This repository contains the dataset from the FAIRqual workshop conducted at the International Transdisciplinary Conference (ITD24) in Utrecht, Netherlands (November 4-8, 2024). The workshop aimed to gather experiences and perspectives on sharing qualitative data in transdisciplinary research contexts.
FAIRqual is a collaborative project between data stewards and qualitative researchers that aims to develop both technological implementations and conceptual procedures for sharing qualitative data based on the FAIR principles (Findable, Accessible, Interoperable, Reusable) in transdisciplinary research. This project is supported by the Open Research Data Program of the ETH Board.
Project website: https://fairqual.github.io/website/about
The workshop brought together 24 researchers interested in transdisciplinary research to:
- Share past experiences with open qualitative data
- Brainstorm challenges and opportunities for data sharing
- Imagine future scenarios for FAIR qualitative data practices
- Identify key concerns about sensitive data handling
Participants worked in four groups using flipcharts and post-it notes to document their discussions. Key themes that emerged included:
- Handling of sensitive data and maintaining confidentiality
- Risks of data misuse and decontextualization
- Concerns about AI applications and data extraction
- Need for appropriate data repositories for qualitative data
- Cost-benefit considerations of preparing data for sharing
The workshop summary is available both as an online article and as a downloadable DOCX file. The datasets (codebook and flipcharts) can be downloaded as CSV or XLSX files from the tables below. For direct programmatic access to the data in R, install the data package following the guidance in the Installation section.
Workshop Summary Document:
| Document | Article | Download |
|---|---|---|
| summary_fairqual_workshop_itd24 | Read Article | Download DOCX |
Datasets:
| Dataset | CSV | XLSX | Pictures |
|---|---|---|---|
| codebook_qualitative | Download CSV | Download XLSX | NA |
| flipcharts1 | Download CSV | Download XLSX | View Pictures |
| flipcharts2 | Download CSV | Download XLSX | View Pictures |
If you prefer to work with the data outside of R, you can download individual datasets as CSV files:
- Right-click on the “Download CSV” link for the dataset you want
- Select “Save Link As” (Chrome, Edge, Firefox) or “Download Linked File” (Safari)
- Choose where you’d like to save the file on your computer
Detailed variable descriptions for each dataset are available in the reference documentation on this website.
You can install the development version of dataitd24 from GitHub with:
# install.packages("devtools")
devtools::install_github("fairqual/dataitd24")## Run the following code in console if you don't have the packages
## install.packages(c("dplyr", "knitr", "readr", "stringr", "gt", "kableExtra", "tibble"))
library(dplyr)
library(knitr)
library(readr)
library(stringr)
library(gt)
library(kableExtra)
library(tibble)The package provides access to three main datasets from the FAIRqual workshop:
library(dataitd24)This document summarizes the workshop. It is available both as a
downloadable DOCX file and as an article on this website. The file
summary_fairqual_workshop_itd24 describes the codes / subcategories /
categories that were identified in a qualitative content analysis
performed on all workshop materials (post-it notes from flipcharts; see
flipcharts1 and flipcharts2). The aim of this document is to provide
context for the flipcharts and post-it notes created during the
workshop, as well as summarizing the discussions that took place. For a
tabular overview of the codes / subcategories / categories see the
dataset codebook_qualitative.
The dataset codebook_qualitative contains the codes / subcategories /
categories that were identified in a qualitative content analysis
performed on all workshop materials (post-it notes from flipcharts; see
flipcharts1 and flipcharts2). The analysis categorized discussions
about sharing qualitative data in transdisciplinary research into
hierarchical themes. It has 50 observations and 4 variables.
codebook_qualitative |>
head(3) |>
gt::gt() |>
gt::as_raw_html()| category | subcategory | code | frequency |
|---|---|---|---|
| data types | interview types | interview | 18 |
| data types | interview types | focus groups | 4 |
| data types | interview types | oral (hi)stories | 3 |
For an overview of the variable names, see the following table.
|
variable_name |
variable_type |
description |
|---|---|---|
|
category |
character |
High-level thematic category from qualitative content analysis |
|
subcategory |
character |
More specific topic within the main category |
|
code |
character |
Detailed code assigned to workshop content |
|
frequency |
numeric |
Number of times this code appeared in the workshop data |
The dataset flipcharts1 contains digitized post-it notes from the
first part of the workshop where participants shared lived and imagined
experiences with qualitative data sharing. It has 217 observations and 6
variables.
flipcharts1 |>
head(3) |>
gt::gt() |>
gt::as_raw_html()| group | question_no | individual_thought_postits | type | comment | umbrella_term_postits |
|---|---|---|---|---|---|
| a | 1 | conent analysis | lived | NA | NA |
| a | 1 | storytelling diagrams? (draw and tell) | lived | NA | NA |
| a | 1 | interview transcripts | lived | NA | NA |
|
variable_name |
variable_type |
description |
|---|---|---|
|
group |
character |
Workshop group identifier (a, b, c, or d) |
|
question_no |
numeric |
Question number discussed (1-4) |
|
individual_thought_postits |
character |
Content of individual post-it notes from participants |
|
type |
character |
Type of experience shared (lived, imagined, or NA) |
|
comment |
character |
Additional comments or notes about the post-it |
|
umbrella_term_postits |
character |
Overarching theme or grouping assigned to related post-its |
The dataset flipcharts2 contains data from the second part of the
workshop where groups were combined to identify key challenges in
sharing qualitative data and propose approaches to address them. It has
9 observations and 3 variables.
flipcharts2 |>
head(3) |>
gt::gt() |>
gt::as_raw_html()| group | challenge | approach |
|---|---|---|
| bd | annonymisation does not work | loss of context (as main reason); contact original research team; learning opportunities |
| bd | misue & decontextualisation of data | ethical concerns; get ethic approval from country where research is done (prior to data collection); ethics committee / ethics consent |
| bd | != ethics considerations to be aligned | what is data; do not publish raw data (e.g. summaries); metadata on data collection process |
|
variable_name |
variable_type |
description |
|---|---|---|
|
group |
character |
Combined workshop groups (ac or bd) |
|
challenge |
character |
Data sharing challenge identified by the group |
|
approach |
character |
Proposed approach or solution to address the challenge |
Workshop participants were informed about data collection and provided consent for sharing. Sensitive content could be marked with special stickers, and participants had the option to opt out of photography using conference-provided orange wristbands.
Data are available as CC-BY.
Please cite this package using:
citation("dataitd24")
#> To cite package 'dataitd24' in publications use:
#>
#> Mohr F, Chapman M, Vienni-Baptista B, Pohl C, Schöbitz L, Tilley E,
#> Albuquerque M, Angarita E, Cheas K, Coetzee W, Forsberg Mussault V,
#> Geiges T, Helgason V, Keryan T, Mennes J, Moser S, Rittmeier A,
#> Siegrist E, Silvonen T, van Vliet O, Vegt K, Wagner-Ahlfs C, Walther
#> P (2026). "dataitd24: FAIRqual Workshop Data from ITD24."
#> doi:10.5281/zenodo.18493525
#> <https://doi.org/10.5281/zenodo.18493525>.
#> <https://github.com/fairqual/dataitd24>.
#>
#> A BibTeX entry for LaTeX users is
#>
#> @Misc{mohr_etall:2026,
#> title = {dataitd24: FAIRqual Workshop Data from ITD24},
#> author = {Franziska Mohr and Mollie Chapman and Bianca Vienni-Baptista and Christian Pohl and Lars Schöbitz and Elizabeth Tilley and Marconi Albuquerque and Erika Angarita and Kirsi Cheas and Wilma Coetzee and Violaine Vera Charlotte {Forsberg Mussault} and Tim Geiges and Vignir Freyr Helgason and Tigran Keryan and Julie Mennes and Stephanie Moser and Aaron Rittmeier and Elena Siegrist and Taru Silvonen and Oscar {van Vliet} and Kirsten Vegt and Christian Wagner-Ahlfs and Pascal Walther},
#> year = {2026},
#> doi = {10.5281/zenodo.18493525},
#> url = {https://github.com/fairqual/dataitd24},
#> abstract = {Contains digitized flipchart data and qualitative analysis results from the FAIRqual workshop at the International Transdisciplinary Conference (ITD24) in Utrecht, November 2024. The workshop gathered experiences and perspectives on sharing qualitative data in transdisciplinary research.},
#> version = {1.0.0},
#> }- Dr. Franziska Mohr (USYS Transdisciplinarity Lab, ETH Zurich)
- Lars Schöbitz (Global Health Engineering, ETH Zurich)
- Dr. Mollie Chapman (USYS Transdisciplinarity Lab, ETH Zurich)
- PD Dr. Bianca Vienni-Baptista (USYS Transdisciplinarity Lab, ETH Zurich)
- Prof. Dr. Elizabeth Tilley (Global Health Engineering, ETH Zurich)
We thank all workshop participants for their valuable contributions and insights. This work is supported by the Open Research Data Program of the ETH Board.