Research Data Management: Research data management

Although research data management (RDM) is not yet part of (advanced) student research practice, it's an important topic with increasing relevance for academics. Due to recent examples of researchers commiting fraud by falsifying or manipulating research data this topic has attracted a lot of attention. These examples of fraud resulted in a Taskforce Scientific Integrity at the EUR, which recommended the introduction of research data management for researchers. For students it has led to stricter supervision and attention to plagiarism.

Watch the video to learn more: The what, why and how of data management planning (5:31).

The benefits of managing your data include:

• Ensuring research integrity and reproducibility.
• Increasing your research efficiency.
• Ensuring research data and records are accurate, complete, authentic and reliable.
• Enhancing data security: minimising the risk of data loss, corruption, unreadability (now or in the future).
• Enabling others to use your data.
• Complying with best practices in RDM.

In each stage of the research life cycle different requirements are identified.We distinguish the following stages:
1. Research planning
2. Research
3. Publishing
4. Archiving

The Checklist for a Data Management Plan (PDF) contains questions about data that arise during the research cycle. Answering the questions will help you develop your own data management plan.

Here's a list of things that should be properly stated and documented:

• Project plan, study design or study protocol (including a unique project identifier).

• Research question(s) / hypothesis.

• Data Management Plan: information about data & data format, metadata content and format, policies for access, sharing, and re-use, long-term storage, curation, preservation and budget.

• “Data section” (“Dataparagraaf”) describing how the researcher will anticipate reuse (open access) of research data as well as how the privacy of the people involved in the project is guarded.

• Ownership of the research data / IPR agreement.

• Agreements about the management, access, sharing, use and re-use storage and archiving of the data for all involved (also commercial partners) and all audiences.

• Description of the data items / format(s) / metadata scheme(s) / standards / identifiers / codes / labels / variable definitions from public or commercially available data.

• The data definitions and criteria used by the data provider.

• Description of researchers, readers, informants, respondents, interviewees, participants, funders and others involved in the research project.

• The submitted version of the publication.

• The reviewed and revised version of the publication.

• The response from the editor (also in case of rejection) plus the reviews.

• Your answers to the reviewers' questions.

• The final version of the publication.

• The publication-specific version of the dataset.