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Research Data Management

RDM principle and requirements

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. This guide is intended to give an overview of the practices and processes of your data management.

A RDM principle is that research data are “as closed as necessary and as open as possible”:
  • “As closed as necessary” means that you need to ensure ethical and legal compliance in data management. Hanken students and researchers are responsible for complying with the ethical principles and good data management practices in accordance with relevant legislations and research integrity.

These issues may require additional data protection safeguard measures and ethical assessment. Before you start to collect data, check:

Contact for advice and assistance. 

  • “As open as possible” means that research data are managed appropriately in line with the FAIR data principles. It is an essentially good scientific practice to follow the FAIR data principles when publishing your research outputs to ensure the discoverability and citability of your research data. 

Follow the Data management flowcharts and stages outlined in Data management processes at Hanken in this LibGuide. These flowcharts and stages give students and researchers, respectively, practical guidance on how to implement this RDM principle and ​how to complete your various RDM tasks step by step throughout your data life cycle.​ The instructions and templates in each stage offer you the guidance that you can trace and complete the whole data management process.

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

                                  Data management flow

What are research data and why manage your data?

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

Help and support for research data management is a network of staff from Hanken's Library, Research Integrity Advisor, Research services, Data protection officer (DPO), legal support, and IT services.

If you have questions about ethical and legal matters concerning data security, data protection and IPR issues, writing and updating your Data management plan (DMP), data storage, backup, and transfers, metadata creation, data archival and preservation, please contact or

We also provide trainings to support you to complete various RDM tasks throughout your research life cycle. Trainings are offered both as part of studies and as 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.

Additional resources