A Practical Guide to Make Data FAIR(er)
Buch, Englisch, 332 Seiten, Format (B × H): 155 mm x 235 mm
ISBN: 978-3-032-41652-0
Verlag: Springer
Making data Findable, Accessible, Interoperable, and Reusable (FAIR) is increasingly recognized as an essential part of responsible data stewardship. But how can the FAIR principles actually be put into practice?
This book provides a practical, step-by-step guide to FAIR data stewardship and the FAIRification of data. Using a project-based learning approach, it presents a realistic use case that is progressively FAIRified throughout the book. Before each step, the reader is introduced to the knowledge and techniques needed to carry it out. Additional examples illustrate how the same principles can be applied to situations beyond the running use case.
The book draws on ten years of experience teaching the FAIR principles and FAIRification processes to hundreds of data stewards, researchers, data scientists, and students across Europe, North America, and Brazil. This includes training delivered through the Nordic e-Infrastructure Collaboration (NeIC), the University of California San Diego, the University of Twente, and Brazilian universities, research communities, and governmental agencies.
Designed for both academic and industrial settings, this book is aimed at data stewards, data scientists, researchers, and other professionals involved in making data FAIR. Its structure mirrors the FAIRification process, providing the knowledge and practical guidance needed at each stage.
Whether you are beginning your FAIR journey or looking for a systematic approach to FAIRifying existing data, this book provides a hands-on introduction to the concepts, methods, and practices needed to make data FAIR(er).
Zielgruppe
Professional/practitioner
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken
- Mathematik | Informatik EDV | Informatik EDV & Informatik Allgemein
- Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung Netzwerksicherheit
- Mathematik | Informatik EDV | Informatik Technische Informatik Computersicherheit
Weitere Infos & Material
1. Introduction.- 2. FAIR principles explained.- 3. FAIRification process and planning.- 4. Semantic interoperability and the FAIR principles.- 5. Semantic data modeling to facilitate data integration.- 6. Metadata and semantic metadata modeling.- 7. FAIR assessment and publication.




