ST-LE-2023-03
Curriculum: Starter TrackData and information management
Motivation
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.
Learning 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
Learning outcomesUnderstanding for the significance of research data management and an overview about concepts and approaches.
Prior knowledge
---
Further Reading
- Wilkinson, M. D. et al. The FAIR Guiding Principles for
scientific data management and stewardship. Sci. Data 3, 160018 (2016).
- Wilkinson, M. D. et al. Comment: A design framework and
exemplar metrics for FAIRness. Sci. Data 5, 1–4 (2018).
- Hodson, S. et al. Turning FAIR data into reality: interim
report from the European Commission Expert Group on FAIR data (Version Interim
draft). Interim Rep. from Eur. Comm. Expert Gr. FAIR data (2018). https://doi.org/10.5281/zenodo.1285272
- Collins, S. et al. FAIR Data Action Plan. Interim Recomm.
actions from Eur. Comm. Expert Gr. FAIR data 1–21 (2018). https://doi.org/10.5281/zenodo.1285290
- Wilkinson, M. D. et al. Interoperability and FAIRness
through a novel combination of Web technologies. PeerJ Comput. Sci. 3, e110
(2017).
- Mons, B. et al. Cloudy, increasingly FAIR; Revisiting the
FAIR Data guiding principles for the European Open Science Cloud. Inf. Serv.
Use 37, 49–56 (2017).
Motivation
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.
Learning 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
Understanding for the significance of research data management and an overview about concepts and approaches.
Prior knowledge
---
Further Reading
- Wilkinson, M. D. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data 3, 160018 (2016).
- Wilkinson, M. D. et al. Comment: A design framework and exemplar metrics for FAIRness. Sci. Data 5, 1–4 (2018).
- Hodson, S. et al. Turning FAIR data into reality: interim report from the European Commission Expert Group on FAIR data (Version Interim draft). Interim Rep. from Eur. Comm. Expert Gr. FAIR data (2018). https://doi.org/10.5281/zenodo.1285272
- Collins, S. et al. FAIR Data Action Plan. Interim Recomm. actions from Eur. Comm. Expert Gr. FAIR data 1–21 (2018). https://doi.org/10.5281/zenodo.1285290
- Wilkinson, M. D. et al. Interoperability and FAIRness through a novel combination of Web technologies. PeerJ Comput. Sci. 3, e110 (2017).
- Mons, B. et al. Cloudy, increasingly FAIR; Revisiting the FAIR Data guiding principles for the European Open Science Cloud. Inf. Serv. Use 37, 49–56 (2017).
When?
March 9, 2023, 9:30 AM - 12:30 PM
Where?
UNICOM 2
Haus Oxford, 2nd floor
2.2090, Large Seminar Room
Mary-Somerville-Straße 2
28359 Bremen
and
Online via Zoom
Register until:
March 06, 2023
Glöckner, Prof. Dr. Frank Oliver
Professor of Earth System Data Science
Department of Geosciences at the University of Bremen
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research
Head of Data at the Computing and Data Center
Head of PANGAEA Data Publisher for Earth & Environmental Science
GFBio e.V.
Email: frank.oliver.gloeckner@awi.de
Kostadinov, Dr. Ivaylo
Data Champion at GFBio e.V.
Email: ikostadi@gfbio.org
Cooperating in U Bremen Research Alliance:
