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Research Data Management@Koç University

This guide outlines the process of research data management, how to develop and share data management plans and FAIR data principles. Planning for the effective creation, management and sharing of your data enables you to get the most out of your research

What is research data?

Research data is the evidence that underpins answers to research questions, and which is necessary to validate research findings. Data can come in various forms and types, characteristic to specific disciplines of research. Sharing and using research data can increase the impact, validity, reproducibility, efficiency, and transparency of scientific research.

Open data is defined as free of charge and freely available, reusable and distributable data that is not subject to any copyright, patent or other control mechanism.

 

At a broad level, data are items of recorded information considered collectively for reference or analysis.

Data can occur in a variety of formats that include, but are not limited to,

  • notebooks
  • survey responses
  • software and code
  • measurements from laboratory or field equipment (such as IR spectra or hygrothermograph charts)
  • images (such as photographs, films, scans, or autoradiograms)
  • audio recordings
  • physical samples 

What is reseach data management?

Research data management (or RDM) is a term that describes the organization, storage, preservation, and sharing of data collected and used in a research project. It involves the everyday management of research data during the lifetime of a research project (for example, using consistent file naming conventions). It also involves decisions about how data will be preserved and shared after the project is completed (for example, depositing the data in a repository for long-term archiving and access).

There are a host of reasons why research data management is important:

  • Data, like journal articles and books, is a scholarly product.
  • Data (especially digital data) is fragile and easily lost.
  • There are growing research data requirements imposed by funders and publishers.
  • Research data management saves time and resources in the long run.
  • Good management helps to prevent errors and increases the quality of your analyses.
  • Well-managed and accessible data allows others to validate and replicate findings.
  • Research data management facilitates sharing of research data and, when shared, data can lead to valuable discoveries by others outside of the original research team.