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Love Data Week



Love Data Week

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Love Data Week is the international celebration of data from February 13-17, 2023 with numerous events on research data management topics.

Research data accumulates during scientific activity and regularly forms the basis of scientific work. Research data management (RDM) - the secure management, storage and long-term archiving of research data - makes an important contribution to the reproducibility of scientific work. 

Researchers face the challenge of not only documenting data, but also preserving it and making it available for reuse. A data management plan (DMP) helps to structure how you handle research data since it describes how you collect, manage, store, archive, and reuse your data.

Some research funders also request a data management plan at the time of application. Even if a DMP is not required, by creating one, you as a researcher will benefit from improved knowledge management, ensure compliance with good scientific practice, and easier re-use of research data.

Love Data Week aims to raise awareness about research data, data management, data literacy, and open science. To generate attention for these topics, numerous events are held each year around Valentine's Day.

These events provide an introduction, give practical tips, and present best-practices, and thus will support you in adopting good data practices. The BIH Quest Center is represented with a contribution "Love your protocol first before you turn to data". We would also like to draw your attention to the following exciting events from the program of FDM initiatives in Germany:

  • February 13, 1 - 1:30 p.m.: Coffee Lecture: Einführung ins Forschungsdatenmanagement
  • February 13, 3 - 4 p.m.: Data (horror) Escape Room - gemeinsam Rätsel zum Thema Forschungsdatenmanagement knacken
  • February 16, 3 - 5 pm: 'Wind of change - sharing is caring' - How to improve research data and its benefits in the Life Sciences.

The complete program for Love Data Week is available on the following websites:

More information on research data management:


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