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Merge pull request #5 from fhdsl/tenseCheck
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sync verb tense
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@kweav
kweav authored Jun 5, 2024
2 parents 0901484 + 94d33b3 commit 2ef9212
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56 changes: 28 additions & 28 deletions pages/Awareness.Rmd
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Original file line number Diff line number Diff line change
Expand Up @@ -31,46 +31,46 @@ demoPlotRaw <- resultsTidy %>%
stylize_bar(demoPlotRaw)
```

## Awareness

```{r, message=FALSE, echo = FALSE}
demoPlot <- resultsTidy %>%
demoPlot <- resultsTidy %>%
group_by(UserType, AnVILDemoAwareness) %>%
summarize(count = n()) %>%
ggplot(aes(y = AnVILDemoAwareness,
x = count,
fill = UserType)) +
ggplot(aes(y = AnVILDemoAwareness,
x = count,
fill = UserType)) +
geom_bar(stat = "identity") +
ggtitle("Have you attended a monthly AnVIL Demo?")
stylize_bar(demoPlot) +
ylab("Awareness")
```

## Takeaway

Most respondents have not attended an AnVIL Demo. To investigate whether this was an awareness issue, we aggregated all responses except `No, didn't know of`. We see that the majority of respondents are aware of AnVIL Demos. These responses are just distributed among different ways of utilizing the demos. Further, there's awareness among both current and potential AnVIL users.
Most respondents have not attended an AnVIL Demo. To investigate whether this is an awareness issue, we aggregated all responses except `No, didn't know of`. We see that the majority of respondents are aware of AnVIL Demos. These responses are just distributed among different ways of utilizing the demos. Further, there's awareness among both current and potential AnVIL users.

<br/>

# AnVIL Support Forum

```{r, message=FALSE, echo=FALSE}
forumdf <- resultsTidy %>%
mutate(AnVILSupportForum = str_replace(AnVILSupportForum,
pattern = "No, ",
replacement= "No ")) %>%
separate(AnVILSupportForum,
c("forumInteractionA", "forumInteractionB", "forumInteractionC"),
sep = ", ",
fill = "right") %>%
forumdf <- resultsTidy %>%
mutate(AnVILSupportForum = str_replace(AnVILSupportForum,
pattern = "No, ",
replacement= "No ")) %>%
separate(AnVILSupportForum,
c("forumInteractionA", "forumInteractionB", "forumInteractionC"),
sep = ", ",
fill = "right") %>%
pivot_longer(starts_with("forumInteraction"), values_to = "forumInteractionDescription") %>%
group_by(UserType, CurrentUsageDescription, forumInteractionDescription) %>%
summarize(count = n()) %>%
drop_na() %>%
mutate(forumInteractionDescription =
group_by(UserType, CurrentUsageDescription, forumInteractionDescription) %>%
summarize(count = n()) %>%
drop_na() %>%
mutate(forumInteractionDescription =
factor(forumInteractionDescription, levels = c("Posted in", "Answered someone's post", "Read through others' posts", "No but aware of", "No didn't know of")),
forumAwareness = factor(
case_when(
Expand All @@ -94,10 +94,10 @@ forumdf <- resultsTidy %>%
## Raw Responses

```{r, message=FALSE, echo=FALSE}
forumPlotRaw <- ggplot(forumdf,
aes(y = reorder(forumInteractionDescription, count),
x = count,
fill = UserType)) +
forumPlotRaw <- ggplot(forumdf,
aes(y = reorder(forumInteractionDescription, count),
x = count,
fill = UserType)) +
geom_bar(stat = "identity") +
ggtitle("Have you ever read or posted in our AnVIL Support Forum?")
Expand All @@ -107,10 +107,10 @@ stylize_bar(forumPlotRaw)
## Awareness

```{r, message=FALSE, echo=FALSE}
forumPlot <- ggplot(forumdf,
aes(y = forumAwareness,
x = count,
fill = UserType)) +
forumPlot <- ggplot(forumdf,
aes(y = forumAwareness,
x = count,
fill = UserType)) +
geom_bar(stat = "identity") +
ggtitle("Have you ever read or posted in our AnVIL Support Forum?")
Expand All @@ -120,4 +120,4 @@ stylize_bar(forumPlot) +

## Takeaway

Most respondents have not used the AnVIL support forum. We aggregated these responses to examine awareness. We observe that there is awareness of the support forum across potential and current users. While utilization in some form is reported by about 20% of respondents, reading through others' posts is the most common way of utilizing the support forum within this sample.
Most respondents have not used the AnVIL support forum. We aggregated these responses to examine awareness. We observe that there is awareness of the support forum across potential and current users. While utilization in some form is reported by about 20% of respondents, reading through others' posts is the most common way of utilizing the support forum within this sample.
57 changes: 28 additions & 29 deletions pages/CurrentUserQs.Rmd
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Expand Up @@ -22,20 +22,20 @@ source(here("resources/scripts/shared_functions.R"))
# Length of Use of the AnVIL

```{r, message = FALSE, echo = FALSE}
timeUsePlot <- resultsTidy %>%
timeUsePlot <- resultsTidy %>%
group_by(LengthOfUse) %>%
summarize(count = n()) %>%
summarize(count = n()) %>%
drop_na() %>%
ggplot(aes(x = LengthOfUse,
y = count,
fill = "#25445A")) +
ggplot(aes(x = LengthOfUse,
y = count,
fill = "#25445A")) +
geom_bar(stat = "identity") +
geom_text(aes(label = count, group = LengthOfUse),
vjust = -1, size=2) +
ggtitle("How long have you been using the AnVIL?")
stylize_bar(timeUsePlot, usertypeColor = FALSE, singleColor = TRUE) +
xlab("Years of Use") +
xlab("Years of Use") +
ylab("Count") +
theme(legend.position = "none")
```
Expand All @@ -49,46 +49,46 @@ We observe a fairly even sampling of the current users with regards to the numbe
# Foreseeable Computational Needs

```{r, message=FALSE, echo=FALSE, warning=FALSE}
compNeedsPlot <- resultsTidy %>%
separate(NeededResources,
c("whichResourceA", "whichResourceB", "whichResourceC", "whichResourceD"),
sep = ", ", fill = "right") %>%
pivot_longer(starts_with("whichResource"), values_to = "ResourceDescription") %>%
group_by(ResourceDescription) %>%
summarize(count = n()) %>%
compNeedsPlot <- resultsTidy %>%
separate(NeededResources,
c("whichResourceA", "whichResourceB", "whichResourceC", "whichResourceD"),
sep = ", ", fill = "right") %>%
pivot_longer(starts_with("whichResource"), values_to = "ResourceDescription") %>%
group_by(ResourceDescription) %>%
summarize(count = n()) %>%
drop_na() %>%
ggplot(aes(x = count,
y = reorder(ResourceDescription, count),
fill = "#25445A")) +
ggplot(aes(x = count,
y = reorder(ResourceDescription, count),
fill = "#25445A")) +
geom_text(aes(label = count, group = ResourceDescription),
hjust = -1, size=2) +
geom_bar(stat = "identity") +
ggtitle("What computational and storage resources do you foresee\nneeding in the next 12 months?")
stylize_bar(compNeedsPlot, usertypeColor = FALSE, singleColor = TRUE) +
stylize_bar(compNeedsPlot, usertypeColor = FALSE, singleColor = TRUE) +
theme(legend.position = "none")
```

## Takeaway

Of the `r nrow(resultsTidy %>% filter(UserType == "Current User"))` current users, all `r 50 - sum(is.na(resultsTidy$NeededResources))` provided an answer to this question. The most common response here was needing large amounts of storage.
Of the `r nrow(resultsTidy %>% filter(UserType == "Current User"))` current users, all `r 50 - sum(is.na(resultsTidy$NeededResources))` provided an answer to this question. The most common response here is needing large amounts of storage.

## Potential Follow-ups

- What do we see in other responses from the "don't know" responses?

<br>

# Recommendation Likelihood
# Recommendation Likelihood

```{r, message = FALSE, echo = FALSE}
recLikePlot <- resultsTidy %>%
group_by(RecommendationLikelihood) %>%
recLikePlot <- resultsTidy %>%
group_by(RecommendationLikelihood) %>%
summarize(count = n()) %>%
drop_na() %>% #not asked to everyone
ggplot(aes(x = RecommendationLikelihood,
y = count,
fill = as.factor(RecommendationLikelihood))) +
ggplot(aes(x = RecommendationLikelihood,
y = count,
fill = as.factor(RecommendationLikelihood))) +
geom_bar(stat="identity") +
ggtitle("How likely are you to recommend the AnVIL to a colleague?") +
coord_cartesian(clip = "off") +
Expand All @@ -107,10 +107,9 @@ recLikePlot <- resultsTidy %>%

## Takeaway

There's a fairly bimodal distribution here with users either extremely likely or only moderately likely to recommend the AnVIL.
There's a fairly bimodal distribution here with users either extremely likely or only moderately likely to recommend the AnVIL.

## Potential Follow-ups

- What do we see in other responses from those who are extremely likely to recommend the AnVIL to a colleague? e.g., Are they part of a consortium?
- What do we see in other responses from those who are only moderately or not at all likely to recommend the AnVIL?

- What do we see in other responses from those who are extremely likely to recommend the AnVIL to a colleague? e.g., Are they part of a consortium?
- What do we see in other responses from those who are only moderately or not at all likely to recommend the AnVIL?
23 changes: 11 additions & 12 deletions pages/Demographics.Rmd
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Expand Up @@ -57,8 +57,8 @@ resultsTidy %>%
pivot_longer(starts_with("whichWork"), values_to = "whichWorkDescription") %>%
select(Timestamp, UserType, whichWorkDescription) %>%
mutate(whichWorkDescription =
recode(whichWorkDescription,
"computational education" = "Computational education",
recode(whichWorkDescription,
"computational education" = "Computational education",
"Program administration," = "Program administration"),
whichWorkDescription = factor(whichWorkDescription),
Timestamp = factor(Timestamp)
Expand All @@ -81,7 +81,7 @@ resultsTidy %>%

## Takeaway

Only a few responses showed project management, leadership, or administration as their only kind of work. This increases our confidence that this won't confound later questions asking about usage of datasets or tools.
Only a few responses report project management, leadership, or administration as their only kind of work. This increases our confidence that this won't confound later questions asking about usage of datasets or tools.

## Potential Follow-ups

Expand All @@ -93,8 +93,8 @@ Only a few responses showed project management, leadership, or administration as

```{r, message=FALSE, echo = FALSE}
instPlot <- resultsTidy %>%
mutate(FurtherSimplifiedInstitutionalType =
factor(FurtherSimplifiedInstitutionalType,
mutate(FurtherSimplifiedInstitutionalType =
factor(FurtherSimplifiedInstitutionalType,
levels = c("Industry & Other", "Education Focused", "Research Intensive"))) %>%
group_by(UserType, FurtherSimplifiedInstitutionalType) %>%
summarize(InstitutionalCount = n()) %>%
Expand All @@ -104,7 +104,7 @@ instPlot <- resultsTidy %>%
fill = UserType
)) +
geom_bar(position = "stack", stat = "identity") +
geom_text(aes(label = after_stat(x),
geom_text(aes(label = after_stat(x),
group = FurtherSimplifiedInstitutionalType),
stat = 'summary', fun = sum, hjust = -1, size=2
) +
Expand All @@ -130,13 +130,13 @@ Most of the individuals using the AnVIL report being affiliated with a research
```{r, message = FALSE, echo = FALSE}
instPlotB <- resultsTidy %>%
select(c(UserType, InstitutionalType)) %>%
group_by(UserType, InstitutionalType) %>%
group_by(UserType, InstitutionalType) %>%
summarize(InstitutionalCount = n()) %>%
ggplot(aes(
y = reorder(InstitutionalType, InstitutionalCount, sum),
x = InstitutionalCount,
fill = UserType
)) +
)) +
geom_bar(position = "stack", stat = "identity") +
geom_text(
aes(label = after_stat(x), group = InstitutionalType),
Expand Down Expand Up @@ -167,13 +167,12 @@ consortiaTable <- resultsTidy %>%
```


Of `r nrow(resultsTidy)` responses, `r sum(!is.na(resultsTidy$ConsortiaAffiliations))` provided an affiliation, with `r nrow(consortiaTable)` unique affiliations provided across those responses (respondents could select more than one consortium). The following table shows the most represented consortia.
Of `r nrow(resultsTidy)` responses, `r sum(!is.na(resultsTidy$ConsortiaAffiliations))` provide an affiliation, with `r nrow(consortiaTable)` unique affiliations represented across those responses (respondents could select more than one consortium). The following table shows the most represented consortia.

```{r, message = FALSE, echo = FALSE}
consortia_df <-
consortiaTable[which(consortiaTable$count >1),] %>%
consortia_df <-
consortiaTable[which(consortiaTable$count >1),] %>%
rename(`consortium` = whichConsortiumName)
kableExtra::kable(consortia_df, table.attr = "style='width:20%;'")
```

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