Data-driven science is becoming increasingly important in answering the pressing research questions of our time. Global warming, massive extinction of species and the impact on human health as well as the socio-economic consequences of the COVID-19 pandemic are just some recent examples. However, there is a significant deficit of qualified persons in (research) data management and data science to foster innovative “Big Data” technologies for science and the private sector worldwide.
The U Bremen Research Alliance, with the support of the Federal State of Bremen, has established the cross-institutional and cross-disciplinary training program "Data Train - Training in Research Data Management and Data Science" for doctoral researchers from member institutions.
"Data is the currency of the 21st century.
We need to invest this currency better to manage and grow our wealth of knowledge."Dr. Arjun Chennu, Data Train lecturer
Group Leader "Data Science and Technology", Leibniz Centre for tropical Marine Research
Currently on Data Train
Kick-off event 2023
During this event we willprovide information on the Data Train program, its scope, concept, and its connection to the Germany-wide initiative "National Research Data Infrastructure (NFDI)". Further, you will get insights into the curriculum planned for 2023.
Moreover, we will shed light on Data Science applications and will elucidate why one should be aware of Research Data Management principles when applied Data Science methods.
Starter Track
In the ‘Starter Track’, thematic overview lectures provide a general knowledge of important topics in data literacy, research data management, and data science. This track is intended for anyone who wants to get started in research data management and data science.
Schedule: January to May 2023
Registration: December 2022 - May 2023 (open shortly before a course starts)
Selected publications related to Data Train
- Whitepaper: Etablierung eines kooperativen Forschungsdatenmanagements in der U Bremen Research Alliance
Pigeot, Glöckner, Drechsler, Hörner, Schönfeld, Steinmann, Schmidt. 2021. Etablierung eines kooperativen Forschungsdatenmanagements in der U Bremen Research Alliance (Version V1). Zenodo. - Disziplinübergreifendes Modell zur Ausbildung von Forschungsdatenmanagement und Data Science Kompetenzen: ‚Data Train – Training in Research Data Management and Data Science‘
Hörner, Glöckner, Drechsler, Pigeot. 2021. Disziplinübergreifendes Modell zur Ausbildung von Forschungsdatenmanagement und Data Science Kompetenzen: ‚Data Train – Training in Research Data Management and Data Science‘. Bausteine Forschungsdatenmanagement, Nr. 3. German: 56-69. - FAIRsFAIR Report: Good Practices in FAIR Competence Education; Data Train als "Good Practice"
Garbuglia, Saenen, Gaillard, Engelhardt. 2021. D7.5 Good Practices in FAIR Competence Education (1.1 DRAFT). Zenodo - FAIRsFAIR Report: Data Train - Training in Research Data Management and Data Science: Good Practice #1
Garbuglia, Saenen, Gaillard. 2022. Data Train - Training in Research Data Management and Data Science: Good Practice #1. Zenodo - Handreichung: Open Educational Resources (OER) im Sinne von Open Science und einer FAIRen Daten-Kultur
Hackl, Hörner, Kalová, Slowig. 2022. Handreichung: Open Educational Resources (OER) im Sinne von Open Science und einer FAIRen Daten-Kultur. Zenodo. - Lernzielmatrix zum Themenbereich Forschungsdatenmanagement (FDM) für die Zielgruppen Studierende, PhDs und Data Stewards
Petersen, Engelhardt, Hörner, Jacob, Kvetnaya, Mühlichen, Schranzhofer, Schulz, Slowig, Trautwein-Bruns, Voigt, Wiljes. 2022. Lernzielmatrix zum Themenbereich Forschungsdatenmanagement (FDM) für die Zielgruppen Studierende, PhDs und Data Stewards (Version 1). Zenodo.
Cooperating in U Bremen Research Alliance:
