Skip to Main Content
It looks like you're using Internet Explorer 11 or older. This website works best with modern browsers such as the latest versions of Chrome, Firefox, Safari, and Edge. If you continue with this browser, you may see unexpected results.

Research Data Management

What is research data management (RDM)?

Research data management (RDM) means organization, description, storage, preservation, and sharing of data collected and used in a research project. This guide is intended to give an overview of the practices and process of managing your research data.

RDM is an integral part of good research practices. Hanken students and researchers are responsible for complying with good data management practices that include Hanken's ethical research guidelines on the management and sharing of research data, data security and data protection in accordance with legislation and research integrity. Departments and principal investigators ought to familiarize students and research staff with good data management practices. See Instructions for supervisors.

Follow the stages and checklist outlined in Data management process at Hanken. These concrete stages with descriptions, as well as must-dos, in each stage offer students and researchers, respectively, comprehensive and thorough guides that you can trace the whole data management process easily, clearly, and closely.

E-forms and templates you (may) need are:

What are research data and why manage your data?

In principle, 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. 

In RDM, research data are generally understood as digital datasets generated, processed, and used in scientific research, and can include

  • 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 up research results for publication.
  • 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

Help and support for research data management is a network of staff from Hanken's research services, legal support, Data Protection Officer, IT Services, and the library. Questions about data management, ethical and legal matters concerning data security, data protection and IPR issues, assistance with data management plans, data storage, and data sharing and preservation, please contact Hanken's Data Protection Officer or

We also provide training in creating data management plans and in data management and data protection throughout your research lifecycle. Training is offered both as part of studies and as staff training. More information, see Courses and workshops.