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Data Science Framework: A View from the EDISON Project 2020 ed. [Kõva köide]

  • Formaat: Hardback, 194 pages, kõrgus x laius: 235x155 mm, kaal: 483 g, 31 Illustrations, color; 4 Illustrations, black and white; XIV, 194 p. 35 illus., 31 illus. in color., 1 Hardback
  • Ilmumisaeg: 02-Oct-2020
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 3030510220
  • ISBN-13: 9783030510220
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  • Hind: 150,61 €*
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  • Formaat: Hardback, 194 pages, kõrgus x laius: 235x155 mm, kaal: 483 g, 31 Illustrations, color; 4 Illustrations, black and white; XIV, 194 p. 35 illus., 31 illus. in color., 1 Hardback
  • Ilmumisaeg: 02-Oct-2020
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 3030510220
  • ISBN-13: 9783030510220

This edited book first consolidates the results of the EU-funded EDISON project (Education for Data Intensive Science to Open New science frontiers), which developed training material and information to assist educators, trainers, employers, and research infrastructure managers in identifying, recruiting and inspiring the data science professionals of the future. It then deepens the presentation of the information and knowledge gained to allow for easier assimilation by the reader.

The contributed chapters are presented in sequence, each chapter picking up from the end point of the previous one. After the initial book and project overview, the chapters present the relevant data science competencies and body of knowledge, the model curriculum required to teach the required foundations, profiles of professionals in this domain, and use cases and applications. The text is supported with appendices on related process models.

The book can be used to develop new courses in data science, evaluate existing modules and courses, draft job descriptions, and plan and design efficient data-intensive research teams across scientific disciplines.


Introduction to the Data Science Framework.- Data Science Competences.- Data Science Body of Knowledge.- Data Science Curriculum.- Data Science Professional Profiles.- Use Cases and Applications.- App. A, Data Science Related Process Models.