

site_01

2

Pinus strobus

site_02

5

Pinus strobus

site_03

5

\n```\n:::\n:::\n\n\n- Can be tricky working with multiple column datatypes\n- Don't use colors or text formatting in tabular data, and only include column names as metadata. All other notes, definitions, etc. should be in an external metadata file (e.g. data dictionary)\n\n### Top References\n\n- Wickham, H. (2014). Tidy Data. Journal of Statistical Software, 59(10), 1--23.\\\n \n- Data Sharing and Management Snafu in 3 Short Acts (video)\\\n \n- Tips for working with data in BASH\\\n \n- Data Organization in Spreadsheets for Ecologists\\\n \n- Cleaning Data and Quality Control\\\n \n\n## Follow ISO 8601 for dates\n\n\n::: {.cell layout-align=\"center\"}\n::: {.cell-output-display}\n![https://imgs.xkcd.com/comics/iso_8601.png](https://imgs.xkcd.com/comics/iso_8601.png){fig-align='center' width=40%}\n:::\n:::\n\n\n### Why?\n\n- Internationally accepted format used across multiple schemas (e.g. `Darwin Core`, `EML`, `ISO 19115`)\n- Removes ambiguity related to timezone, daylight savings time changes, and time of day\n- Better software integration of time date/time elements\n\n### Key Information\n\n- UTC (AKA `Zulu` or `GMT`): Coordinated Universal Time (UTC) is the primary time standard by which the world regulates clocks and time. It is time relative to `0°` longitude and is not adjusted for daylight saving time. ([from Wikipedia](https://en.wikipedia.org/wiki/ISO_8601)).\n- Conversion to UTC, or between time zones, may depend on daylight savings\n\n*Examples: April 3, 2023 standardized to ISO 8601*\n\n\n::: {.cell}\n::: {.cell-output-display}\n```{=html}\n

Description

Written in ISO 8601

Date

2023-04-03

Date and Time with timezone offset

2023-04-03T18:29:38+00:00

Date and Time in UTC

2023-04-03T18:29:38Z

Time Interval in UTC (April 3 - 5, 2023)

2023-04-03T18:29:38Z/2023-04-05T00:29:38Z

\n```\n:::\n:::\n\n\n*Examples: different styles of timezone annotation*\n\n\n::: {.cell}\n::: {.cell-output-display}\n```{=html}\n

Description

Written in ISO 8601

Date

2023-04-03

Date and Time with timezone offset

2023-04-03T18:29:38+00:00

Date and Time in UTC

2023-04-03T18:29:38Z

Time Interval in UTC (April 3 - 5, 2023)

2023-04-03T18:29:38Z/2023-04-05T00:29:38Z

\n```\n:::\n:::\n\n\n### Top References\n\n- ISO 8601 wiki: \n- R package lubridate, OlsonNames()\n- Python go-to package, datetime \n- Article on datetime uncertainty: \n- Map of offset from UTC: \n- Nice time converter: \n\n## Match scientific names to a taxonomic authority\n\n### Why?\n\n- To integrate or aggregate datasets, we need a common frame of reference for taxonomic name\n- Provides an anchor for the taxonomy as scientific understanding evolves.\n\n### Key Information\n\n- Definition: As used here, a taxonomic authority is an online resource that maintains up-to-date species-level classification information and provides persistent identifiers for taxonomic classifications. Example: For the species *Balaenoptera borealis* (Lesson, 1828), the WoRMS taxonomic authority ID link is and the LSID is `urn:lsid:marinespecies.org:taxname:137088`.\n- Use an existing taxonomic authority (e.g. [World Register of Marine Species](https://www.marinespecies.org) , [Integrated Taxonomic Information System](https://itis.gov/) , [NCBI taxonomy](https://www.ncbi.nlm.nih.gov/taxonomy)) and include the authority who manages said information in your metadata\n- List of many authorities can be found here: \n- Make yourself aware of the structure, limits, and history of the authority you are using.\n- Adopt standard binomial nomenclature, when possible\n- When possible, reference the unique identifier in addition to the nomenclature.\n- Always save and document the originally recorded name.\n- Put notes about identification uncertainty in a separate column.\n- Many authorities have APIs through which you can match names to identifiers.\n\n### Top References\n\n- R packages\n - taxize is a taxonomic toolbelt for R. taxize wraps APIs for a large suite of taxonomic databases available on the web\\\n \n - worrms is an API client for [World Register of Marine Species](http://www.marinespecies.org/)\\\n \n - worms: another API client for WoRMS\\\n \n - Ritis: API client for ITIS \\\n- Python packages\n - WoRMS API client\\\n \n- Global Names Resolver to compare taxonomic concepts across authorities\\\n \n- Article: Recommendations for the Standardisation of Open Taxonomic Nomenclature for Image-Based Identifications\\\n \n- TDWG 2022 Keynote: Richard Pyle, \"An Introduction to the Scientific Names of Organisms and the Taxon Concepts they Represent\"\\\n \n\n## Record latitude and longitude in decimal degrees in WGS84\n\n\n::: {.cell layout-align=\"center\"}\n::: {.cell-output-display}\n![https://imgs.xkcd.com/comics/coordinate_precision.png](https://imgs.xkcd.com/comics/coordinate_precision.png){fig-align='center' width=40%}\n:::\n:::\n\n\n### Why?\n\n- Users have to know where you collected this data, which requires a latitude, longitude, reference system and uncertainty.\n- Decimal-degrees avoids special symbols (`°` or `‘`) which is preferable for machine readable formats\n- `WGS84` is a reference coordinate system that is widely used and incorporated in many GPS units and tools, and recognized as a standard by many government agencies.\n\n### Key Information\n\n- If possible, encourage data providers to confirm, and record, the WGS84 datum prior to data collection.\n- Understand and report the device/instrument uncertainty associated with your coordinates because it affects the usability of your data.\n- Consider including the vertical component (altitude, depth, height off bottom, elevation, etc)\n- Generally speaking, `degrees-minutes-seconds (DMS)` can be converted to `decimal-degrees (DD)` by:\n - `DD = d + (min/60) + (sec/3600)`\n - Watch out for mixed formats, like degrees, `decimal-minutes (DDM)`.\n- Degrees West and South become negative in DD.\n - Values for longitude range from `-180` to `180`, inclusive.\n - Values for latitude range from `-90` to `90`, inclusive.\n\n*Example Coordinates*\n\n\n::: {.cell}\n::: {.cell-output-display}\n```{=html}\n

Format

Example

Decimal Degrees (DD)

30.50833333

Degrees Minutes Seconds (DMS)

30° 15' 10 N

Degrees Decimal Minutes (DM or DDM)

30° 15.1667 N

\n```\n:::\n:::\n\n\n### Top References\n\n- Existing R/python/ESRI packages/functions\n - R - measurements \n - EML (find \"bounding Coordinates)\n - CF \n- Getting lat/lon to decimal degrees\\\n \n- Some background on precision\n - \n - \n- DMS to DD calculator\\\n -- The three most commonly used datums are WGS84, NAD83, and NAD27. A more complete list can be found here: \n\n## Use persistent unique identifiers\n\n### Why?\n\n- It can be useful to have unique identifiers to unambiguously identify granules of information, e.g. dataset, collection, database, taxonomic concept, etc. This will allow users to precisely refer to the data and allow your data to remain identifiable when aggregated with other datasets.\n- To be able to uniquely identify a record in your data system or across data systems. Useful to create relational databases or merge records.\n- Although it increases workload, it safeguards against confusion and inefficiency in the future.\n\n### Key Information\n\n- There are good reasons to keep an identifier opaque, i.e. it does not indicate anything about the content of information it points to. However, there are also transparent, or semi-opaque identifiers in use that take advantage of semantics to guide humans as well as machines.\n- One way to create a unique identifier is concatenation of sampling event, location, time, enumeration of unique observation or event. (e.g. `Station_95_Date_09JAN1997:14:35:00.000`)\n- Some prefer using opaque identifiers. (e.g. `10FC9784-B30F-48ED-8DB5-FF65A2A9934E`)\n- If there is an existing persistent unique identifier, it's usually a good idea to use it (i.e. when using a taxonomic authority like WoRMS and applying their LSID).\n- It is important to manage any identifiers you create, if they are not managed by an authority (e.g. DOIs).\n- Important that it be persistent (consider samples possibly moving between institutions)\n\n*Examples of PIDs*\n\n\n::: {.cell}\n::: {.cell-output-display}\n```{=html}\n

Type of PID

Use Case

Example

Digital Object Identifier (DOI)

Actionable persistent link for papers, data, and other digital objects

https://doi.org/10.6084/m9.figshare.16806712.v2

International Geo Sample Number (IGSN)

Persistent identifier for physical samples

http://igsn.org/AU1243>

Life Science Identifier (LSID)

Persistent structured method for biologically significant data

urn:lsid:marinespecies.org:taxname:218214

Open Researcher and Contributor ID (ORCID)

Persistent actionable link for individuals

https://orcid.org/0000-0002-4391-107X

\n```\n:::\n:::\n\n\n### Top References\n\n- Software and Packages to generate uuids:\n - R - uuid \n - python - uuid \n - \n - \n- Guidance on how to use GUIDs (Globally Unique Identifiers) to meet specific requirements of the biodiversity information community\\\n \n- Use of globally unique identifiers (GUIDs) to link herbarium specimen records to physical specimens\\\n \n- A Beginner's Guide to Persistent Identifiers\\\n \n", "supporting": [], "filters": [ "rmarkdown/pagebreak.lua" diff --git a/.quarto/_freeze/SOFTWARE_READY/execute-results/tex.json b/.quarto/_freeze/SOFTWARE_READY/execute-results/tex.json index 44e8065..ab38f8b 100644 --- a/.quarto/_freeze/SOFTWARE_READY/execute-results/tex.json +++ b/.quarto/_freeze/SOFTWARE_READY/execute-results/tex.json @@ -1,7 +1,7 @@ { - "hash": "f7618691fb5182b0a3a787b81d883471", + "hash": "0668efee2c4de4b6e1303759e17ba606", "result": { - "markdown": "# Make Your Data Software Ready {.unnumbered}\n\n## Use non-proprietary formats\n\n### Why?\n\n- Allows data to be useful in perpetuity by ensuring data readability and reusability across multiple platforms.\n- To align better with the FAIR principles (findability, accessibility, interoperability, reusability)\n- Makes data more socially equitable, supporting open science. Proprietary formats can depend on software that require licenses, which not everyone can afford/has access to.\n\n### Key Information\n\n- *Non-proprietary formats* are supported by more than one developer and can be accessed with different software systems. For example, comma separated values (CSV) format is becoming an increasingly popular non-proprietary format.\n- A [*proprietary file format*](https://en.wikipedia.org/wiki/Proprietary_file_format) is a file format of a company, organization, or individual that contains data that is ordered and stored according to a particular encoding-scheme, designed by the company or organization to be secret or with restricted access, such that the decoding and interpretation of this stored data is easily accomplished only with particular software or hardware that the company itself has developed. There may also be costs associated with it and access may be limited. Examples include `Microsoft Excel (xlsx)` and `ESRI shapefiles (shp)`.\n- Many applications (e.g. Microsoft Office) allow exporting in multiple formats.\n\n### Top References\n\n- Table of commonly used formats for common data types\\\n \n \n- A more detailed table that is specific to US Federal records management\\\n \n\n## Structure tabular data in tidy/long format\n\n### Why?\n\n*This is specifically intended for tabular data*\n\n- There is a clear and easy to understand structure that can make your data more machine readable and easier to analyze/visualize\n - Clear structure: one observation per row\n - Data are as atomic as possible (e.g., don't mix types in field)\n- In the biological data community, tidy formats are more likely to work with commonly-used software\n- Easier to aggregate data across multiple files\n\n### Key Information\n\nExample of Wide Format\n\n\n\n::: {.cell}\n::: {.cell-output-display}\n```{=latex}\n\\global\\setlength{\\Oldarrayrulewidth}{\\arrayrulewidth}\n\n\\global\\setlength{\\Oldtabcolsep}{\\tabcolsep}\n\n\\setlength{\\tabcolsep}{0pt}\n\n\\renewcommand*{\\arraystretch}{1.5}\n\n\n\n\\providecommand{\\ascline}[3]{\\noalign{\\global\\arrayrulewidth #1}\\arrayrulecolor[HTML]{#2}\\cline{#3}}\n\n\\begin{longtable}[c]{|p{1.13in}|p{0.78in}|p{0.78in}|p{0.78in}}\n\n\n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 1.13in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{species}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.78in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{site\\_01}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.78in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{site\\_02}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.78in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{site\\_03}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endfirsthead \n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 1.13in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{species}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.78in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{site\\_01}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.78in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{site\\_02}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.78in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{site\\_03}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endhead\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 1.13in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Tilia\\ americana}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.78in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{2}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.78in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{3}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.78in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{1}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedright}m{\\dimexpr 1.13in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Pinus\\ strobus}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.78in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{4}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.78in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{2}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.78in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{5}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\end{longtable}\n\n\n\n\\arrayrulecolor[HTML]{000000}\n\n\\global\\setlength{\\arrayrulewidth}{\\Oldarrayrulewidth}\n\n\\global\\setlength{\\tabcolsep}{\\Oldtabcolsep}\n\n\\renewcommand*{\\arraystretch}{1}\n```\n:::\n:::\n\n\n\nExample of Long Format\n\n\n\n::: {.cell}\n::: {.cell-output-display}\n```{=latex}\n\\global\\setlength{\\Oldarrayrulewidth}{\\arrayrulewidth}\n\n\\global\\setlength{\\Oldtabcolsep}{\\tabcolsep}\n\n\\setlength{\\tabcolsep}{0pt}\n\n\\renewcommand*{\\arraystretch}{1.5}\n\n\n\n\\providecommand{\\ascline}[3]{\\noalign{\\global\\arrayrulewidth #1}\\arrayrulecolor[HTML]{#2}\\cline{#3}}\n\n\\begin{longtable}[c]{|p{1.13in}|p{0.69in}|p{0.66in}}\n\n\n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 1.13in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{species}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.69in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{site}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.66in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{count}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endfirsthead \n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 1.13in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{species}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.69in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{site}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.66in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{count}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endhead\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 1.13in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Tilia\\ americana}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.69in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{site\\_01}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.66in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{1}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedright}m{\\dimexpr 1.13in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Tilia\\ americana}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.69in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{site\\_02}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.66in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{5}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 1.13in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Tilia\\ americana}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.69in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{site\\_03}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.66in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{2}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedright}m{\\dimexpr 1.13in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Pinus\\ strobus}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.69in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{site\\_01}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.66in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{3}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 1.13in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Pinus\\ strobus}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.69in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{site\\_02}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.66in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{4}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedright}m{\\dimexpr 1.13in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Pinus\\ strobus}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.69in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{site\\_03}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.66in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{5}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\end{longtable}\n\n\n\n\\arrayrulecolor[HTML]{000000}\n\n\\global\\setlength{\\arrayrulewidth}{\\Oldarrayrulewidth}\n\n\\global\\setlength{\\tabcolsep}{\\Oldtabcolsep}\n\n\\renewcommand*{\\arraystretch}{1}\n```\n:::\n:::\n\n\n\n- Can be tricky working with multiple column datatypes\n- Don't use colors or text formatting in tabular data, and only include column names as metadata. All other notes, definitions, etc. should be in an external metadata file (e.g. data dictionary)\n\n### Top References\n\n- Wickham, H. (2014). Tidy Data. Journal of Statistical Software, 59(10), 1--23.\\\n \n- Data Sharing and Management Snafu in 3 Short Acts (video)\\\n \n- Tips for working with data in BASH\\\n \n- Data Organization in Spreadsheets for Ecologists\\\n \n- Cleaning Data and Quality Control\\\n \n\n## Follow ISO 8601 for dates\n\n\n\n::: {.cell layout-align=\"center\"}\n::: {.cell-output-display}\n![https://imgs.xkcd.com/comics/iso_8601.png](https://imgs.xkcd.com/comics/iso_8601.png){fig-align='center' width=40%}\n:::\n:::\n\n\n\n### Why?\n\n- Internationally accepted format used across multiple schemas (e.g. `Darwin Core`, `EML`, `ISO 19115`)\n- Removes ambiguity related to timezone, daylight savings time changes, and time of day\n- Better software integration of time date/time elements\n\n### Key Information\n\n- UTC (AKA `Zulu` or `GMT`): Coordinated Universal Time (UTC) is the primary time standard by which the world regulates clocks and time. It is time relative to `0°` longitude and is not adjusted for daylight saving time. ([from Wikipedia](https://en.wikipedia.org/wiki/ISO_8601)).\n- Conversion to UTC, or between time zones, may depend on daylight savings\n\n*Examples: April 3, 2023 standardized to ISO 8601*\n\n\n\n::: {.cell}\n::: {.cell-output-display}\n```{=latex}\n\\global\\setlength{\\Oldarrayrulewidth}{\\arrayrulewidth}\n\n\\global\\setlength{\\Oldtabcolsep}{\\tabcolsep}\n\n\\setlength{\\tabcolsep}{0pt}\n\n\\renewcommand*{\\arraystretch}{1.5}\n\n\n\n\\providecommand{\\ascline}[3]{\\noalign{\\global\\arrayrulewidth #1}\\arrayrulecolor[HTML]{#2}\\cline{#3}}\n\n\\begin{longtable}[c]{|p{2.91in}|p{3.45in}}\n\n\n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 2.91in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{Description}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 3.45in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{Written\\ in\\ ISO\\ 8601}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endfirsthead \n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 2.91in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{Description}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 3.45in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{Written\\ in\\ ISO\\ 8601}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endhead\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 2.91in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Date}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 3.45in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{2023-04-03}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedright}m{\\dimexpr 2.91in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Date\\ and\\ Time\\ with\\ timezone\\ offset}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 3.45in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{2023-04-03T18:29:38+00:00}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 2.91in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Date\\ and\\ Time\\ in\\ UTC}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 3.45in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{2023-04-03T18:29:38Z}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedright}m{\\dimexpr 2.91in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Time\\ Interval\\ in\\ UTC\\ (April\\ 3\\ -\\ 5,\\ 2023)}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 3.45in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{2023-04-03T18:29:38Z/2023-04-05T00:29:38Z}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\end{longtable}\n\n\n\n\\arrayrulecolor[HTML]{000000}\n\n\\global\\setlength{\\arrayrulewidth}{\\Oldarrayrulewidth}\n\n\\global\\setlength{\\tabcolsep}{\\Oldtabcolsep}\n\n\\renewcommand*{\\arraystretch}{1}\n```\n:::\n:::\n\n\n\n*Examples: different styles of timezone annotation*\n\n\n\n::: {.cell}\n::: {.cell-output-display}\n```{=latex}\n\\global\\setlength{\\Oldarrayrulewidth}{\\arrayrulewidth}\n\n\\global\\setlength{\\Oldtabcolsep}{\\tabcolsep}\n\n\\setlength{\\tabcolsep}{0pt}\n\n\\renewcommand*{\\arraystretch}{1.5}\n\n\n\n\\providecommand{\\ascline}[3]{\\noalign{\\global\\arrayrulewidth #1}\\arrayrulecolor[HTML]{#2}\\cline{#3}}\n\n\\begin{longtable}[c]{|p{2.91in}|p{3.45in}}\n\n\n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 2.91in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{Description}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 3.45in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{Written\\ in\\ ISO\\ 8601}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endfirsthead \n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 2.91in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{Description}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 3.45in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{Written\\ in\\ ISO\\ 8601}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endhead\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 2.91in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Date}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 3.45in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{2023-04-03}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedright}m{\\dimexpr 2.91in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Date\\ and\\ Time\\ with\\ timezone\\ offset}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 3.45in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{2023-04-03T18:29:38+00:00}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 2.91in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Date\\ and\\ Time\\ in\\ UTC}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 3.45in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{2023-04-03T18:29:38Z}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedright}m{\\dimexpr 2.91in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Time\\ Interval\\ in\\ UTC\\ (April\\ 3\\ -\\ 5,\\ 2023)}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 3.45in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{2023-04-03T18:29:38Z/2023-04-05T00:29:38Z}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\end{longtable}\n\n\n\n\\arrayrulecolor[HTML]{000000}\n\n\\global\\setlength{\\arrayrulewidth}{\\Oldarrayrulewidth}\n\n\\global\\setlength{\\tabcolsep}{\\Oldtabcolsep}\n\n\\renewcommand*{\\arraystretch}{1}\n```\n:::\n:::\n\n\n\n### Top References\n\n- ISO 8601 wiki: \n- R package lubridate, OlsonNames()\n- Python go-to package, datetime \n- Article on datetime uncertainty: \n- Map of offset from UTC: \n- Nice time converter: \n\n## Match scientific names to a taxonomic authority\n\n### Why?\n\n- To integrate or aggregate datasets, we need a common frame of reference for taxonomic name\n- Provides an anchor for the taxonomy as scientific understanding evolves.\n\n### Key Information\n\n- Definition: As used here, a taxonomic authority is an online resource that maintains up-to-date species-level classification information and provides persistent identifiers for taxonomic classifications. Example: For the species *Balaenoptera borealis* (Lesson, 1828), the WoRMS taxonomic authority ID link is and the LSID is `urn:lsid:marinespecies.org:taxname:137088`.\n- Use an existing taxonomic authority (e.g. [World Register of Marine Species](https://www.marinespecies.org) , [Integrated Taxonomic Information System](https://itis.gov/) , [NCBI taxonomy](https://www.ncbi.nlm.nih.gov/taxonomy)) and include the authority who manages said information in your metadata\n- List of many authorities can be found here: \n- Make yourself aware of the structure, limits, and history of the authority you are using.\n- Adopt standard binomial nomenclature, when possible\n- When possible, reference the unique identifier in addition to the nomenclature.\n- Always save and document the originally recorded name.\n- Put notes about identification uncertainty in a separate column.\n- Many authorities have APIs through which you can match names to identifiers.\n\n### Top References\n\n- R packages\n - taxize is a taxonomic toolbelt for R. taxize wraps APIs for a large suite of taxonomic databases available on the web\\\n \n - worrms is an API client for [World Register of Marine Species](http://www.marinespecies.org/)\\\n \n - worms: another API client for WoRMS\\\n \n - Ritis: API client for ITIS \\\n- Python packages\n - WoRMS API client\\\n \n- Global Names Resolver to compare taxonomic concepts across authorities\\\n \n- Article: Recommendations for the Standardisation of Open Taxonomic Nomenclature for Image-Based Identifications\\\n \n- TDWG 2022 Keynote: Richard Pyle, \"An Introduction to the Scientific Names of Organisms and the Taxon Concepts they Represent\"\\\n \n\n## Record latitude and longitude in decimal degrees in WGS84\n\n\n\n::: {.cell layout-align=\"center\"}\n::: {.cell-output-display}\n![https://imgs.xkcd.com/comics/coordinate_precision.png](https://imgs.xkcd.com/comics/coordinate_precision.png){fig-align='center' width=40%}\n:::\n:::\n\n\n\n### Why?\n\n- Users have to know where you collected this data, which requires a latitude, longitude, reference system and uncertainty.\n- Decimal-degrees avoids special symbols (`°` or `‘`) which is preferable for machine readable formats\n- `WGS84` is a reference coordinate system that is widely used and incorporated in many GPS units and tools, and recognized as a standard by many government agencies.\n\n### Key Information\n\n- If possible, encourage data providers to confirm, and record, the WGS84 datum prior to data collection.\n- Understand and report the device/instrument uncertainty associated with your coordinates because it affects the usability of your data.\n- Consider including the vertical component (altitude, depth, height off bottom, elevation, etc)\n- Generally speaking, `degrees-minutes-seconds (DMS)` can be converted to `decimal-degrees (DD)` by:\n - `DD = d + (min/60) + (sec/3600)`\n - Watch out for mixed formats, like degrees, `decimal-minutes (DDM)`.\n- Degrees West and South become negative in DD.\n - Values for longitude range from `-180` to `180`, inclusive.\n - Values for latitude range from `-90` to `90`, inclusive.\n\n*Example Coordinates*\n\n\n\n::: {.cell}\n::: {.cell-output-display}\n```{=latex}\n\\global\\setlength{\\Oldarrayrulewidth}{\\arrayrulewidth}\n\n\\global\\setlength{\\Oldtabcolsep}{\\tabcolsep}\n\n\\setlength{\\tabcolsep}{0pt}\n\n\\renewcommand*{\\arraystretch}{1.5}\n\n\n\n\\providecommand{\\ascline}[3]{\\noalign{\\global\\arrayrulewidth #1}\\arrayrulecolor[HTML]{#2}\\cline{#3}}\n\n\\begin{longtable}[c]{|p{2.98in}|p{1.26in}}\n\n\n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 2.98in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{Format}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 1.26in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{Example}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endfirsthead \n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 2.98in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{Format}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 1.26in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{Example}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endhead\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 2.98in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Decimal\\ Degrees\\ (DD)}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 1.26in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{30.50833333}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedright}m{\\dimexpr 2.98in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Degrees\\ Minutes\\ Seconds\\ (DMS)}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 1.26in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{30°\\ 15'\\ 10\\ N}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 2.98in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Degrees\\ Decimal\\ Minutes\\ (DM\\ or\\ DDM)}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 1.26in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{30°\\ 15.1667\\ N}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\end{longtable}\n\n\n\n\\arrayrulecolor[HTML]{000000}\n\n\\global\\setlength{\\arrayrulewidth}{\\Oldarrayrulewidth}\n\n\\global\\setlength{\\tabcolsep}{\\Oldtabcolsep}\n\n\\renewcommand*{\\arraystretch}{1}\n```\n:::\n:::\n\n\n\n### Top References\n\n- Existing R/python/ESRI packages/functions\n - R - measurements \n - EML (find \"bounding Coordinates)\n - CF \n- Getting lat/lon to decimal degrees\\\n \n- Some background on precision\n - \n - \n- DMS to DD calculator\\\n -- The three most commonly used datums are WGS84, NAD83, and NAD27. A more complete list can be found here: \n\n## Use persistent unique identifiers\n\n### Why?\n\n- It can be useful to have unique identifiers to unambiguously identify granules of information, e.g. dataset, collection, database, taxonomic concept, etc. This will allow users to precisely refer to the data and allow your data to remain identifiable when aggregated with other datasets.\n- To be able to uniquely identify a record in your data system or across data systems. Useful to create relational databases or merge records.\n- Although it increases workload, it safeguards against confusion and inefficiency in the future.\n\n### Key Information\n\n- There are good reasons to keep an identifier opaque, i.e. it does not indicate anything about the content of information it points to. However, there are also transparent, or semi-opaque identifiers in use that take advantage of semantics to guide humans as well as machines.\n- One way to create a unique identifier is concatenation of sampling event, location, time, enumeration of unique observation or event. (e.g. `Station_95_Date_09JAN1997:14:35:00.000`)\n- Some prefer using opaque identifiers. (e.g. `10FC9784-B30F-48ED-8DB5-FF65A2A9934E`)\n- If there is an existing persistent unique identifier, it's usually a good idea to use it (i.e. when using a taxonomic authority like WoRMS and applying their LSID).\n- It is important to manage any identifiers you create, if they are not managed by an authority (e.g. DOIs).\n- Important that it be persistent (consider samples possibly moving between institutions)\n\n*Examples of PIDs*\n\n\n\n::: {.cell}\n::: {.cell-output-display}\n```{=latex}\n\\global\\setlength{\\Oldarrayrulewidth}{\\arrayrulewidth}\n\n\\global\\setlength{\\Oldtabcolsep}{\\tabcolsep}\n\n\\setlength{\\tabcolsep}{0pt}\n\n\\renewcommand*{\\arraystretch}{1.5}\n\n\n\n\\providecommand{\\ascline}[3]{\\noalign{\\global\\arrayrulewidth #1}\\arrayrulecolor[HTML]{#2}\\cline{#3}}\n\n\\begin{longtable}[c]{|p{1.50in}|p{1.50in}|p{3.00in}}\n\n\n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 1.5in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{Type\\ of\\ PID}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 1.5in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{Use\\ Case}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 3in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{Example}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endfirsthead \n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 1.5in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{Type\\ of\\ PID}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 1.5in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{Use\\ Case}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 3in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{Example}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endhead\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 1.5in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Digital\\ Object\\ Identifier\\ (DOI)}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 1.5in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Actionable\\ persistent\\ link\\ for\\ papers,\\ data,\\ and\\ other\\ digital\\ objects}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 3in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{https://doi.org/10.6084/m9.figshare.16806712.v2}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedright}m{\\dimexpr 1.5in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{International\\ Geo\\ Sample\\ Number\\ (IGSN)}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 1.5in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Persistent\\ identifier\\ for\\ physical\\ samples}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 3in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{http://igsn.org/AU1243>}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 1.5in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Life\\ Science\\ Identifier\\ (LSID)}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 1.5in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Persistent\\ structured\\ method\\ for\\ biologically\\ significant\\ data}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 3in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{urn:lsid:marinespecies.org:taxname:218214}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedright}m{\\dimexpr 1.5in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Open\\ Researcher\\ and\\ Contributor\\ ID\\ (ORCID)}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 1.5in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Persistent\\ actionable\\ link\\ for\\ individuals}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 3in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{https://orcid.org/0000-0002-4391-107X}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\end{longtable}\n\n\n\n\\arrayrulecolor[HTML]{000000}\n\n\\global\\setlength{\\arrayrulewidth}{\\Oldarrayrulewidth}\n\n\\global\\setlength{\\tabcolsep}{\\Oldtabcolsep}\n\n\\renewcommand*{\\arraystretch}{1}\n```\n:::\n:::\n\n\n\n### Top References\n\n- Software and Packages to generate uuids:\n - R - uuid \n - python - uuid \n - \n - \n- Guidance on how to use GUIDs (Globally Unique Identifiers) to meet specific requirements of the biodiversity information community\\\n \n- Use of globally unique identifiers (GUIDs) to link herbarium specimen records to physical specimens\\\n \n- A Beginner's Guide to Persistent Identifiers\\\n \n", + "markdown": "# Make Your Data Software Ready\n\n## Use non-proprietary formats\n\n### Why?\n\n- Allows data to be useful in perpetuity by ensuring data readability and reusability across multiple platforms.\n- To align better with the FAIR principles (findability, accessibility, interoperability, reusability)\n- Makes data more socially equitable, supporting open science. Proprietary formats can depend on software that require licenses, which not everyone can afford/has access to.\n\n### Key Information\n\n- *Non-proprietary formats* are supported by more than one developer and can be accessed with different software systems. For example, comma separated values (CSV) format is becoming an increasingly popular non-proprietary format.\n- A [*proprietary file format*](https://en.wikipedia.org/wiki/Proprietary_file_format) is a file format of a company, organization, or individual that contains data that is ordered and stored according to a particular encoding-scheme, designed by the company or organization to be secret or with restricted access, such that the decoding and interpretation of this stored data is easily accomplished only with particular software or hardware that the company itself has developed. There may also be costs associated with it and access may be limited. Examples include `Microsoft Excel (xlsx)` and `ESRI shapefiles (shp)`.\n- Many applications (e.g. Microsoft Office) allow exporting in multiple formats.\n\n### Top References\n\n- Table of commonly used formats for common data types\\\n \n\n- A more detailed table that is specific to US Federal records management\\\n \n\n## Structure tabular data in tidy/long format\n\n### Why?\n\n*This is specifically intended for tabular data*\n\n- There is a clear and easy to understand structure that can make your data more machine readable and easier to analyze/visualize\n - Clear structure: one observation per row\n - Data are as atomic as possible (e.g., don't mix types in field)\n- In the biological data community, tidy formats are more likely to work with commonly-used software\n- Easier to aggregate data across multiple files\n\n### Key Information\n\nExample of Wide Format\n\n\n\n::: {.cell}\n::: {.cell-output-display}\n```{=latex}\n\\global\\setlength{\\Oldarrayrulewidth}{\\arrayrulewidth}\n\n\\global\\setlength{\\Oldtabcolsep}{\\tabcolsep}\n\n\\setlength{\\tabcolsep}{0pt}\n\n\\renewcommand*{\\arraystretch}{1.5}\n\n\n\n\\providecommand{\\ascline}[3]{\\noalign{\\global\\arrayrulewidth #1}\\arrayrulecolor[HTML]{#2}\\cline{#3}}\n\n\\begin{longtable}[c]{|p{1.13in}|p{0.78in}|p{0.78in}|p{0.78in}}\n\n\n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 1.13in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{species}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.78in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{site\\_01}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.78in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{site\\_02}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.78in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{site\\_03}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endfirsthead \n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 1.13in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{species}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.78in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{site\\_01}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.78in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{site\\_02}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.78in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{site\\_03}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endhead\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 1.13in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Tilia\\ americana}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.78in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{0}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.78in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{4}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.78in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{3}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedright}m{\\dimexpr 1.13in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Pinus\\ strobus}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.78in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{3}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.78in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{5}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.78in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{5}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\end{longtable}\n\n\n\n\\arrayrulecolor[HTML]{000000}\n\n\\global\\setlength{\\arrayrulewidth}{\\Oldarrayrulewidth}\n\n\\global\\setlength{\\tabcolsep}{\\Oldtabcolsep}\n\n\\renewcommand*{\\arraystretch}{1}\n```\n:::\n:::\n\n\n\nExample of Long Format\n\n\n\n::: {.cell}\n::: {.cell-output-display}\n```{=latex}\n\\global\\setlength{\\Oldarrayrulewidth}{\\arrayrulewidth}\n\n\\global\\setlength{\\Oldtabcolsep}{\\tabcolsep}\n\n\\setlength{\\tabcolsep}{0pt}\n\n\\renewcommand*{\\arraystretch}{1.5}\n\n\n\n\\providecommand{\\ascline}[3]{\\noalign{\\global\\arrayrulewidth #1}\\arrayrulecolor[HTML]{#2}\\cline{#3}}\n\n\\begin{longtable}[c]{|p{1.13in}|p{0.69in}|p{0.66in}}\n\n\n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 1.13in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{species}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.69in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{site}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.66in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{count}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endfirsthead \n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 1.13in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{species}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 0.69in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{site}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedleft}m{\\dimexpr 0.66in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{count}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endhead\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 1.13in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Tilia\\ americana}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.69in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{site\\_01}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.66in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{3}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedright}m{\\dimexpr 1.13in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Tilia\\ americana}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.69in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{site\\_02}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.66in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{5}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 1.13in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Tilia\\ americana}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.69in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{site\\_03}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.66in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{4}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedright}m{\\dimexpr 1.13in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Pinus\\ strobus}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.69in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{site\\_01}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.66in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{4}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 1.13in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Pinus\\ strobus}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 0.69in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{site\\_02}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedleft}m{\\dimexpr 0.66in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{0}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedright}m{\\dimexpr 1.13in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Pinus\\ strobus}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 0.69in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{site\\_03}}} & \\multicolumn{1}{>{\\raggedleft}m{\\dimexpr 0.66in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{2}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\end{longtable}\n\n\n\n\\arrayrulecolor[HTML]{000000}\n\n\\global\\setlength{\\arrayrulewidth}{\\Oldarrayrulewidth}\n\n\\global\\setlength{\\tabcolsep}{\\Oldtabcolsep}\n\n\\renewcommand*{\\arraystretch}{1}\n```\n:::\n:::\n\n\n\n- Can be tricky working with multiple column datatypes\n- Don't use colors or text formatting in tabular data, and only include column names as metadata. All other notes, definitions, etc. should be in an external metadata file (e.g. data dictionary)\n\n### Top References\n\n- Wickham, H. (2014). Tidy Data. Journal of Statistical Software, 59(10), 1--23.\\\n \n- Data Sharing and Management Snafu in 3 Short Acts (video)\\\n \n- Tips for working with data in BASH\\\n \n- Data Organization in Spreadsheets for Ecologists\\\n \n- Cleaning Data and Quality Control\\\n \n\n## Follow ISO 8601 for dates\n\n\n\n::: {.cell layout-align=\"center\"}\n::: {.cell-output-display}\n![https://imgs.xkcd.com/comics/iso_8601.png](https://imgs.xkcd.com/comics/iso_8601.png){fig-align='center' width=40%}\n:::\n:::\n\n\n\n### Why?\n\n- Internationally accepted format used across multiple schemas (e.g. `Darwin Core`, `EML`, `ISO 19115`)\n- Removes ambiguity related to timezone, daylight savings time changes, and time of day\n- Better software integration of time date/time elements\n\n### Key Information\n\n- UTC (AKA `Zulu` or `GMT`): Coordinated Universal Time (UTC) is the primary time standard by which the world regulates clocks and time. It is time relative to `0°` longitude and is not adjusted for daylight saving time. ([from Wikipedia](https://en.wikipedia.org/wiki/ISO_8601)).\n- Conversion to UTC, or between time zones, may depend on daylight savings\n\n*Examples: April 3, 2023 standardized to ISO 8601*\n\n\n\n::: {.cell}\n::: {.cell-output-display}\n```{=latex}\n\\global\\setlength{\\Oldarrayrulewidth}{\\arrayrulewidth}\n\n\\global\\setlength{\\Oldtabcolsep}{\\tabcolsep}\n\n\\setlength{\\tabcolsep}{0pt}\n\n\\renewcommand*{\\arraystretch}{1.5}\n\n\n\n\\providecommand{\\ascline}[3]{\\noalign{\\global\\arrayrulewidth #1}\\arrayrulecolor[HTML]{#2}\\cline{#3}}\n\n\\begin{longtable}[c]{|p{2.91in}|p{3.45in}}\n\n\n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 2.91in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{Description}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 3.45in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{Written\\ in\\ ISO\\ 8601}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endfirsthead \n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 2.91in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{Description}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 3.45in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{Written\\ in\\ ISO\\ 8601}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endhead\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 2.91in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Date}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 3.45in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{2023-04-03}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedright}m{\\dimexpr 2.91in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Date\\ and\\ Time\\ with\\ timezone\\ offset}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 3.45in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{2023-04-03T18:29:38+00:00}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 2.91in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Date\\ and\\ Time\\ in\\ UTC}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 3.45in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{2023-04-03T18:29:38Z}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedright}m{\\dimexpr 2.91in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Time\\ Interval\\ in\\ UTC\\ (April\\ 3\\ -\\ 5,\\ 2023)}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 3.45in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{2023-04-03T18:29:38Z/2023-04-05T00:29:38Z}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\end{longtable}\n\n\n\n\\arrayrulecolor[HTML]{000000}\n\n\\global\\setlength{\\arrayrulewidth}{\\Oldarrayrulewidth}\n\n\\global\\setlength{\\tabcolsep}{\\Oldtabcolsep}\n\n\\renewcommand*{\\arraystretch}{1}\n```\n:::\n:::\n\n\n\n*Examples: different styles of timezone annotation*\n\n\n\n::: {.cell}\n::: {.cell-output-display}\n```{=latex}\n\\global\\setlength{\\Oldarrayrulewidth}{\\arrayrulewidth}\n\n\\global\\setlength{\\Oldtabcolsep}{\\tabcolsep}\n\n\\setlength{\\tabcolsep}{0pt}\n\n\\renewcommand*{\\arraystretch}{1.5}\n\n\n\n\\providecommand{\\ascline}[3]{\\noalign{\\global\\arrayrulewidth #1}\\arrayrulecolor[HTML]{#2}\\cline{#3}}\n\n\\begin{longtable}[c]{|p{2.91in}|p{3.45in}}\n\n\n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 2.91in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{Description}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 3.45in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{Written\\ in\\ ISO\\ 8601}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endfirsthead \n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 2.91in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{Description}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 3.45in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{Written\\ in\\ ISO\\ 8601}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endhead\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 2.91in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Date}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 3.45in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{2023-04-03}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedright}m{\\dimexpr 2.91in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Date\\ and\\ Time\\ with\\ timezone\\ offset}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 3.45in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{2023-04-03T18:29:38+00:00}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 2.91in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Date\\ and\\ Time\\ in\\ UTC}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 3.45in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{2023-04-03T18:29:38Z}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedright}m{\\dimexpr 2.91in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Time\\ Interval\\ in\\ UTC\\ (April\\ 3\\ -\\ 5,\\ 2023)}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 3.45in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{2023-04-03T18:29:38Z/2023-04-05T00:29:38Z}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\end{longtable}\n\n\n\n\\arrayrulecolor[HTML]{000000}\n\n\\global\\setlength{\\arrayrulewidth}{\\Oldarrayrulewidth}\n\n\\global\\setlength{\\tabcolsep}{\\Oldtabcolsep}\n\n\\renewcommand*{\\arraystretch}{1}\n```\n:::\n:::\n\n\n\n### Top References\n\n- ISO 8601 wiki: \n- R package lubridate, OlsonNames()\n- Python go-to package, datetime \n- Article on datetime uncertainty: \n- Map of offset from UTC: \n- Nice time converter: \n\n## Match scientific names to a taxonomic authority\n\n### Why?\n\n- To integrate or aggregate datasets, we need a common frame of reference for taxonomic name\n- Provides an anchor for the taxonomy as scientific understanding evolves.\n\n### Key Information\n\n- Definition: As used here, a taxonomic authority is an online resource that maintains up-to-date species-level classification information and provides persistent identifiers for taxonomic classifications. Example: For the species *Balaenoptera borealis* (Lesson, 1828), the WoRMS taxonomic authority ID link is and the LSID is `urn:lsid:marinespecies.org:taxname:137088`.\n- Use an existing taxonomic authority (e.g. [World Register of Marine Species](https://www.marinespecies.org) , [Integrated Taxonomic Information System](https://itis.gov/) , [NCBI taxonomy](https://www.ncbi.nlm.nih.gov/taxonomy)) and include the authority who manages said information in your metadata\n- List of many authorities can be found here: \n- Make yourself aware of the structure, limits, and history of the authority you are using.\n- Adopt standard binomial nomenclature, when possible\n- When possible, reference the unique identifier in addition to the nomenclature.\n- Always save and document the originally recorded name.\n- Put notes about identification uncertainty in a separate column.\n- Many authorities have APIs through which you can match names to identifiers.\n\n### Top References\n\n- R packages\n - taxize is a taxonomic toolbelt for R. taxize wraps APIs for a large suite of taxonomic databases available on the web\\\n \n - worrms is an API client for [World Register of Marine Species](http://www.marinespecies.org/)\\\n \n - worms: another API client for WoRMS\\\n \n - Ritis: API client for ITIS \\\n- Python packages\n - WoRMS API client\\\n \n- Global Names Resolver to compare taxonomic concepts across authorities\\\n \n- Article: Recommendations for the Standardisation of Open Taxonomic Nomenclature for Image-Based Identifications\\\n \n- TDWG 2022 Keynote: Richard Pyle, \"An Introduction to the Scientific Names of Organisms and the Taxon Concepts they Represent\"\\\n \n\n## Record latitude and longitude in decimal degrees in WGS84\n\n\n\n::: {.cell layout-align=\"center\"}\n::: {.cell-output-display}\n![https://imgs.xkcd.com/comics/coordinate_precision.png](https://imgs.xkcd.com/comics/coordinate_precision.png){fig-align='center' width=40%}\n:::\n:::\n\n\n\n### Why?\n\n- Users have to know where you collected this data, which requires a latitude, longitude, reference system and uncertainty.\n- Decimal-degrees avoids special symbols (`°` or `‘`) which is preferable for machine readable formats\n- `WGS84` is a reference coordinate system that is widely used and incorporated in many GPS units and tools, and recognized as a standard by many government agencies.\n\n### Key Information\n\n- If possible, encourage data providers to confirm, and record, the WGS84 datum prior to data collection.\n- Understand and report the device/instrument uncertainty associated with your coordinates because it affects the usability of your data.\n- Consider including the vertical component (altitude, depth, height off bottom, elevation, etc)\n- Generally speaking, `degrees-minutes-seconds (DMS)` can be converted to `decimal-degrees (DD)` by:\n - `DD = d + (min/60) + (sec/3600)`\n - Watch out for mixed formats, like degrees, `decimal-minutes (DDM)`.\n- Degrees West and South become negative in DD.\n - Values for longitude range from `-180` to `180`, inclusive.\n - Values for latitude range from `-90` to `90`, inclusive.\n\n*Example Coordinates*\n\n\n\n::: {.cell}\n::: {.cell-output-display}\n```{=latex}\n\\global\\setlength{\\Oldarrayrulewidth}{\\arrayrulewidth}\n\n\\global\\setlength{\\Oldtabcolsep}{\\tabcolsep}\n\n\\setlength{\\tabcolsep}{0pt}\n\n\\renewcommand*{\\arraystretch}{1.5}\n\n\n\n\\providecommand{\\ascline}[3]{\\noalign{\\global\\arrayrulewidth #1}\\arrayrulecolor[HTML]{#2}\\cline{#3}}\n\n\\begin{longtable}[c]{|p{2.98in}|p{1.26in}}\n\n\n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 2.98in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{Format}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 1.26in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{Example}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endfirsthead \n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 2.98in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{Format}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 1.26in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{Example}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endhead\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 2.98in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Decimal\\ Degrees\\ (DD)}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 1.26in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{30.50833333}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedright}m{\\dimexpr 2.98in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Degrees\\ Minutes\\ Seconds\\ (DMS)}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 1.26in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{30°\\ 15'\\ 10\\ N}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 2.98in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Degrees\\ Decimal\\ Minutes\\ (DM\\ or\\ DDM)}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 1.26in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{30°\\ 15.1667\\ N}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\end{longtable}\n\n\n\n\\arrayrulecolor[HTML]{000000}\n\n\\global\\setlength{\\arrayrulewidth}{\\Oldarrayrulewidth}\n\n\\global\\setlength{\\tabcolsep}{\\Oldtabcolsep}\n\n\\renewcommand*{\\arraystretch}{1}\n```\n:::\n:::\n\n\n\n### Top References\n\n- Existing R/python/ESRI packages/functions\n - R - measurements \n - EML (find \"bounding Coordinates)\n - CF \n- Getting lat/lon to decimal degrees\\\n \n- Some background on precision\n - \n - \n- DMS to DD calculator\\\n -- The three most commonly used datums are WGS84, NAD83, and NAD27. A more complete list can be found here: \n\n## Use persistent unique identifiers\n\n### Why?\n\n- It can be useful to have unique identifiers to unambiguously identify granules of information, e.g. dataset, collection, database, taxonomic concept, etc. This will allow users to precisely refer to the data and allow your data to remain identifiable when aggregated with other datasets.\n- To be able to uniquely identify a record in your data system or across data systems. Useful to create relational databases or merge records.\n- Although it increases workload, it safeguards against confusion and inefficiency in the future.\n\n### Key Information\n\n- There are good reasons to keep an identifier opaque, i.e. it does not indicate anything about the content of information it points to. However, there are also transparent, or semi-opaque identifiers in use that take advantage of semantics to guide humans as well as machines.\n- One way to create a unique identifier is concatenation of sampling event, location, time, enumeration of unique observation or event. (e.g. `Station_95_Date_09JAN1997:14:35:00.000`)\n- Some prefer using opaque identifiers. (e.g. `10FC9784-B30F-48ED-8DB5-FF65A2A9934E`)\n- If there is an existing persistent unique identifier, it's usually a good idea to use it (i.e. when using a taxonomic authority like WoRMS and applying their LSID).\n- It is important to manage any identifiers you create, if they are not managed by an authority (e.g. DOIs).\n- Important that it be persistent (consider samples possibly moving between institutions)\n\n*Examples of PIDs*\n\n\n\n::: {.cell}\n::: {.cell-output-display}\n```{=latex}\n\\global\\setlength{\\Oldarrayrulewidth}{\\arrayrulewidth}\n\n\\global\\setlength{\\Oldtabcolsep}{\\tabcolsep}\n\n\\setlength{\\tabcolsep}{0pt}\n\n\\renewcommand*{\\arraystretch}{1.5}\n\n\n\n\\providecommand{\\ascline}[3]{\\noalign{\\global\\arrayrulewidth #1}\\arrayrulecolor[HTML]{#2}\\cline{#3}}\n\n\\begin{longtable}[c]{|p{1.50in}|p{1.50in}|p{3.00in}}\n\n\n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 1.5in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{Type\\ of\\ PID}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 1.5in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{Use\\ Case}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 3in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{Example}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endfirsthead \n\n\\hhline{>{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}->{\\arrayrulecolor[HTML]{000000}\\global\\arrayrulewidth=0pt}-}\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 1.5in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{Type\\ of\\ PID}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 1.5in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{Use\\ Case}}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{CFCFCF}\\raggedright}m{\\dimexpr 3in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{11}{11}\\selectfont{\\textbf{Example}}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\\endhead\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 1.5in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Digital\\ Object\\ Identifier\\ (DOI)}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 1.5in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Actionable\\ persistent\\ link\\ for\\ papers,\\ data,\\ and\\ other\\ digital\\ objects}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 3in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{https://doi.org/10.6084/m9.figshare.16806712.v2}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedright}m{\\dimexpr 1.5in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{International\\ Geo\\ Sample\\ Number\\ (IGSN)}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 1.5in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Persistent\\ identifier\\ for\\ physical\\ samples}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 3in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{http://igsn.org/AU1243>}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 1.5in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Life\\ Science\\ Identifier\\ (LSID)}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 1.5in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Persistent\\ structured\\ method\\ for\\ biologically\\ significant\\ data}}} & \\multicolumn{1}{>{\\cellcolor[HTML]{EFEFEF}\\raggedright}m{\\dimexpr 3in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{urn:lsid:marinespecies.org:taxname:218214}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\multicolumn{1}{>{\\raggedright}m{\\dimexpr 1.5in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Open\\ Researcher\\ and\\ Contributor\\ ID\\ (ORCID)}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 1.5in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{Persistent\\ actionable\\ link\\ for\\ individuals}}} & \\multicolumn{1}{>{\\raggedright}m{\\dimexpr 3in+0\\tabcolsep}}{\\textcolor[HTML]{000000}{\\fontsize{9}{9}\\selectfont{https://orcid.org/0000-0002-4391-107X}}} \\\\\n\n\\noalign{\\global\\arrayrulewidth 0pt}\\arrayrulecolor[HTML]{000000}\n\n\n\n\n\n\\end{longtable}\n\n\n\n\\arrayrulecolor[HTML]{000000}\n\n\\global\\setlength{\\arrayrulewidth}{\\Oldarrayrulewidth}\n\n\\global\\setlength{\\tabcolsep}{\\Oldtabcolsep}\n\n\\renewcommand*{\\arraystretch}{1}\n```\n:::\n:::\n\n\n\n### Top References\n\n- Software and Packages to generate uuids:\n - R - uuid \n - python - uuid \n - \n - \n- Guidance on how to use GUIDs (Globally Unique Identifiers) to meet specific requirements of the biodiversity information community\\\n \n- Use of globally unique identifiers (GUIDs) to link herbarium specimen records to physical specimens\\\n \n- A Beginner's Guide to Persistent Identifiers\\\n \n", "supporting": [ "SOFTWARE_READY_files" ], diff --git a/.quarto/cites/index.json b/.quarto/cites/index.json index f629e60..d561d70 100644 --- a/.quarto/cites/index.json +++ b/.quarto/cites/index.json @@ -1 +1 @@ -{"3-INTEGRATE_DATA.qmd":[],"5-SHARE_DATA_WEB.qmd":[],"SHARE_DATA_WEB.qmd":[],"INTEGRATE_DATA.qmd":[],"INTEROPERABLE_DATA.qmd":[],"intro.qmd":[],"1-intro.qmd":[],"SOFTWARE_READY.qmd":[],"4-INTEROPERABLE_DATA.qmd":[],"6-SOFTWARE_READY.qmd":[],"CONTEXT_UNDERSTANDABILITY.qmd":[],"index.qmd":[],"2-CONTEXT_UNDERSTANDABILITY.qmd":[]} +{"index.qmd":[],"SHARE_DATA_WEB.qmd":[],"3-INTEGRATE_DATA.qmd":[],"5-SHARE_DATA_WEB.qmd":[],"1-intro.qmd":[],"INTEROPERABLE_DATA.qmd":[],"CONTEXT_UNDERSTANDABILITY.qmd":[],"2-CONTEXT_UNDERSTANDABILITY.qmd":[],"6-SOFTWARE_READY.qmd":[],"intro.qmd":[],"4-INTEROPERABLE_DATA.qmd":[],"INTEGRATE_DATA.qmd":[],"SOFTWARE_READY.qmd":[]} diff --git a/.quarto/idx/SOFTWARE_READY.qmd.json b/.quarto/idx/SOFTWARE_READY.qmd.json index 0a81ac4..e663b00 100644 --- a/.quarto/idx/SOFTWARE_READY.qmd.json +++ b/.quarto/idx/SOFTWARE_READY.qmd.json @@ -1 +1 @@ -{"title":"Make Your Data Software Ready","markdown":{"headingText":"Make Your Data Software Ready","headingAttr":{"id":"","classes":["unnumbered"],"keyvalue":[]},"containsRefs":false,"markdown":"\n## Use non-proprietary formats\n\n### Why?\n\n- Allows data to be useful in perpetuity by ensuring data readability and reusability across multiple platforms.\n- To align better with the FAIR principles (findability, accessibility, interoperability, reusability)\n- Makes data more socially equitable, supporting open science. Proprietary formats can depend on software that require licenses, which not everyone can afford/has access to.\n\n### Key Information\n\n- *Non-proprietary formats* are supported by more than one developer and can be accessed with different software systems. For example, comma separated values (CSV) format is becoming an increasingly popular non-proprietary format.\n- A [*proprietary file format*](https://en.wikipedia.org/wiki/Proprietary_file_format) is a file format of a company, organization, or individual that contains data that is ordered and stored according to a particular encoding-scheme, designed by the company or organization to be secret or with restricted access, such that the decoding and interpretation of this stored data is easily accomplished only with particular software or hardware that the company itself has developed. There may also be costs associated with it and access may be limited. Examples include `Microsoft Excel (xlsx)` and `ESRI shapefiles (shp)`.\n- Many applications (e.g. Microsoft Office) allow exporting in multiple formats.\n\n### Top References\n\n- Table of commonly used formats for common data types\\\n \n \n- A more detailed table that is specific to US Federal records management\\\n \n\n## Structure tabular data in tidy/long format\n\n### Why?\n\n*This is specifically intended for tabular data*\n\n- There is a clear and easy to understand structure that can make your data more machine readable and easier to analyze/visualize\n - Clear structure: one observation per row\n - Data are as atomic as possible (e.g., don't mix types in field)\n- In the biological data community, tidy formats are more likely to work with commonly-used software\n- Easier to aggregate data across multiple files\n\n### Key Information\n\nExample of Wide Format\n\n```{r}\n\n#| label: tbl-tidyformat wide\n\n\n\nlibrary(dplyr)\nlibrary(flextable)\n#library(gt)\n\nexample_df <- data.frame(species = c(\"Tilia americana\",\n \"Pinus strobus\"),\n site_01 = sample(0:5, size = 2),\n site_02 = sample(0:5, size = 2),\n site_03 = sample(0:5, size = 2))\n\nlong_example <- tidyr::pivot_longer(data = example_df, cols = site_01:site_03, names_to = \"site\", values_to = \"count\")\n\n# flextable is awesome, but captions aren't working yet: %\n set_caption(caption = \"Wide Format\") %>% \n fontsize(size = 9) %>% \n autofit() %>% \n theme_zebra()\n\n```\n\nExample of Long Format\n\n```{r}\n\n#| label: tbl-tidyformat long\n\n\n\nlibrary(dplyr)\nlibrary(flextable)\n#library(gt)\n\nexample_df <- data.frame(species = c(\"Tilia americana\",\n \"Pinus strobus\"),\n site_01 = sample(0:5, size = 2),\n site_02 = sample(0:5, size = 2),\n site_03 = sample(0:5, size = 2))\n\nlong_example <- tidyr::pivot_longer(data = example_df, cols = site_01:site_03, names_to = \"site\", values_to = \"count\")\n\n# flextable is awesome, but captions aren't working yet: %\n set_caption(caption = \"Long Format\") %>%\n fontsize(size = 9) %>% \n autofit() %>% theme_zebra()\n\n# example_df %>% \n# gt(caption = \"Wide Format\")\n# \n# long_example %>% \n# gt(caption = \"Long Format\")\n\n```\n\n- Can be tricky working with multiple column datatypes\n- Don't use colors or text formatting in tabular data, and only include column names as metadata. All other notes, definitions, etc. should be in an external metadata file (e.g. data dictionary)\n\n### Top References\n\n- Wickham, H. (2014). Tidy Data. Journal of Statistical Software, 59(10), 1--23.\\\n \n- Data Sharing and Management Snafu in 3 Short Acts (video)\\\n \n- Tips for working with data in BASH\\\n \n- Data Organization in Spreadsheets for Ecologists\\\n \n- Cleaning Data and Quality Control\\\n \n\n## Follow ISO 8601 for dates\n\n```{r xkcd1, echo = FALSE, out.width=\"40%\", fig.align=\"center\", fig.cap=\"https://imgs.xkcd.com/comics/iso_8601.png\"}\n\nknitr::include_graphics('https://imgs.xkcd.com/comics/iso_8601.png')\n\n```\n\n### Why?\n\n- Internationally accepted format used across multiple schemas (e.g. `Darwin Core`, `EML`, `ISO 19115`)\n- Removes ambiguity related to timezone, daylight savings time changes, and time of day\n- Better software integration of time date/time elements\n\n### Key Information\n\n- UTC (AKA `Zulu` or `GMT`): Coordinated Universal Time (UTC) is the primary time standard by which the world regulates clocks and time. It is time relative to `0°` longitude and is not adjusted for daylight saving time. ([from Wikipedia](https://en.wikipedia.org/wiki/ISO_8601)).\n- Conversion to UTC, or between time zones, may depend on daylight savings\n\n*Examples: April 3, 2023 standardized to ISO 8601*\n\n```{r}\n\n#| label: tbl-datetime1\n#| echo: FALSE\n#| message: FALSE\n#| warnings: FALSE\n#| results: 'asis'}\n\ntab1 <-\n tibble(\n Description = c(\n \"Date\",\n \"Date and Time with timezone offset\",\n \"Date and Time in UTC\",\n \"Time Interval in UTC (April 3 - 5, 2023)\"\n ),\n \"Written in ISO 8601\" = c(\n \"2023-04-03\",\n \"2023-04-03T18:29:38+00:00\",\n \"2023-04-03T18:29:38Z\",\n \"2023-04-03T18:29:38Z/2023-04-05T00:29:38Z\"\n )\n )\n\nflextable(tab1) %>%\n #set_caption(caption = \"\") %>%\n autofit() %>% \n fontsize(size = 9) %>% \n theme_zebra()\n\n```\n\n*Examples: different styles of timezone annotation*\n\n```{r}\n\n#| label: tbl-datetime2\n#| echo: FALSE\n#| message: FALSE\n#| warnings: FALSE\n#| results: 'asis'}\n\ntab2 <-\n tibble(\n \"Description\" = c(\"Date and Time with timezone offset\", \"Date and Time in UTC\"),\n \"Example\" = c(\"2023-04-03T18:29:38+00:00\", \"2023-04-03T18:29:38Z\"),\n \"Annotation\" = c(\n \"YYYY-MM-DD[the letter capital T]HH:MM:SS+[Timezone offset]\",\n \"YYYY-MM-DD[capital T]HH:MM:SS+[capital Z to indicate an offset of zero]\"\n )\n )\n\n\nflextable(tab1) %>%\n #set_caption(caption = \"\") %>%\n autofit() %>% \n fontsize(size = 9) %>% \n theme_zebra()\n\n```\n\n### Top References\n\n- ISO 8601 wiki: \n- R package lubridate, OlsonNames()\n- Python go-to package, datetime \n- Article on datetime uncertainty: \n- Map of offset from UTC: \n- Nice time converter: \n\n## Match scientific names to a taxonomic authority\n\n### Why?\n\n- To integrate or aggregate datasets, we need a common frame of reference for taxonomic name\n- Provides an anchor for the taxonomy as scientific understanding evolves.\n\n### Key Information\n\n- Definition: As used here, a taxonomic authority is an online resource that maintains up-to-date species-level classification information and provides persistent identifiers for taxonomic classifications. Example: For the species *Balaenoptera borealis* (Lesson, 1828), the WoRMS taxonomic authority ID link is and the LSID is `urn:lsid:marinespecies.org:taxname:137088`.\n- Use an existing taxonomic authority (e.g. [World Register of Marine Species](https://www.marinespecies.org) , [Integrated Taxonomic Information System](https://itis.gov/) , [NCBI taxonomy](https://www.ncbi.nlm.nih.gov/taxonomy)) and include the authority who manages said information in your metadata\n- List of many authorities can be found here: \n- Make yourself aware of the structure, limits, and history of the authority you are using.\n- Adopt standard binomial nomenclature, when possible\n- When possible, reference the unique identifier in addition to the nomenclature.\n- Always save and document the originally recorded name.\n- Put notes about identification uncertainty in a separate column.\n- Many authorities have APIs through which you can match names to identifiers.\n\n### Top References\n\n- R packages\n - taxize is a taxonomic toolbelt for R. taxize wraps APIs for a large suite of taxonomic databases available on the web\\\n \n - worrms is an API client for [World Register of Marine Species](http://www.marinespecies.org/)\\\n \n - worms: another API client for WoRMS\\\n \n - Ritis: API client for ITIS \\\n- Python packages\n - WoRMS API client\\\n \n- Global Names Resolver to compare taxonomic concepts across authorities\\\n \n- Article: Recommendations for the Standardisation of Open Taxonomic Nomenclature for Image-Based Identifications\\\n \n- TDWG 2022 Keynote: Richard Pyle, \"An Introduction to the Scientific Names of Organisms and the Taxon Concepts they Represent\"\\\n \n\n## Record latitude and longitude in decimal degrees in WGS84\n\n```{r xkcd2, echo = FALSE, out.width=\"40%\", fig.align=\"center\", fig.cap=\"https://imgs.xkcd.com/comics/coordinate_precision.png\"}\n\nknitr::include_graphics('https://imgs.xkcd.com/comics/coordinate_precision.png')\n\n```\n\n### Why?\n\n- Users have to know where you collected this data, which requires a latitude, longitude, reference system and uncertainty.\n- Decimal-degrees avoids special symbols (`°` or `‘`) which is preferable for machine readable formats\n- `WGS84` is a reference coordinate system that is widely used and incorporated in many GPS units and tools, and recognized as a standard by many government agencies.\n\n### Key Information\n\n- If possible, encourage data providers to confirm, and record, the WGS84 datum prior to data collection.\n- Understand and report the device/instrument uncertainty associated with your coordinates because it affects the usability of your data.\n- Consider including the vertical component (altitude, depth, height off bottom, elevation, etc)\n- Generally speaking, `degrees-minutes-seconds (DMS)` can be converted to `decimal-degrees (DD)` by:\n - `DD = d + (min/60) + (sec/3600)`\n - Watch out for mixed formats, like degrees, `decimal-minutes (DDM)`.\n- Degrees West and South become negative in DD.\n - Values for longitude range from `-180` to `180`, inclusive.\n - Values for latitude range from `-90` to `90`, inclusive.\n\n*Example Coordinates*\n\n```{r}\n\n#| label: tbl-example_coordinates\n#| echo: FALSE\n\nds <- tibble(\n Format = c(\n \"Decimal Degrees (DD)\",\n \"Degrees Minutes Seconds (DMS)\",\n \"Degrees Decimal Minutes (DM or DDM)\"\n ),\n Example = c(\n 30.50833333,\n paste(\"30\\u00B0\", \"15'\", '10 N'),\n paste(\"30\\u00B0\", \"15.1667 N\")\n )\n)\n\n\nflextable(ds) %>% \n #set_caption(caption = \"\") %>%\n autofit() %>% \n fontsize(size = 9) %>% \n theme_zebra()\n \n```\n\n### Top References\n\n- Existing R/python/ESRI packages/functions\n - R - measurements \n - EML (find \"bounding Coordinates)\n - CF \n- Getting lat/lon to decimal degrees\\\n \n- Some background on precision\n - \n - \n- DMS to DD calculator\\\n -- The three most commonly used datums are WGS84, NAD83, and NAD27. A more complete list can be found here: \n\n## Use persistent unique identifiers\n\n### Why?\n\n- It can be useful to have unique identifiers to unambiguously identify granules of information, e.g. dataset, collection, database, taxonomic concept, etc. This will allow users to precisely refer to the data and allow your data to remain identifiable when aggregated with other datasets.\n- To be able to uniquely identify a record in your data system or across data systems. Useful to create relational databases or merge records.\n- Although it increases workload, it safeguards against confusion and inefficiency in the future.\n\n### Key Information\n\n- There are good reasons to keep an identifier opaque, i.e. it does not indicate anything about the content of information it points to. However, there are also transparent, or semi-opaque identifiers in use that take advantage of semantics to guide humans as well as machines.\n- One way to create a unique identifier is concatenation of sampling event, location, time, enumeration of unique observation or event. (e.g. `Station_95_Date_09JAN1997:14:35:00.000`)\n- Some prefer using opaque identifiers. (e.g. `10FC9784-B30F-48ED-8DB5-FF65A2A9934E`)\n- If there is an existing persistent unique identifier, it's usually a good idea to use it (i.e. when using a taxonomic authority like WoRMS and applying their LSID).\n- It is important to manage any identifiers you create, if they are not managed by an authority (e.g. DOIs).\n- Important that it be persistent (consider samples possibly moving between institutions)\n\n*Examples of PIDs*\n\n```{r}\n\n#| label: tbl-PIDExamples\n#| echo: FALSE\n\n\n# Autowrap isn't working in pdfs for flextable when overridden by font size\n# Hard returns seem to be the answer\nds <- tibble(\n \"Type of PID\" = c(\n \"Digital Object Identifier (DOI)\",\n \"International Geo Sample Number (IGSN)\",\n \"Life Science Identifier (LSID)\",\n \"Open Researcher and Contributor ID (ORCID)\"\n ),\n \"Use Case\" = c(\n \"Actionable persistent link for papers, data, and other digital objects\",\n \"Persistent identifier for physical samples\",\n \"Persistent structured method for biologically significant data\",\n \"Persistent actionable link for individuals\"\n ),\n \"Example\" = c(\n \"https://doi.org/10.6084/m9.figshare.16806712.v2\",\n \"http://igsn.org/AU1243>\",\n \"urn:lsid:marinespecies.org:taxname:218214\",\n \"https://orcid.org/0000-0002-4391-107X\"\n )\n)\n\nflextable(ds) %>% \n#set_caption(caption = \"\") %>%\n #set_table_properties(layout = \"autofit\") %>% \n fontsize(size = 9) %>% \n width(j = 1,\n width = 1.5) %>%\n width(j = 2,\n width = 1.5) %>% \n width(j = 3,\n width = 3) %>% \n theme_zebra() \n \n```\n\n### Top References\n\n- Software and Packages to generate uuids:\n - R - uuid \n - python - uuid \n - \n - \n- Guidance on how to use GUIDs (Globally Unique Identifiers) to meet specific requirements of the biodiversity information community\\\n \n- Use of globally unique identifiers (GUIDs) to link herbarium specimen records to physical specimens\\\n \n- A Beginner's Guide to Persistent Identifiers\\\n \n","srcMarkdownNoYaml":""},"formats":{"html":{"identifier":{"display-name":"HTML","target-format":"html","base-format":"html"},"execute":{"fig-width":7,"fig-height":5,"fig-format":"retina","fig-dpi":96,"df-print":"default","error":false,"eval":true,"cache":null,"freeze":false,"echo":false,"output":true,"warning":false,"include":true,"keep-md":false,"keep-ipynb":false,"ipynb":null,"enabled":null,"daemon":null,"daemon-restart":false,"debug":false,"ipynb-filters":[],"message":false,"engine":"knitr"},"render":{"keep-tex":false,"keep-source":false,"keep-hidden":false,"prefer-html":false,"output-divs":true,"output-ext":"html","fig-align":"default","fig-pos":null,"fig-env":null,"code-fold":"none","code-overflow":"scroll","code-link":false,"code-line-numbers":false,"code-tools":false,"tbl-colwidths":"auto","merge-includes":true,"inline-includes":false,"preserve-yaml":false,"latex-auto-mk":true,"latex-auto-install":true,"latex-clean":true,"latex-max-runs":10,"latex-makeindex":"makeindex","latex-makeindex-opts":[],"latex-tlmgr-opts":[],"latex-input-paths":[],"latex-output-dir":null,"link-external-icon":true,"link-external-newwindow":true,"self-contained-math":false,"format-resources":[],"notebook-links":true,"format-links":true,"link-external-filter":"^(?:http:|https:)\\/\\/esipfed\\.github\\.io"},"pandoc":{"standalone":true,"wrap":"none","default-image-extension":"png","to":"html","output-file":"SOFTWARE_READY.html"},"language":{"toc-title-document":"Table 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principles (findability, accessibility, interoperability, reusability)\n- Makes data more socially equitable, supporting open science. Proprietary formats can depend on software that require licenses, which not everyone can afford/has access to.\n\n### Key Information\n\n- *Non-proprietary formats* are supported by more than one developer and can be accessed with different software systems. For example, comma separated values (CSV) format is becoming an increasingly popular non-proprietary format.\n- A [*proprietary file format*](https://en.wikipedia.org/wiki/Proprietary_file_format) is a file format of a company, organization, or individual that contains data that is ordered and stored according to a particular encoding-scheme, designed by the company or organization to be secret or with restricted access, such that the decoding and interpretation of this stored data is easily accomplished only with particular software or hardware that the company itself has developed. There may also be costs associated with it and access may be limited. Examples include `Microsoft Excel (xlsx)` and `ESRI shapefiles (shp)`.\n- Many applications (e.g. Microsoft Office) allow exporting in multiple formats.\n\n### Top References\n\n- Table of commonly used formats for common data types\\\n \n\n- A more detailed table that is specific to US Federal records management\\\n \n\n## Structure tabular data in tidy/long format\n\n### Why?\n\n*This is specifically intended for tabular data*\n\n- There is a clear and easy to understand structure that can make your data more machine readable and easier to analyze/visualize\n - Clear structure: one observation per row\n - Data are as atomic as possible (e.g., don't mix types in field)\n- In the biological data community, tidy formats are more likely to work with commonly-used software\n- Easier to aggregate data across multiple files\n\n### Key Information\n\nExample of Wide Format\n\n```{r}\n\n#| label: tbl-tidyformat wide\n\n\n\nlibrary(dplyr)\nlibrary(flextable)\n#library(gt)\n\nexample_df <- data.frame(species = c(\"Tilia americana\",\n \"Pinus strobus\"),\n site_01 = sample(0:5, size = 2),\n site_02 = sample(0:5, size = 2),\n site_03 = sample(0:5, size = 2))\n\nlong_example <- tidyr::pivot_longer(data = example_df, cols = site_01:site_03, names_to = \"site\", values_to = \"count\")\n\n# flextable is awesome, but captions aren't working yet: %\n set_caption(caption = \"Wide Format\") %>% \n fontsize(size = 9) %>% \n autofit() %>% \n theme_zebra()\n\n```\n\nExample of Long Format\n\n```{r}\n\n#| label: tbl-tidyformat long\n\n\n\nlibrary(dplyr)\nlibrary(flextable)\n#library(gt)\n\nexample_df <- data.frame(species = c(\"Tilia americana\",\n \"Pinus strobus\"),\n site_01 = sample(0:5, size = 2),\n site_02 = sample(0:5, size = 2),\n site_03 = sample(0:5, size = 2))\n\nlong_example <- tidyr::pivot_longer(data = example_df, cols = site_01:site_03, names_to = \"site\", values_to = \"count\")\n\n# flextable is awesome, but captions aren't working yet: %\n set_caption(caption = \"Long Format\") %>%\n fontsize(size = 9) %>% \n autofit() %>% theme_zebra()\n\n# example_df %>% \n# gt(caption = \"Wide Format\")\n# \n# long_example %>% \n# gt(caption = \"Long Format\")\n\n```\n\n- Can be tricky working with multiple column datatypes\n- Don't use colors or text formatting in tabular data, and only include column names as metadata. All other notes, definitions, etc. should be in an external metadata file (e.g. data dictionary)\n\n### Top References\n\n- Wickham, H. (2014). Tidy Data. Journal of Statistical Software, 59(10), 1--23.\\\n \n- Data Sharing and Management Snafu in 3 Short Acts (video)\\\n \n- Tips for working with data in BASH\\\n \n- Data Organization in Spreadsheets for Ecologists\\\n \n- Cleaning Data and Quality Control\\\n \n\n## Follow ISO 8601 for dates\n\n```{r xkcd1, echo = FALSE, out.width=\"40%\", fig.align=\"center\", fig.cap=\"https://imgs.xkcd.com/comics/iso_8601.png\"}\n\nknitr::include_graphics('https://imgs.xkcd.com/comics/iso_8601.png')\n\n```\n\n### Why?\n\n- Internationally accepted format used across multiple schemas (e.g. `Darwin Core`, `EML`, `ISO 19115`)\n- Removes ambiguity related to timezone, daylight savings time changes, and time of day\n- Better software integration of time date/time elements\n\n### Key Information\n\n- UTC (AKA `Zulu` or `GMT`): Coordinated Universal Time (UTC) is the primary time standard by which the world regulates clocks and time. It is time relative to `0°` longitude and is not adjusted for daylight saving time. ([from Wikipedia](https://en.wikipedia.org/wiki/ISO_8601)).\n- Conversion to UTC, or between time zones, may depend on daylight savings\n\n*Examples: April 3, 2023 standardized to ISO 8601*\n\n```{r}\n\n#| label: tbl-datetime1\n#| echo: FALSE\n#| message: FALSE\n#| warnings: FALSE\n#| results: 'asis'}\n\ntab1 <-\n tibble(\n Description = c(\n \"Date\",\n \"Date and Time with timezone offset\",\n \"Date and Time in UTC\",\n \"Time Interval in UTC (April 3 - 5, 2023)\"\n ),\n \"Written in ISO 8601\" = c(\n \"2023-04-03\",\n \"2023-04-03T18:29:38+00:00\",\n \"2023-04-03T18:29:38Z\",\n \"2023-04-03T18:29:38Z/2023-04-05T00:29:38Z\"\n )\n )\n\nflextable(tab1) %>%\n #set_caption(caption = \"\") %>%\n autofit() %>% \n fontsize(size = 9) %>% \n theme_zebra()\n\n```\n\n*Examples: different styles of timezone annotation*\n\n```{r}\n\n#| label: tbl-datetime2\n#| echo: FALSE\n#| message: FALSE\n#| warnings: FALSE\n#| results: 'asis'}\n\ntab2 <-\n tibble(\n \"Description\" = c(\"Date and Time with timezone offset\", \"Date and Time in UTC\"),\n \"Example\" = c(\"2023-04-03T18:29:38+00:00\", \"2023-04-03T18:29:38Z\"),\n \"Annotation\" = c(\n \"YYYY-MM-DD[the letter capital T]HH:MM:SS+[Timezone offset]\",\n \"YYYY-MM-DD[capital T]HH:MM:SS+[capital Z to indicate an offset of zero]\"\n )\n )\n\n\nflextable(tab1) %>%\n #set_caption(caption = \"\") %>%\n autofit() %>% \n fontsize(size = 9) %>% \n theme_zebra()\n\n```\n\n### Top References\n\n- ISO 8601 wiki: \n- R package lubridate, OlsonNames()\n- Python go-to package, datetime \n- Article on datetime uncertainty: \n- Map of offset from UTC: \n- Nice time converter: \n\n## Match scientific names to a taxonomic authority\n\n### Why?\n\n- To integrate or aggregate datasets, we need a common frame of reference for taxonomic name\n- Provides an anchor for the taxonomy as scientific understanding evolves.\n\n### Key Information\n\n- Definition: As used here, a taxonomic authority is an online resource that maintains up-to-date species-level classification information and provides persistent identifiers for taxonomic classifications. Example: For the species *Balaenoptera borealis* (Lesson, 1828), the WoRMS taxonomic authority ID link is and the LSID is `urn:lsid:marinespecies.org:taxname:137088`.\n- Use an existing taxonomic authority (e.g. [World Register of Marine Species](https://www.marinespecies.org) , [Integrated Taxonomic Information System](https://itis.gov/) , [NCBI taxonomy](https://www.ncbi.nlm.nih.gov/taxonomy)) and include the authority who manages said information in your metadata\n- List of many authorities can be found here: \n- Make yourself aware of the structure, limits, and history of the authority you are using.\n- Adopt standard binomial nomenclature, when possible\n- When possible, reference the unique identifier in addition to the nomenclature.\n- Always save and document the originally recorded name.\n- Put notes about identification uncertainty in a separate column.\n- Many authorities have APIs through which you can match names to identifiers.\n\n### Top References\n\n- R packages\n - taxize is a taxonomic toolbelt for R. taxize wraps APIs for a large suite of taxonomic databases available on the web\\\n \n - worrms is an API client for [World Register of Marine Species](http://www.marinespecies.org/)\\\n \n - worms: another API client for WoRMS\\\n \n - Ritis: API client for ITIS \\\n- Python packages\n - WoRMS API client\\\n \n- Global Names Resolver to compare taxonomic concepts across authorities\\\n \n- Article: Recommendations for the Standardisation of Open Taxonomic Nomenclature for Image-Based Identifications\\\n \n- TDWG 2022 Keynote: Richard Pyle, \"An Introduction to the Scientific Names of Organisms and the Taxon Concepts they Represent\"\\\n \n\n## Record latitude and longitude in decimal degrees in WGS84\n\n```{r xkcd2, echo = FALSE, out.width=\"40%\", fig.align=\"center\", fig.cap=\"https://imgs.xkcd.com/comics/coordinate_precision.png\"}\n\nknitr::include_graphics('https://imgs.xkcd.com/comics/coordinate_precision.png')\n\n```\n\n### Why?\n\n- Users have to know where you collected this data, which requires a latitude, longitude, reference system and uncertainty.\n- Decimal-degrees avoids special symbols (`°` or `‘`) which is preferable for machine readable formats\n- `WGS84` is a reference coordinate system that is widely used and incorporated in many GPS units and tools, and recognized as a standard by many government agencies.\n\n### Key Information\n\n- If possible, encourage data providers to confirm, and record, the WGS84 datum prior to data collection.\n- Understand and report the device/instrument uncertainty associated with your coordinates because it affects the usability of your data.\n- Consider including the vertical component (altitude, depth, height off bottom, elevation, etc)\n- Generally speaking, `degrees-minutes-seconds (DMS)` can be converted to `decimal-degrees (DD)` by:\n - `DD = d + (min/60) + (sec/3600)`\n - Watch out for mixed formats, like degrees, `decimal-minutes (DDM)`.\n- Degrees West and South become negative in DD.\n - Values for longitude range from `-180` to `180`, inclusive.\n - Values for latitude range from `-90` to `90`, inclusive.\n\n*Example Coordinates*\n\n```{r}\n\n#| label: tbl-example_coordinates\n#| echo: FALSE\n\nds <- tibble(\n Format = c(\n \"Decimal Degrees (DD)\",\n \"Degrees Minutes Seconds (DMS)\",\n \"Degrees Decimal Minutes (DM or DDM)\"\n ),\n Example = c(\n 30.50833333,\n paste(\"30\\u00B0\", \"15'\", '10 N'),\n paste(\"30\\u00B0\", \"15.1667 N\")\n )\n)\n\n\nflextable(ds) %>% \n #set_caption(caption = \"\") %>%\n autofit() %>% \n fontsize(size = 9) %>% \n theme_zebra()\n \n```\n\n### Top References\n\n- Existing R/python/ESRI packages/functions\n - R - measurements \n - EML (find \"bounding Coordinates)\n - CF \n- Getting lat/lon to decimal degrees\\\n \n- Some background on precision\n - \n - \n- DMS to DD calculator\\\n -- The three most commonly used datums are WGS84, NAD83, and NAD27. A more complete list can be found here: \n\n## Use persistent unique identifiers\n\n### Why?\n\n- It can be useful to have unique identifiers to unambiguously identify granules of information, e.g. dataset, collection, database, taxonomic concept, etc. This will allow users to precisely refer to the data and allow your data to remain identifiable when aggregated with other datasets.\n- To be able to uniquely identify a record in your data system or across data systems. Useful to create relational databases or merge records.\n- Although it increases workload, it safeguards against confusion and inefficiency in the future.\n\n### Key Information\n\n- There are good reasons to keep an identifier opaque, i.e. it does not indicate anything about the content of information it points to. However, there are also transparent, or semi-opaque identifiers in use that take advantage of semantics to guide humans as well as machines.\n- One way to create a unique identifier is concatenation of sampling event, location, time, enumeration of unique observation or event. (e.g. `Station_95_Date_09JAN1997:14:35:00.000`)\n- Some prefer using opaque identifiers. (e.g. `10FC9784-B30F-48ED-8DB5-FF65A2A9934E`)\n- If there is an existing persistent unique identifier, it's usually a good idea to use it (i.e. when using a taxonomic authority like WoRMS and applying their LSID).\n- It is important to manage any identifiers you create, if they are not managed by an authority (e.g. DOIs).\n- Important that it be persistent (consider samples possibly moving between institutions)\n\n*Examples of PIDs*\n\n```{r}\n\n#| label: tbl-PIDExamples\n#| echo: FALSE\n\n\n# Autowrap isn't working in pdfs for flextable when overridden by font size\n# Hard returns seem to be the answer\nds <- tibble(\n \"Type of PID\" = c(\n \"Digital Object Identifier (DOI)\",\n \"International Geo Sample Number (IGSN)\",\n \"Life Science Identifier (LSID)\",\n \"Open Researcher and Contributor ID (ORCID)\"\n ),\n \"Use Case\" = c(\n \"Actionable persistent link for papers, data, and other digital objects\",\n \"Persistent identifier for physical samples\",\n \"Persistent structured method for biologically significant data\",\n \"Persistent actionable link for individuals\"\n ),\n \"Example\" = c(\n \"https://doi.org/10.6084/m9.figshare.16806712.v2\",\n \"http://igsn.org/AU1243>\",\n \"urn:lsid:marinespecies.org:taxname:218214\",\n \"https://orcid.org/0000-0002-4391-107X\"\n )\n)\n\nflextable(ds) %>% \n#set_caption(caption = \"\") %>%\n #set_table_properties(layout = \"autofit\") %>% \n fontsize(size = 9) %>% \n width(j = 1,\n width = 1.5) %>%\n width(j = 2,\n width = 1.5) %>% \n width(j = 3,\n width = 3) %>% \n theme_zebra() \n \n```\n\n### Top References\n\n- Software and Packages to generate uuids:\n - R - uuid \n - python - uuid \n - \n - \n- Guidance on how to use GUIDs (Globally Unique Identifiers) to meet specific requirements of the biodiversity information community\\\n \n- Use of globally unique identifiers (GUIDs) to link herbarium specimen records to physical specimens\\\n \n- A Beginner's Guide to Persistent Identifiers\\\n 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-{"title":"Preface","markdown":{"yaml":{},"headingText":"Preface","headingAttr":{"id":"","classes":["unnumbered"],"keyvalue":[]},"containsRefs":false,"markdown":"\n\n## ESIP BDS Primer Guide Suite of Documents\n\nThe [ESIP Biological Data Standards Cluster](https://wiki.esipfed.org/Biological_Data_Standards_Cluster) formed in 2020 to maximize data relevance and utility for understanding changes in biodiversity over time. To accomplish this the cluster facilitates guidance, best practice documentation, training, and community building for the US biological data community. The first product from this cluster [Biological Data Standards Primer](https://doi.org/10.6084/m9.figshare.16806712.v2), while an easy to digest resource, does not provide the context data managers need to decide which standards to use for the data they are working with. The guides are intended to be a bridge between the full, lengthy standards documentation, and the short primer quick reference. The first document being developed is for the \"Make Your Data Software Ready?\" section of the primer.\n\n### How to contribute\n\nIf you would like to suggest changes or additions to the current version of the best practice documents, please use the [GitHub issues](https://github.com/ESIPFed/bds-primer-best-practices/issues/new/choose) to document your request. The current draft can be seen as a rendered webpage [here](https://esipfed.github.io/bds-primer-best-practices/introduction.html).\n\n### Structure \n\nThe structure for each section is:\n\n- Value proposition (Why?)\n- List / key information (bulleted)\n- References list\n","srcMarkdownNoYaml":"\n# Preface {.unnumbered}\n\n## ESIP BDS Primer Guide Suite of Documents\n\nThe [ESIP Biological Data Standards Cluster](https://wiki.esipfed.org/Biological_Data_Standards_Cluster) formed in 2020 to maximize data relevance and utility for understanding changes in biodiversity over time. To accomplish this the cluster facilitates guidance, best practice documentation, training, and community building for the US biological data community. The first product from this cluster [Biological Data Standards Primer](https://doi.org/10.6084/m9.figshare.16806712.v2), while an easy to digest resource, does not provide the context data managers need to decide which standards to use for the data they are working with. The guides are intended to be a bridge between the full, lengthy standards documentation, and the short primer quick reference. The first document being developed is for the \"Make Your Data Software Ready?\" section of the primer.\n\n### How to contribute\n\nIf you would like to suggest changes or additions to the current version of the best practice documents, please use the [GitHub issues](https://github.com/ESIPFed/bds-primer-best-practices/issues/new/choose) to document your request. The current draft can be seen as a rendered webpage [here](https://esipfed.github.io/bds-primer-best-practices/introduction.html).\n\n### Structure \n\nThe structure for each section is:\n\n- Value proposition (Why?)\n- List / key information (bulleted)\n- References list\n"},"formats":{"html":{"identifier":{"display-name":"HTML","target-format":"html","base-format":"html"},"execute":{"fig-width":7,"fig-height":5,"fig-format":"retina","fig-dpi":96,"df-print":"default","error":false,"eval":true,"cache":null,"freeze":false,"echo":false,"output":true,"warning":false,"include":true,"keep-md":false,"keep-ipynb":false,"ipynb":null,"enabled":null,"daemon":null,"daemon-restart":false,"debug":false,"ipynb-filters":[],"message":false,"engine":"markdown"},"render":{"keep-tex":false,"keep-source":false,"keep-hidden":false,"prefer-html":false,"output-divs":true,"output-ext":"html","fig-align":"default","fig-pos":null,"fig-env":null,"code-fold":"none","code-overflow":"scroll","code-link":false,"code-line-numbers":false,"code-tools":false,"tbl-colwidths":"auto","merge-includes":true,"inline-includes":false,"preserve-yaml":false,"latex-auto-mk":true,"latex-auto-install":true,"latex-clean":true,"latex-max-runs":10,"latex-makeindex":"makeindex","latex-makeindex-opts":[],"latex-tlmgr-opts":[],"latex-input-paths":[],"latex-output-dir":null,"link-external-icon":true,"link-external-newwindow":true,"self-contained-math":false,"format-resources":[],"notebook-links":true,"format-links":true,"link-external-filter":"^(?:http:|https:)\\/\\/esipfed\\.github\\.io"},"pandoc":{"standalone":true,"wrap":"none","default-image-extension":"png","to":"html","output-file":"index.html"},"language":{"toc-title-document":"Table 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to maximize data relevance and utility for understanding changes in biodiversity over time. To accomplish this the cluster facilitates guidance, best practice documentation, training, and community building for the US biological data community. The first product from this cluster [Biological Data Standards Primer](https://doi.org/10.6084/m9.figshare.16806712.v2), while an easy to digest resource, does not provide the context data managers need to decide which standards to use for the data they are working with. The guides are intended to be a bridge between the full, lengthy standards documentation, and the short primer quick reference. The first document being developed is for the \"Make Your Data Software Ready?\" section of the primer.\n\n### How to contribute\n\nIf you would like to suggest changes or additions to the current version of the best practice documents, please use the [GitHub issues](https://github.com/ESIPFed/bds-primer-best-practices/issues/new/choose) to document your request. The current draft can be seen as a rendered webpage [here](https://esipfed.github.io/bds-primer-best-practices/index.html).\n\n### Structure\n\nThe structure for each section is:\n\n- Value proposition (Why?)\n- List / key information (bulleted)\n- References list\n","srcMarkdownNoYaml":"\n\n# Preface {.unnumbered}\n\n## ESIP BDS Primer Guide Suite of Documents\n\nThe [ESIP Biological Data Standards Cluster](https://wiki.esipfed.org/Biological_Data_Standards_Cluster) formed in 2020 to maximize data relevance and utility for understanding changes in biodiversity over time. To accomplish this the cluster facilitates guidance, best practice documentation, training, and community building for the US biological data community. The first product from this cluster [Biological Data Standards Primer](https://doi.org/10.6084/m9.figshare.16806712.v2), while an easy to digest resource, does not provide the context data managers need to decide which standards to use for the data they are working with. The guides are intended to be a bridge between the full, lengthy standards documentation, and the short primer quick reference. The first document being developed is for the \"Make Your Data Software Ready?\" section of the primer.\n\n### How to contribute\n\nIf you would like to suggest changes or additions to the current version of the best practice documents, please use the [GitHub issues](https://github.com/ESIPFed/bds-primer-best-practices/issues/new/choose) to document your request. The current draft can be seen as a rendered webpage [here](https://esipfed.github.io/bds-primer-best-practices/index.html).\n\n### Structure\n\nThe structure for each section is:\n\n- Value proposition (Why?)\n- List / key information (bulleted)\n- References list\n"},"formats":{"html":{"identifier":{"display-name":"HTML","target-format":"html","base-format":"html"},"execute":{"fig-width":7,"fig-height":5,"fig-format":"retina","fig-dpi":96,"df-print":"default","error":false,"eval":true,"cache":null,"freeze":false,"echo":false,"output":true,"warning":false,"include":true,"keep-md":false,"keep-ipynb":false,"ipynb":null,"enabled":null,"daemon":null,"daemon-restart":false,"debug":false,"ipynb-filters":[],"message":false,"engine":"markdown"},"render":{"keep-tex":false,"keep-source":false,"keep-hidden":false,"prefer-html":false,"output-divs":true,"output-ext":"html","fig-align":"default","fig-pos":null,"fig-env":null,"code-fold":"none","code-overflow":"scroll","code-link":false,"code-line-numbers":false,"code-tools":false,"tbl-colwidths":"auto","merge-includes":true,"inline-includes":false,"preserve-yaml":false,"latex-auto-mk":true,"latex-auto-install":true,"latex-clean":true,"latex-max-runs":10,"latex-makeindex":"makeindex","latex-makeindex-opts":[],"latex-tlmgr-opts":[],"latex-input-paths":[],"latex-output-dir":null,"link-external-icon":true,"link-external-newwindow":true,"self-contained-math":false,"format-resources":[],"notebook-links":true,"format-links":true,"link-external-filter":"^(?:http:|https:)\\/\\/esipfed\\.github\\.io"},"pandoc":{"standalone":true,"wrap":"none","default-image-extension":"png","to":"html","number-offset":1,"toc":false,"output-file":"index.html"},"language":{"toc-title-document":"Table 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High","listing-page-field-date":"Date","listing-page-field-title":"Title","listing-page-field-description":"Description","listing-page-field-author":"Author","listing-page-field-filename":"File Name","listing-page-field-filemodified":"Modified","listing-page-field-subtitle":"Subtitle","listing-page-field-readingtime":"Reading Time","listing-page-field-categories":"Categories","listing-page-minutes-compact":"{0} min","listing-page-category-all":"All","listing-page-no-matches":"No matching items"},"metadata":{"number-depth":2,"editor":"visual","lang":"en"},"extensions":{"book":{"selfContainedOutput":true}}}},"projectFormats":["html","pdf","docx"]} \ No newline at end of file diff --git a/.quarto/xref/12086bf0 b/.quarto/xref/12086bf0 index c71ae86..d681de4 100644 --- a/.quarto/xref/12086bf0 +++ b/.quarto/xref/12086bf0 @@ -1 +1 @@ -{"entries":[],"headings":["preface","esip-bds-primer-guide-suite-of-documents","how-to-contribute","structure"],"options":{"chapters":true}} \ No newline at end of file +{"headings":["preface","esip-bds-primer-guide-suite-of-documents","how-to-contribute","structure"],"entries":[],"options":{"chapters":true}} \ No newline at end of file diff --git a/.quarto/xref/4083d7b9 b/.quarto/xref/4083d7b9 index 4252d54..1006091 100644 --- a/.quarto/xref/4083d7b9 +++ b/.quarto/xref/4083d7b9 @@ -1 +1 @@ -{"entries":[],"options":{"chapters":true},"headings":["ecological-metadata-language-eml","what-is-it","why","key-information","top-references","iso-19115","what-is-it-1","why-1","what","top-references-1","minimum-information-about-any-x-sequence-mixs","what-is-it-2","why-2","key-information-1","top-references-2"]} \ No newline at end of file +{"options":{"chapters":true},"entries":[],"headings":["ecological-metadata-language-eml","what-is-it","why","key-information","top-references","iso-19115","what-is-it-1","why-1","what","top-references-1","minimum-information-about-any-x-sequence-mixs","who","what-is-it-2","why-2","key-information-1","top-references-2"]} \ No newline at end of file diff --git a/.quarto/xref/e95e2d34 b/.quarto/xref/e95e2d34 index de36463..8e22d34 100644 --- a/.quarto/xref/e95e2d34 +++ b/.quarto/xref/e95e2d34 @@ -1 +1 @@ -{"entries":[],"headings":["use-non-proprietary-formats","why","key-information","top-references","structure-tabular-data-in-tidylong-format","why-1","key-information-1","top-references-1","follow-iso-8601-for-dates","why-2","key-information-2","top-references-2","match-scientific-names-to-a-taxonomic-authority","why-3","key-information-3","top-references-3","record-latitude-and-longitude-in-decimal-degrees-in-wgs84","why-4","key-information-4","top-references-4","use-persistent-unique-identifiers","why-5","key-information-5","top-references-5"],"options":{"chapters":true}} \ No newline at end of file +{"options":{"chapters":true},"entries":[],"headings":["use-non-proprietary-formats","why","key-information","top-references","structure-tabular-data-in-tidylong-format","why-1","key-information-1","top-references-1","follow-iso-8601-for-dates","why-2","key-information-2","top-references-2","match-scientific-names-to-a-taxonomic-authority","why-3","key-information-3","top-references-3","record-latitude-and-longitude-in-decimal-degrees-in-wgs84","why-4","key-information-4","top-references-4","use-persistent-unique-identifiers","why-5","key-information-5","top-references-5"]} \ No newline at end of file diff --git a/CONTEXT_UNDERSTANDABILITY.qmd b/CONTEXT_UNDERSTANDABILITY.qmd index 99d77e2..75e7395 100644 --- a/CONTEXT_UNDERSTANDABILITY.qmd +++ b/CONTEXT_UNDERSTANDABILITY.qmd @@ -1,15 +1,14 @@ -# Provide Context and Understandability to Your Data {.unnumbered} - +# Provide Context and Understandability to Your Data ## Ecological Metadata Language (EML) ### What Is It? -Ecological Metadata Language (EML) is an XML schema. An EML instance (XML document) holds metadata to describe one or more data objects. Data tables are the most common, but almost any data object can be accommodated. +EML is a community-developed metadata schema designed for ecological data, which encompasses biological data. EML is normally presented as [Extensible Markup Language (XML)](https://www.w3schools.com/xml/). An EML instance (XML document) holds metadata to describe one or more data objects. Data tables are the most common, but almost any data object can be accommodated. ### Why? -- Provide context to your data. +- Provide context to your data and improve reproducability of the data. - Can capture linked data relationships within EML (dataset series) - Standardized representation of information. - EML was designed for ecological data, which encompasses biological data. @@ -87,9 +86,13 @@ Content standard for describing geographic data sponsored by the International S ## Minimum Information about any (x) Sequence (MIxS) +### Who? + +This is a standard for molecular data, like DNA and RNA. It is used by molecular biologist and ecologists who generate, manage and archive these type of sequence data. + ### What is it? -A set of checklists and packages for genomic sequence data +A set of checklists and packages for genomic sequence data. ### Why? @@ -108,7 +111,7 @@ A set of checklists and packages for genomic sequence data - [![MIxS Structure](http://www.gensc.org/images/mixs_ext_graphic-1024x731.png)](http://www.gensc.org/pages/standards-intro.html) ### Top References - + - [MIxS Term Search Tool](http://www.gensc.org/pages/standards/search-terms.html) - [Genomic Standards Consortium term list](https://genomicsstandardsconsortium.github.io/mixs/) diff --git a/SOFTWARE_READY.qmd b/SOFTWARE_READY.qmd index 036d345..988f38e 100644 --- a/SOFTWARE_READY.qmd +++ b/SOFTWARE_READY.qmd @@ -1,4 +1,4 @@ -# Make Your Data Software Ready {.unnumbered} +# Make Your Data Software Ready ## Use non-proprietary formats @@ -18,7 +18,7 @@ - Table of commonly used formats for common data types\ - + - A more detailed table that is specific to US Federal records management\ diff --git a/_quarto.yml b/_quarto.yml index 8e24bbd..406c9cb 100644 --- a/_quarto.yml +++ b/_quarto.yml @@ -14,7 +14,10 @@ book: #- INTEROPERABLE_DATA.qmd #- SHARE_DATA_WEB.qmd - SOFTWARE_READY.qmd - + +number-depth: 2 +number-offset: 1 + execute: echo: FALSE warning: FALSE @@ -28,11 +31,11 @@ format: link-external-icon: true link-external-newwindow: true link-external-filter: '^(?:http:|https:)\/\/esipfed\.github\.io' + toc: false + pdf: default docx: toc: false # This isn't populating for some reason - #toc-depth: 2 - number-sections: true fig-align: center #tbl-colwidths: auto lang: en diff --git a/docs/CONTEXT_UNDERSTANDABILITY.html b/docs/CONTEXT_UNDERSTANDABILITY.html index a8f12ee..8ca554f 100644 --- a/docs/CONTEXT_UNDERSTANDABILITY.html +++ b/docs/CONTEXT_UNDERSTANDABILITY.html @@ -7,7 +7,7 @@ -ESIP Biological Data Cluster (BDS) Primer Guide - Provide Context and Understandability to Your Data +ESIP Biological Data Cluster (BDS) Primer Guide - 1  Provide Context and Understandability to Your Data

species

site_01

site_02

site_03

Tilia americana

1

0

2

Pinus strobus

2

1

1

+

species

site_01

site_02

site_03

Tilia americana

5

4

5

Pinus strobus

4

2

0

Example of Long Format

-

species

site

count

Tilia americana

site_01

3

Tilia americana

site_02

3

Tilia americana

site_03

4

Pinus strobus

site_01

2

Pinus strobus

site_02

2

Pinus strobus

site_03

1

+

species

site

count

Tilia americana

site_01

3

Tilia americana

site_02

3

Tilia americana

site_03

0

Pinus strobus

site_01

2

Pinus strobus

site_02

5

Pinus strobus

site_03

5

    @@ -266,8 +223,8 @@

    Top References

-
-

Follow ISO 8601 for dates

+
+

2.3 Follow ISO 8601 for dates

@@ -296,14 +253,14 @@

Key Information

-

Description

Written in ISO 8601

Date

2023-04-03

Date and Time with timezone offset

2023-04-03T18:29:38+00:00

Date and Time in UTC

2023-04-03T18:29:38Z

Time Interval in UTC (April 3 - 5, 2023)

2023-04-03T18:29:38Z/2023-04-05T00:29:38Z

+

Description

Written in ISO 8601

Date

2023-04-03

Date and Time with timezone offset

2023-04-03T18:29:38+00:00

Date and Time in UTC

2023-04-03T18:29:38Z

Time Interval in UTC (April 3 - 5, 2023)

2023-04-03T18:29:38Z/2023-04-05T00:29:38Z

Examples: different styles of timezone annotation

-

Description

Written in ISO 8601

Date

2023-04-03

Date and Time with timezone offset

2023-04-03T18:29:38+00:00

Date and Time in UTC

2023-04-03T18:29:38Z

Time Interval in UTC (April 3 - 5, 2023)

2023-04-03T18:29:38Z/2023-04-05T00:29:38Z

+

Description

Written in ISO 8601

Date

2023-04-03

Date and Time with timezone offset

2023-04-03T18:29:38+00:00

Date and Time in UTC

2023-04-03T18:29:38Z

Time Interval in UTC (April 3 - 5, 2023)

2023-04-03T18:29:38Z/2023-04-05T00:29:38Z

@@ -319,8 +276,8 @@

Top References

-
-

Match scientific names to a taxonomic authority

+
+

2.4 Match scientific names to a taxonomic authority

Why?

    @@ -369,8 +326,8 @@

    Top References

-
-

Record latitude and longitude in decimal degrees in WGS84

+
+

2.5 Record latitude and longitude in decimal degrees in WGS84

@@ -410,7 +367,7 @@

Key Information

-

Format

Example

Decimal Degrees (DD)

30.50833333

Degrees Minutes Seconds (DMS)

30° 15' 10 N

Degrees Decimal Minutes (DM or DDM)

30° 15.1667 N

+

Format

Example

Decimal Degrees (DD)

30.50833333

Degrees Minutes Seconds (DMS)

30° 15' 10 N

Degrees Decimal Minutes (DM or DDM)

30° 15.1667 N

@@ -435,8 +392,8 @@

Top References

-
-

Use persistent unique identifiers

+
+

2.6 Use persistent unique identifiers

Why?

    @@ -459,7 +416,7 @@

    Key Information

    -

    Type of PID

    Use Case

    Example

    Digital Object Identifier (DOI)

    Actionable persistent link for papers, data, and other digital objects

    https://doi.org/10.6084/m9.figshare.16806712.v2

    International Geo Sample Number (IGSN)

    Persistent identifier for physical samples

    http://igsn.org/AU1243>

    Life Science Identifier (LSID)

    Persistent structured method for biologically significant data

    urn:lsid:marinespecies.org:taxname:218214

    Open Researcher and Contributor ID (ORCID)

    Persistent actionable link for individuals

    https://orcid.org/0000-0002-4391-107X

    +

    Type of PID

    Use Case

    Example

    Digital Object Identifier (DOI)

    Actionable persistent link for papers, data, and other digital objects

    https://doi.org/10.6084/m9.figshare.16806712.v2

    International Geo Sample Number (IGSN)

    Persistent identifier for physical samples

    http://igsn.org/AU1243>

    Life Science Identifier (LSID)

    Persistent structured method for biologically significant data

    urn:lsid:marinespecies.org:taxname:218214

    Open Researcher and Contributor ID (ORCID)

    Persistent actionable link for individuals

    https://orcid.org/0000-0002-4391-107X

@@ -738,7 +695,7 @@

Top References