Digitized post-it notes from the first part of the FAIRqual workshop where participants shared lived and imagined experiences with qualitative data sharing. Four groups (a, b, c, d) responded to four questions about past experiences and future scenarios.
Format
A tibble with 217 rows and 6 variables:
- group
Workshop group identifier. Character variable with values "a", "b", "c", or "d".
- question_no
Question number discussed. Character variable with values "1", "2", "3", "4", or NA, where:
1 = What types of qualitative data have you collected?
2 = Have you shared qualitative data? If yes, how?
3 = What challenges did you face when sharing?
4 = What would enable better data sharing?
NA = Post-its from round 2 where original question placement was unclear
- individual_thought_postits
Content of individual post-it notes written by participants. Character variable containing the actual text from each post-it.
- type
Type of experience shared. Character variable with values "lived" (actual experience), "imagined" (hypothetical scenario), or NA.
- comment
Additional comments or notes about the post-it. Character variable, often NA.
- umbrella_term_postits
Overarching theme or grouping assigned to related post-its during the workshop synthesis. Character variable, often NA.
Source
FAIRqual Workshop at the International Transdisciplinary Conference (ITD24), Utrecht, Netherlands, November 4-8, 2024.
See also
codebook_qualitative for the analyzed results
flipcharts2 for the workshop part 2 data
Examples
# Load the data
data(flipcharts1)
# View structure
str(flipcharts1)
#> tibble [217 × 6] (S3: tbl_df/tbl/data.frame)
#> $ group : chr [1:217] "a" "a" "a" "a" ...
#> $ question_no : chr [1:217] "1" "1" "1" "1" ...
#> $ individual_thought_postits: chr [1:217] "conent analysis" "storytelling diagrams? (draw and tell)" "interview transcripts" "workshop (post-its)" ...
#> $ type : chr [1:217] "lived" "lived" "lived" "lived" ...
#> $ comment : chr [1:217] NA NA NA NA ...
#> $ umbrella_term_postits : chr [1:217] NA NA NA NA ...
# Count post-its by group and question
library(dplyr)
library(tidyr)
flipcharts1 %>%
count(group, question_no) %>%
pivot_wider(names_from = question_no, values_from = n)
#> # A tibble: 4 × 6
#> group `1` `2` `3` `4` na
#> <chr> <int> <int> <int> <int> <int>
#> 1 a 22 12 15 10 2
#> 2 b 21 21 7 5 NA
#> 3 c 21 13 11 8 3
#> 4 d 18 12 13 3 NA
# View lived vs imagined experiences
flipcharts1 %>%
filter(!is.na(type)) %>%
count(type, question_no)
#> # A tibble: 9 × 3
#> type question_no n
#> <chr> <chr> <int>
#> 1 imagined 1 14
#> 2 imagined 2 24
#> 3 imagined 3 20
#> 4 imagined 4 20
#> 5 lived 1 68
#> 6 lived 2 34
#> 7 lived 3 26
#> 8 lived 4 6
#> 9 na na 5