Introduction RDM

Research data management is about ensuring the right decisions are taken when creating, organizing, and storing data derived from diverse research activities. Research data management (RDM) is also about taking decisions and planning how this data will be looked after over the lifetime of a project and beyond.


Research data refers to data which is created during a particular research process or is the result from this process. Research data can be generated through a variety of methods such as experiments, measurements, interviews, questionnaires, etc. This results in different definitions and interpretations as to what research data are by different research communities.

Benefits of good research data management (RDM)

  • Data security is enhanced, data loss minimized
  • Your research remains accurate, transparent, und reliable
  • Helps you comply with funding requirements
  • Your research outputs meet the FAIR Standard and may thus be replicated



In 2018 the academic senate approved the MLU’s research data management policy and an open science working group, mentored by the Vice-Chancellor for research, started a number of activities. These include the procurement of advice and support for scientists and data creators on a variety of research data management topics, the provision of an infrastructure for publishing scientific results, and the creation of an expert’s network to provide our research communities subject specific interdisciplinary advice on a number of RDM topics.

The ULB participates actively in these groups focusing on providing specific advice with the writing of research data management plans and support for publishing research results via our publications and research data repository Share_it.  We work closely with other service institutions at the MLU to create a suitable open research data ecosystem for our authors and data creators.