Research Data Guide

Managing research data

IT administration of the University of Oulu

IT services: Data storage: Personal storage at the University of Oulu

Naming and managing files. File formats

RD files and folders need to be organized in a systematic way so that they are identifiable and accessible for yourself, your colleques and for future users. Therefore pay attention that names of files and folders are consistent but unique. Consider including e.g. following elements

  • project name/acronym
  • experiment/instrument type
  • initials of researchers
  • date
  • version number

Avoid special characters and spaces when naming files and folders.

Data versioning is about saving new copies of your files when you make changes so that you can go back and retrieve specific versions of your files later. E.g. rd1; rd2; re2.1. etc.  or  naming files like final or final_revised etc.

Read about naming and managing files and about physical data storage  by Finnish Social Science Data Archive

File formats that are suitable for long terms storage of research data by CSC

File naming and folder structure by CESSDA

Document your file naming conventions and folder structure.

UOulu data helpdesk

Licensing research data

It is recommended to make all research data, code and software created within a research project available for reuse e.g. under Creative Commons, GNU, MIT or another relevant license. The recommended CC license according to open science principles is the CC-BY.

Research data. How to license. Training materials by OpenAIRE.

SPDX LIcense List

Storing research data during the research project

Research data are a valuable resource, even after the research projects has ended. Research data are also viewed by many research funders as a public good which should be openly available to the academic community and preserved for future re-use.

Researchers and research groups should have basic knowledge of what data preservation and physical storage entail. Physical preservation requires careful monitoring of data quality and system integrity, upgrade and validation measures, disaster preparedness, and constant development of the system. At least

Data repositories