Research Data

Research Data
Knowledge Items

What is Research Data?

At VU Amsterdam, research data refers to:

“Information that is collected, observed, generated, or reused for the purpose of underpinning academic research.”

Research data can take many forms, including text, images, audio, video, databases, software, survey results, laboratory measurements, and other materials used to support research findings.

In the context of the Research Data and Software Management Policy, research data includes not only the data itself, but also the metadata, documentation, and contextual information needed to understand, verify, and reuse it.

Examples of Research Data

Research data are produced across all academic disciplines and can take many different forms. It’s impossible to present an exhaustive list, but the overview below gives an impression of what types of data can be used in research (based on).

  • Databases and statistical datasets
  • Survey responses
  • Interview and focus group recordings in audio or video, and transcripts thereof
  • Primary sources such as images, audio recordings, videos, photographs, and text
  • Notes, e.g. field notes describing an event, behavior or object; or annotations of primary sources
  • Laboratory measurements and experimental results
  • Observational data, e.g. sensor data or participant behavior captured in field notes or recordings
  • Physical samples and sequencing data
  • Physical objects and pictures thereof, e.g. archival objects, art, landscapes
  • Quotes extracted from e.g. primary sources, interviews or focus groups
  • Thematic classification, argument maps and other ways of structuring relevant information
  • Bibliographies
  • Software, code, algorithms, and computational models
  • Research protocols, workflows, and documentation

Research data may be newly collected, generated during analysis, or reused from existing sources. It can be quantitative or qualitative, personal or non-personal, and may require specific legal, ethical, or security safeguards.

Research Data Throughout a Project

Research data often evolve throughout the research lifecycle. Different versions may exist, such as raw data, cleaned data, processed data, and final datasets used to support publications. It’s important to acknowledge all these versions and manage each of them appropriately.

During the project, research data should be stored in secure, backed-up storage environments that comply with institutional and legal requirements to ensure data integrity and appropriate access control throughout the research.

Managing these data carefully is essential for ensuring transparency, reproducibility, and long-term reuse, in line with the FAIR principles.

Reference and Further Reading

  • Organisation for Economic Co-operation and Development. (2007). OECD principles and guidelines for access to research data from public funding. OECD Publishing. https://doi.org/10.1787/9789264034020-en-fr
  • University of Geneva. (n.d.). Identify research data. Researchdata. https://www.unige.ch/researchdata/generate-collect/identifier-donnees-de-recherche
  • Vrije Universiteit Amsterdam. Research Data and Software Management (RDSM) Policy, version 3.0. https://rdm.vu.nl/public/policies-regulations/RDSM-policy-VU-EN-v3.0.pdf