Research Data Management

Research data management (RDM) means description, organization, storage, preservation, sharing, and publishing of data collected and used in a research project. Effective and responsible RDM is an integral part and essential requirement of good scientific practices and research skills. 

Departments and principal investigators ought to familiarize students and research staff with good data management practices. See also Instructions for supervisors.

Research data can be any material a research project uses and produces as the basis for research findings from the starting (hypothesis, research questions) to the concluding (research outputs) point of the research, in either physical or digital form. 

Digital datasets generated, processed, and used in scientific research can be:

• data collected by various methods (such as surveys, interviews, video recordings, images),
• data produced during the research (such as analysis results),
• research sources reused (such as open archived data, commercial databases),
• source code and software, and
• information describing the context, contents and structure of the data (readme files and metadata).

Benefits of managing research data include:

• Well-managed and documented data make it easier to write research results for publications.
• Making it easier to find, understand, cite, and reuse your data to increase the impact of your research.
• Enabling the sharing of data within and across disciplines, facilitating collaboration and promoting new discoveries.
• Meeting funders' requirements and journal data policies.
• Comply with data protection legislation and agree upon data ownership and rights.
• Archiving and preserving your data in the long term.
• Saving time and resources.
• Supporting open science.

Help and support for RDM is a network of staff from Hanken's Library, Research integrity advisor, Research services, Data protection specialist, legal support, and IT services.

Contact dataethics@hanken.fi if you have any questions on ethical and legal matters concerning data security, data protection and IPR issues, Data management plan (DMP), data storage, backup, and transfers, metadata creation, data archival and preservation.

Trainings are offered as part of studies and staff training. They can be integrated into standard seminars or courses, independent training sessions, individual guidance or online guides. More information, see Courses and workshops.

• Data management guidelines by the Finnish Social Science Data Archive (FSD).
• Data Management and Storage by CSC.
• CSC's self-study course on Research data management (Log in with your HAKA ID): CSC's self-study "Research data management" course has been published.
• Data management checklist by the Fairdata services fairdata.fi.
• Research data management by the University of Helsinki.
• Guidance for research data management at JYU by the University of Jyväskylä.
• Research Data Management Training MANTRA by the University of Edinburgh.
• The Research Data Alliance.