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Research Data Management

Research Data Management is a broad term referring to technologies and best practices related to tracking the creation, backing up, processing, analysis, publishing, archiving, and ultimately destroying research data, also known as the data life cycle (cf. diagram on this page, CC BY - University Library Zurich). Metadata describing the data is stored in addition to the data itself.

Managing data can be challenging for various reasons, including when:

  • Data volumes are large
  • Many people need to share and access data
  • Data is continuously created from multiple sources
  • Data is analyzed using central workflows
  • Data needs to be converted or pre-processed
  • Data access needs to be controlled or logged
  • Metadata describing the data is complex
  • Handling sensitive or confidential data

Science IT can support you in one or more of the above-mentioned areas, including support to access National Data management services, such as In addition, we have practical experience managing large datasets and setting up and running data management tools such as openBIS.

Do you need help with other aspects of the research data management, such as for example data management planning or publishing and sharing data on a repository, please get in touch with the University Library's Open Science Services.

How to initiate an expert service

  • Get in contact with Science IT and explain briefly what type of service you are interested in together with a short description of your use case and needs  contact Science IT
  • Based on the information you provided, your request will be routed to a suitable expert, who gets in contact with you to follow up on the remaining steps

Terms and conditions

  • Efforts-based costs
  • Expert services are restricted to UZH researchers and groups
  • More details (incl. costs and agreement templates) are available in the UZH Intranet