Research data and research data management
Research data are representations of observations, objects, or other entities used as evidence of phenomena for the purpose of research or scholarship1.
What is research data management?
As a researcher, you will already be familiar with many of the activities surrounding research data management. Research data management covers practically everything in the life cycle of research data in a research project.
Research data management comprises several steps:
- Create a data management plan that explains how data will be managed both during and after the research project.
- Store research data safely and securely throughout the research project and share it with authorized colleagues.
- During the project, it is important that the data is sorted, organised and documented so that result data and valuable data can be reused in future research projects, and fulfill the requirement of open as possible closed as necessary and the FAIR principles. (Metadata and documentation)
Why research data management?
"... we all do data, whether we are humanists, scientists or social scientists"
(Graham Pryor (2012)
Research data management is good research practice as it:
- increases the value of research
- improves research visibility
- increases the possibility of more citation
- reduces the risk of data loss and corruption
- avoids data duplication
- enables research verifiability
- allows sharing and re-using of data with future researchers
- maximizes the impact of scientific publications
- increases public visibility of funded research and encourages "citizen science"
Research data management and accessibility to public research data are required by the Government, the Research Council of Norway, EU, the European Research Council and UiO.
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1Definition of research data from Borgman, Christine L. 2015. Big Data, Little Data, No Data : Scholarship in the Networked World. Cambridge, MA: MIT Press.