# README: Quantitative Assessment of Research Data Management Practices - 2025

## Dataset Overview

This dataset contains aggregated and anonymized survey results from the **2025 Quantitative Assessment of Research Data Management (RDM) Practices** survey. The survey was conducted across several Swiss higher education institutions (HEIs) with the goal of collecting insights into how researchers manage their research data and code throughout the lifecycle of their projects.

The dataset includes key information about:

- Storage and Organization
- Data sharing and collaboration platforms
- Documentation and metadata usage
- Formats and software
- Governance and compliance
- Publication and long-term archiving
- Support and training

The survey included some conditional questions. For example, participants’ affiliation to an institution triggered questions specific to their department and relevant RDM-related services. Apart from these, the majority of questions were the same across all institutions. Conditional branching was also used for in-depth exploration of certain RDM practices, such as metadata usage. In these cases, a shorter version of the questionnaire was provided for most respondents, while additional, more specific questions were presented to those with relevant experience.

This dataset is intended to inform the development of academic RDM services for researchers at the involved institutions.

## File Inventory

- **CSV and XLSX files**: Aggregated, anonymized data from the survey.
- **PDF files**: Graphical representations of the survey results, automatically generated by the SurveyHero platform in landscape and portrait modes.
- **This README file**: Provides contextual documentation for understanding and using the dataset.

## Survey questions

Below is the ordered list of questions asked in the survey:

### Intro Page

1. What is your current role?
2. What is your main institutional affiliation?
    1. What is your main EPFL affiliation?
    2. What is your main Eawag department?
    3. What is your main Empa department?
    4. What is your main WSL research unit?
    5. What PSI center do you belong?
    6. What is your main FHNW affiliation?
    7. What is your main UNIL / CHUV affiliation?
        1. Please, specify your CHUV affiliation?
    8. What is your main ETH Zurich affiliation?
    9. What is your main USI affiliation?
    10. What is your main IHEID affiliation?
    11. What is your main UniBE affiliation
    12. What is your main UniBas affiliation?
    13. What is your CERN department?
        1. Which experiment or experiment facility are you working in?

### A. Storage & Backup

1. How much data / code / software do you manage across projects?
2. On which storage solution(s) do you store your data / code / software (incl. temporary storage)?
3. Which storage solution(s) do you use to share data / code / software when collaborating with others?
4. Which storage(s) solution do you use to backup your data / code / software?
    1. How do you backup your research data / code / software?
    2. How frequently is your data / code / software backed up?

### B. Documentation & Organization

1. Which kind of documentation do you produce to accompany your data / code / software?
2. Do you use any metadata standards for your data / code / software?
    1. Which metadata standard do you use?
3. If you manage data, how do you version it?
4. If you manage code / software, how do you version it?
5. Do you follow any naming convention for files / folders / databases?
    1. What kind of naming convention do you follow?

### C. Formats & Software

1. Do you use / produce open format files or open source code / software?
2. What types of tools do you use to manage data / code / software?
    1. Which type of AI assistants / tools do you use for managing your data / code / software?
3. Which resource(s) do or did you use to write a Data Management Plan (DMP)?

### D. Governance & Compliance

1. During your research, with whom do you share your research data / code / software?
2. On average, how many hours of work do you put every week into managing data / code / software? (estimate)
3. Who or what defines the rules you follow when managing your research data / code / software?
4. Are you concerned about the physical location(s) of your data / code / software?
5. Do you know the physical location(s) where your data / code / software is stored (or shared or backed-up)?
6. Do you manage personal data?
7. Do you manage sensitive personal data?
8. Have your project(s) been submitted to any ethics committee?
    1. Which one(s)?

### E. Publication & Long-term Archiving

1. Where do you publish your data / code / software as an academic output?
    1. On which specific platform(s) do you publish your data / code / software as an academic output?
    2. Under what license(s) are your data published?
    3. Under what license(s) is your code / software published?
    4. Who encourages you to publish openly your data / code / software?
2. What are the main reasons you don't openly publish your data / code / software?
3. Where do you store your data / code / software for the long term?
    1. On which specific platform(s) do you store your data / code / software for the long term?
4. Do you have a process in place for deleting data (what, when, who, how)?

### F. Support & Training

1. For what RDM-related topics would you like help?
2. Have you already consulted any institutional RDM service / support?
3. What type of RDM service / support do you find helpful?
    1. What type of training do you find most helpful?
    2. What type of consulting do you find most helpful?
    3. What type of resources do you find most helpful?
4. Please, share with us your suggestions for improving RDM support / service / ressources
5. Please, share with us any comments concerning this survey (e.g. technical dificulties, insecurities, feedback, ...)

## Provenance and Contributors

The dataset was collected using the **SurveyHero** platform and follows ethical standards in line with GDPR and Swiss FADP regulations. No personal identifiable information was collected, and data has been aggregated to ensure respondents' privacy.

The survey was a collaborative project involving the following people from the respective institutions:

- **Ellen Knappe** (Lib4RI) - <ellen.knappe@lib4ri.ch>
- **Carmen Jambe** (UNIL) - <carmen.jambe@unil.ch>
- **Christine Krebs** (UniBE) - <christine.r.krebs@unibe.ch>
- **Ursula Loosli** (UniBE) - <ursula.loosli@unibe.ch>
- **Daniela Subotic** (DaSCH) - <daniela.subotic@dasch.swiss>
- **Igor Sarman** (USI) - <igor.sarman@usi.ch>
- **Sebastian Perrig** (FHNW) - <sebastian.perrig@fhnw.ch>
- **Guillaume Pasquier** (IHEID) - <guillaume.pasquier@graduateinstitute.ch>
- **Fabian Schmid** (ETH Zurich) - <fabian.schmid@library.ethz.ch>
- **Markus Bossert** (Unibas) - <markus.bossert@unibas.ch>
- **Merten Dahlkemper** (CERN) - <merten.dahlkemper@cern.ch>
- **Francesco Varrato** (EPFL) - <francesco.varrato@epfl.ch>
- **Christopher Tremblay** (EPFL) - <christopher.tremblay@epfl.ch>

## Methodology

The survey was conducted from September 2025 to January 2026 across CERN, DaSCH, EPFL, ETH Zurich, FHNW, IHEID, Lib4RI (for Eawag, Empa, PSI and WSL), UniBas, UniBE, UNIL, and USI

## Ethical and Legal Compliance

This dataset was collected and processed in full compliance with:

- **GDPR (General Data Protection Regulation)**: Ensures the privacy and protection of personal data.
- **Swiss FADP (Federal Act on Data Protection)**: Aligns with Swiss regulations for data privacy.

**Data Processor**: enuvo GmbH (SurveyHero platform) acted as the data processor under a signed Data Processing Agreement (DPA).

## Reuse and Licensing

This dataset is openly available under the **CC-BY 4.0** license. You are free to share, copy, distribute, and adapt the dataset, provided appropriate credit is given to the contributors.

## Contact Information

For further inquiries about this dataset, please contact:

- **Francesco Varrato** (EPFL) - <francesco.varrato@epfl.ch>
- **Christopher Tremblay** (EPFL) - <christopher.tremblay@epfl.ch>
