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Why Research Data Management?

There are many reasons why you should engage with research data management (RDM).

Collecting data is often expensive. Discovering and using existing data can save valuable resources, time, and costly duplication of efforts.

RDM can help you avoid data loss. More than a third of the respondents of the Austria-wide study "Researchers and Their Data" (2015) had experienced this during their career.

Research data management makes results reproducible. It allows to validate the robustness of the results in replication studies, thereby increasing the scientific recognition and reputation of the original study.

Research data contains scientific findings that often go beyond the scope of the original project. They can also be linked to other data and analyzed using text and data mining. RDM supports interdisciplinary research as well as the generation of new, data-driven hypotheses.

Research funding agencies such as the FWF in Austria and academic publishers such as the American Economic Association recognize the relevance of research data. They want to make the use of research data available to others in order to maximize the potential of the data. Therefore, they increasingly demand professional research data management and require this for financial support and publication of studies.

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