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Research Data Management (RDM): What is Research Data

One stop shop for all things related to Research Data and how to manage your data throughout its entire lifecycle

What is Research Data

Research data is any information collected or generated for the purpose of analysis to generate or validate scientific claims and original research findings.

They are the evidential basis that substantiates published research findings.

They may be primary data generated or collected by the researcher or secondary data collected from existing sources and processed as part of the research activity.

In addition to the 'raw' data, research data include information about the means necessary to generate data or replicate results, such as computer code, experimental methods and instruments used, and essential interpretive and contextual information, e.g. specifications of variables. Therefore, besides research data, RDM also requires you to manage the documentation needed to make those data understandable.

Types of research data

There is a huge variety of data types.

Research data can be classified in different ways, for example, based on their:

  • Content: numerical, textual, audiovisual, multimedia…
  • Format: spreadsheets, databases, images, maps, audio files, (un)structured text…
  • Mode of data collection: experimental, observational, simulation, derived/compiled from other sources
  • Digital (born-digital or digitized) or non-digital nature (e.g. paper surveys, notes…)
  • Primary (generated by the researcher for a particular research purpose or project) or secondary nature (originally created by someone else for another purpose)
  • Raw or processed nature

Research data can take many forms. It might be:

  • documents, spreadsheets
  • laboratory notebooks, field notebooks, diaries
  • clinical records of treatments and test results
  • questionnaires, transcripts, codebooks
  • survey responses
  • audiotapes, videotapes
  • photographs, films
  • test responses
  • slides, artefacts, specimens, physical samples
  • collections of digital outputs
  • data files
  • database contents (video, audio, text, images)
  • models, algorithms, scripts
  • contents of an application (input, output, logfiles for analysis software, simulation software, schemas)
  • methodologies and workflows
  • standard operating procedures and protocols
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