Skip to Main Content
It looks like you're using Internet Explorer 11 or older. This website works best with modern browsers such as the latest versions of Chrome, Firefox, Safari, and Edge. If you continue with this browser, you may see unexpected results.

Data management for students: What are research data?

What are research data?

Research data are data that were used as the source for an analysis or data that were collected during research.

Research data can take on many forms, e.g.:

  • measurement data of experiments (e.g. from equipment)
  • illustrations
  • geographical data
  • survey results
  • models (e.g. economic or mathematical or on climate)
  • chromatograms
  • sources (data obtained through archival research or literature reviews)
  • interviews (you need informed consent from the interviewees)
  • Archival scans

Data jargon

  • Raw data = data that has not yet been analyzed, data in the state in which it was collected.
  • Processed data = data that has been subjected to analysis, from which some variables have been selected or data that has been organized in some other way.
  • Models = data that have been processed into a computer model, a calculation sample, or a formula.
  • Logbooks = raw data written down in the course of experiments, observations etc., together with notes and explanations.
  • Informed consent = one of the founding principles of research ethics. Its intent is that human participants can enter research freely (voluntarily) with full information about what it means for them to take part, and that they give consent before they enter the research.
  • Metadata = documentation and/or information on research data required to understand the content and context of the data, by adding terms that will also improve the findability of your data, e.g. author, title, type(s) of data, field of research
  • Naming convention = a standard method to name your files, e.g. name_field-of-research_sample-number_date.

You can find more data jargon here.

Why manage your data?

Research data management (RDM) is about handling research data effectively and appropriately throughout the timespan of a research project and beyond. It refers to all aspects of creating, storing, sharing and archiving data and is an essential aspect of conducting responsible research.

RDM helps you to think about your research data as well as how to keep your data safe. Above all, RDM stimulates an open and transparent academic attitude as it encourages to share data for reuse. Tilburg University believes that a responsible researcher has to store and archive his or her research data and make them retrievable and accessible. This is important to replicate results and contribute to the work of other investigators.