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Research Data Management

A comprehensive guide to the best practices for planning, collecting, working with, sharing and reusing research data

Documentation & Metadata

Data documentation and metadata play an important role in making data FAIR, which both provide critical information about data necessary to understand, interpret and effectively use the data. While data documentation is any human-readable documents that describe the data in a research project in a variety of forms, metadata is the structured machine-understandable information about the data in a controlled format.

Data documentation can be written at project or file level and in a variety of forms, e.g. data dictionaries, codebooks, vocabularies and readme-files, etc.

Project Level Documentation:

A good project level documentation describes the general parameters of the research project, which should answer the following questions:

  • For what purpose was the data created
  • What does the dataset contain?
  • How was data collected?
  • Who collected the data and when?
  • How was the data processed?
  • What possible manipulations were done to the data?
  • What were the quality assurance procedures?
  • How can the data be accessed?

File Level Documentation:

A file level documentation describes the contents of an individual data file, which could include the following elements if applicable:

  • names, labels and descriptions for variables
  • specialized formats or other abbreviations used
  • unit of measurement
  • codes of, and reasons for, missing data
  • coding or classification schemes used
  • algorithms used to transform data
  • File format and software used, etc.

Learning Resources

Knowledge clip: Data Documentation

In this video, we talk about the importance of documentation to keep data understandable and reusable. What are the different types of documentation levels and what should be documented at each of these levels?

UGent Data Stewards. (2020, December 2). Knowledge clip: Data Documentation [Video]. YouTube.

Metadata is the "data about data" which provides structured information about data in a controlled format that is readable by machine. To maximize reusability of data, you are encouraged to use a discipline-specific metadata standard to describe your research data whenever possible. You can make use of the following tools to find out the metadata standards commonly used in your field:

Learning Resources

Knowledge clip: Metadata

In this knowledge clip, we talk about metadata. Why do we need it and what different types of metadata exist? And how is metadata created and where can be stored? We also have a look at metadata in data repositories and provide a brief explanation about metadata standards.

Source: UGent Data Stewards. (2020, October 15). Knowledge clip: Metadata [Video]. YouTube.