This webpage is work in progress and will be updated regularly.
What is data?
Research data includes any materials or information sources that were collected, processed and/or analyzed in order to support or describe research findings. Examples are text files, spreadsheets, surveys, code books, scripts, audio recordings, computational models, databases from secondary sources, specimens, etc.
Every researcher handles quite an amount of data during research. In order to keep your data understandable and useful for yourself, colleagues and third parties, proper data management is key.
Data life cycle
Data is the fundament of scientific research. Since data plays a crucial role throughout the entire research cycle, it is important to think about research data management from the very start of your research. Planning ahead saves you a lot of time.
A useful basis for sound data management are the FAIR principles. FAIR stands for Findable,Accessible,Interoperable, Reusable. Making your data FAIR enhances the value and impact of you data. Both you and others will benefit from FAIR data.
FAIR data and Open Science are connected, but are not the same. Adopting FAIR principles does not per definition mean you must share your data with the entire world. For example, ‘findable’ could refer to making data findable for you and your colleagues, for collaborating companies and universities, or for everyone.
More information about FAIR data can be found on the UBVU website.
What's in it for me as a researcher?
Adopting good RDM practices will help you to:
· Increase research efficiency
· Increase your visibility and impact as a researcher
· Promote wider dissemination and increased impact of results
· Enhance data security, by minimizing the risk of loss, theft or misuse of data
· Ensure sound processing of (privacy) sensitive data
What's in it for the world?
Good RDM practices - starting by making your data FAIR - will enhance transparency and sustainability of scientific research.
Tools for data management
The following section will be updated regularly with hands-on materials to help researchers with data management.
> Support before research:
A checklist for writing an informed consent letter.
Ethical advice or approval for research involving (data of) humans participants.
With the tool DMPonline you can easily write a data management plan and benefit from guidance and example answers. You can log in with your VU credentials.
Some quick guidance for writing a data management plan (DMP) can be found here.
> Support during research:
An decision tree of current data storage options suitable for most research at SBE. Note that new storage options (e.g. ResearchDrive) are in the pipeline!
Possibilities for extra computational power.
What data to keep and what data to bin, with help of Marie Kondo.
> Support after research:
The VU policy on RDM states that you should register your data at Pure to increase findability and transparency. This manual will help you.
How to publish open access.
Make yourself findable as a researcher by getting an ORCID identifier.
> Other tips:
VU library has an extensive LibGuide on research data management.
This road map guides you in managing your research data.
SBE also has a research data management policy.
The Consortium of European Social Sciences Data Archives (CESSDA) provides hands-on tips about data management.