various minor adjustments #79

* minor wording fixes in various places as per Silas' suggestions in #79

common_formatissues.md

@@ -1,8 +1,6 @@
 ## Other Important Data Formatting Steps
 
-Below you will find other important data formatting steps and guidelines that datasets being published to OBIS should adhere to.
-
-**Contents:**
+After creating data tables and mapping terms to DwC, additional data formatting steps may be needed and/or some common issues may arise. On this page, you will find guidelines for specific data formatting cases, including:
 
 - [Temporal issues: dates/times](#temporal-dates-and-times)
 - [Historical data](#historical-data)
@@ -45,8 +43,9 @@ Some specific examples of acceptable ISO 8601 dates are:
 
 It is important to note that although ISO 8601 also supports ordinal dates (YYYY-DDD) and week dates (YYYY-Www-D), these formats are not supported by OBIS. Additionally, ISO 8601 guidelines for [durations](https://en.wikipedia.org/wiki/ISO_8601#Durations) should not be used. Durations for an event (e.g., length of observation) can instead be indicated with the DwC terms [startDayOfYear](https://dwc.tdwg.org/list/#dwc_startDayOfYear) and [endDayOfYear](https://dwc.tdwg.org/list/#dwc_endDayOfYear). Durations refer to the actual length of time an event (e.g., occurrence) occurred, whereas intervals indicate the time period during which an event was recorded.
 
-**A note about intervals…**
-Take care when entering date intervals as, for example, entering 1960/1975-08-04 indicates that the event or observation started any time in 1960, and ended any time on 1975-08-04. If you know the exact date and time, you should specify that information. This also helps for continuous samplings and time-series integrated datasets.
+**A note about intervals:**
+
+> Take care when entering date intervals as, for example, entering 1960/1975-08-04 indicates that the event or observation started any time in 1960, and ended any time on 1975-08-04. If you know the exact date and time, you should specify that information. This also helps for continuous samplings and time-series integrated datasets.
 
 If you have a mix of dates and times for different aspects of a sampling event, you can embed this information in the Event Core table using hierarchies of date structure. To do this, you can use separate records for events, and specify each event date individually. See [example](#how-to-handle-mixed-date-information).
 

format_emof.md

@@ -36,7 +36,7 @@ Other potential fields are shown in the table below (also listed in the [checkli
 * Class Measurement | DwC:measurementValue
 * Class Measurement | DwC:measurementValueID
 
-*For `measurementTypeID`, `measurementUnitID`, and `measurementValueID` you must use controlled vocabulary terms. We know choosing the correct vocabulary term can be challenging, so we have provided some guidance on how to [select the correct vocabulary](vocabulary.html). It is strongly recommended to ensure these fields are filled as correctly as possible. Missing or incorrect terms will be documented in the [measurementOrFact reports](https://r.obis.org/mof/).
+> *For `measurementTypeID`, `measurementUnitID`, and `measurementValueID` you must use controlled vocabulary terms. We know choosing the correct vocabulary term can be challenging, so we have provided some guidance on how to [select the correct vocabulary](vocabulary.html) and are continuously working to improve guidelines. It is strongly recommended to ensure these fields are filled as correctly as possible. Missing or incorrect terms will be documented in the [measurementOrFact reports](https://r.obis.org/mof/).
 
 #### How to structure eMoF
 

formatting.md

@@ -4,7 +4,7 @@
 
 Formatting data can be challenging. This section of the manual deals with how to format data for OBIS, beginning with an overview of dataset structure.
 
-Deciding on your dataset structure is one of the first steps towards getting your data ready for publishing. At this step, there are different non arbitrary you need to do with your data, but it is important to determine which structure best suits your dataset before proceeding. Then, once you have decided on the dataset structure, you can continue formatting your data.
+Determining how your dataset will be structured is one of the first steps towards getting your data ready for publishing. At this first step it is important to determine which structure best suits your dataset before proceeding because it will determine which Darwin Core fields will need to be included in your data. Once you have decided on the dataset structure, you can continue formatting the dataset.
 
 We have created the following flow chart for an overview on how to determine what structure best suits your data.
 

name_matching.md

@@ -111,7 +111,7 @@ In cases where no match can be found, WoRMS will indicate none. For these cases
 
 If a scientific name does not appear in any register, you should contact the original data provider, where possible, to confirm taxonomic spelling, authority, and obtain any original description documents, then attempt to match again. If even after this there are no matches, please contact the WoRMS data management team at <[email protected]> to see if the taxon should be added to the WoRMS register.
 
-#### Step 2: Match with other registers
+#### Step 2: Check name in other registers
 
 If you do not find a match with WoRMS, you should next check other registers. The [LifeWatch taxon match](http://www.lifewatch.be/data-services/) compares your taxon list to multiple taxonomic standards. Matching with multiple registers gives an indication of the correct spelling of a name, regardless of its environment. If a name would not appear in any of the registers, this could indicate a mistake in the scientific name and the name should go back to the provider for additional checking/verification.
 
@@ -146,4 +146,4 @@ See the table below for a summary of the different tools available.
 |-----------|---------------------|-----------------|
 |WoRMS taxon match | Accessible online, Does not require coding knowledge | Requires rematch information back to your data |
 |obistools::match_taxa | Produces same output as WoRMS taxon match, Already in R so easier to merge back with data | Requires knowledge of R or python |
-|worrms::wm_records_taxamatch | Outputs all WoRMS matching information | Outputs a tibble for each taxa name specified, Requires knowledge of R or python |
+|worrms::wm_records_taxamatch | Outputs all WoRMS matching information | Outputs a tibble for each taxa name specified; Requires knowledge of R or python |