1. PhD-course Research Data Management (RDM) Expert Centre Research Data

2. INTRODUCTION Welcome Structure of the course: focus on data life cycle Last week: - Creating data, processing data In between:- Writing your data management plan Today: - Discuss your data management plan - Preserving data, giving access to data, reusing data Afterwards: - Finish your data management plan - Send it in for feedback

3. PLENARY DISCUSSION 1. Research project Planning research: 2. Organisational context 3. Data management roles 4. Costs What were issues and bottlenecks in writing your data management plan?

4. PLENARY DISCUSSION Collecting data: 5. Use of existing data 6. Collection process 7. Informed consent 8. Ethics committee 9. Privacy 10. Security What were issues and bottlenecks in writing your data management plan?

5. PLENARY DISCUSSION What were issues and bottlenecks in writing your data management plan? Processing & analysing data: 11. Overview of research data 12. Storing during research 13. Privacy 14. Structuring your data 15. Sharing during research 16. Documentation

6. PLENARY DISCUSSION What were issues and bottlenecks in writing your data management plan? Preserving and giving access: 17. Long-term storage 18. Metadata and documentation 19. Giving access to data

7. PRESERVING DATA

8. PRESERVING DATA: POLICY Radboud University policy states: “ data are stored at the latest at the time of publication of the research”. Sometimes it is not allowed to store your data (publicly), e.g. due to agreements with funder or research subjects However, due to integrity reasons, the deletion of data is strongly discouraged.

9. DISCUSSION: OWNERSHIP OF / CUSTODIANSHIP OVER DATA Plenary discussion of the following questions: When you finish your PhD and leave Radboud University, who decides what happens with your data? Radboud University? The funder? You? Can you take your data with you when you leave Radboud University? Can you publish articles on your data when you are no longer working for Radboud University? Time: 10 min. In the near future: see our website for more information about ownership of / custodianship over datawebsite

10. PRESERVING DATA: ARCHIVES When you choose long-term storage, there are several trusted options. National facilities: DANS: alpha, gamma and life sciences.DANS 3TU.Datacentrum: technical and exact sciences.3TU.Datacentrum Local facilities: Donders initiative (under construction) Radboud initiative: RIS interfaceRIS interface Guidelines / initiatives from research institutes International: Re3data.org: overview of more than 1.000 data archives. You can select archives by discipline, type of data or countryRe3data.org

11. PRESERVING DATA: ARCHIVES Quality is an issue  look for trusted repositories Things to take into account when choosing an archive: Guarantees data archiving for the long term; Data is stored in accordance with applicable Dutch law; Uses clear copyright procedures: the depositor holds the right to the data; Archive is certified with the Data Seal of Approval;Data Seal of Approval Makes use of preferred standard formats that guarantee that data will be readable in the long term; Uses persistent identifiers, such as DOI’s that ensure the findability of the data; Allows for various levels of access to archived data; Provides statistics on use.

12. PRESERVING DATA: LONG-TERM STORAGE Which data should be stored? Two possibilities: From the perspective of reuse: Final (definitive) versions of data used for analysis, possibly also raw and processed data. Documentation/codebooks necessary for understanding the data. Read me.txt for understanding the structure and content of the deposit. From the perspective of scientific integrity: Approval ethical committee Informed consent & information sheet Raw, processed and analyzed data Documentation/codebooks Read me.txt Data Management Plan Audit trails and query trails

13. PRESERVING DATA: PREFERRED FORMATS How should your data be stored? 1. Formats: Choose a format which has a long-term guarantee. Some repositories (f.i. DANS) know preferred formats: they guarantee availability of the data in these formats in the far future.DANS

14. PRESERVING DATA: PRIVACY Privacy: * If possible: Interview data and other privacy sensitive data must be anonymised. * Removal of names is not sufficient for anonymisation in most cases. * Several legal documents to guide you. * Codelist and study data should be stored seperately Relevant are: * Dutch Data Protection ActDutch Data Protection Act * Code of conduct VSNUCode of conduct VSNU * Commissie Mensgebonden onderzoek (Committee on Research involving Human Subjects)Commissie Mensgebonden onderzoek * Ethics committees (Ethische toetsingscommissies) on faculty level

15. PRESERVING DATA: FOLDER STRUCTURE When you have multiple files and / or folders, design a structure which is easy to use, also in the future. Example: Longitudinal study on family relationships and personality: Questionnaires for four members in each family Three measurement waves Several content themes, for example problem behaviour, family relations, identity

16. PRESERVING DATA: ACCESSIBILITY How to make your data accessible? Use good metadata Who collected the data, where, when, what kind of data, subjects etc. General standards (Dublin Core) and standards for disciplines. Especially important when the data itself is not searchable. Use a persistent identifier In most data archives a persistent identifier (DOI or other) is assigned to your stored data You can use this identifier in your publications to refer to your dataset

17. PRESERVING DATA: USE When you start your project, think about how you are going to manage your research data. Write a data management plan. It will save you a lot of time in the end. Preserving your data in the right way will make sure that you can always use your data whenever you want. Furthermore, also other researchers can easily use your data!

18. GIVING ACCESS TO DATA

19. GIVING ACCESS TO DATA: WHY Why share data with other researchers? Promote innovation and potential new data uses. Build on each others work, which is (in most cases) funded by public money. No duplication of data creation. Prevent fraud and improve research integrity. Increase visibility of research and therefore citations. Make possible new collaborations and (possibly) publications. Encourage scientific debate. Meet requirements of funders, journals and universities. Preparing data for sharing makes it also suitable for long term preservation.

20. GIVING ACCESS TO DATA Questions to consider when you want to share data: Are there ethical and legal reasons not to share my data? Must all data be shared? Where is my data safe? Is my data in an easy to use format? Will my data be accessible in the long term? Do I have sufficient documentation and metadata?

21. GIVING ACCESS TO DATA: TERMS You can set the terms of use of your data: Levels of access: -Open (with or without registration) -Restricted (request to depositor when someone wants to use the data) -Dark archive Citations Co-authorship Etc.

22. RE-USING DATA

23. RE-USING DATA: CITATION In citing data mention: -author -title -year of publication -publisher (for data this is often the archive where it is housed) -edition or version -access information (a URL or other persistent identifier). Bibliographical styles often have templates for citing datasets (f.i. APA 6 th ) And you can always reuse your own data!

24. WRITING YOUR DATA MANAGEMENT PLAN Continue writing / adjusting your data management plan (don’t forget versioning) Do you have questions? Do you want our feedback on your data management plan? Email us at researchdata@ubn.ru.nl!researchdata@ubn.ru.nl Discuss your data management plan with your supervisor / (co-)promoter Evaluation form & feedback Thank you for your attention

25. SUPPORT Expert Centre Research Data www.ru.nl/researchdata researchdata@ubn.ru.nl 024-3612863 Clinical Research Centre Nijmegen (for questions concerning clinical data management) Radboudumc CRNC intranet website crcn@crcn.umcn.nl 024-3668333