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Data Train–Training in Research Data Management and Data Science

Currently on Data Train

In full swing: the "Data Train Starter Track"

Next course to come:

Data and information management, 14.04.2021 9-12 am

Data sets

A comprehensive management of research data is part of each research project and belongs to good scientific practice. It accompanies each phase of a research project – from the proposal phase via data acquisition and data analyses to the publication phase. The overall goal of research data management is the production of findable (F), accessible (A), Interoperable (I) and reusable (R) – FAIR - data sets.

A good stewardship of data (following the FAIR principles; Wilkinson et al., 2016) and an open data culture (Nosek et al., 2015) foster reproducibility as well as sustainability in science and makes up the fundament for data science applications

Contents

  • Research data: Data life cycle and accompanied challenges
  • Data management plans (DMP)
  • FAIR data principle
  • Meta data: standardization and its significance
  • Archiving, publication and citation of research data sets

Outcomes

  • Understanding for the significance of research data management and an overview about concepts and approaches

Frank Oliver Glöckner & Ivaylo Kostadinov

Professor for Earth System Data Science at University Bremen

&

Data Champion at GFBio e.V.

 

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