The Data Science Framework: A View from the EDISON Project
The Data Science Framework: A View from the EDISON Project
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- More about The Data Science Framework: A View from the EDISON Project
The edited book consolidates the results of the EU-funded EDISON project and presents data science competencies, body of knowledge, model curriculum, profiles of professionals, and use cases and applications, with appendices on related process models. It can be used to develop new courses, evaluate existing modules and courses, draft job descriptions, and plan and design efficient data-intensive research teams across scientific disciplines.
Format: Paperback / softback
Length: 194 pages
Publication date: 03 October 2021
Publisher: Springer Nature Switzerland AG
Edited Book: "Education for Data Intensive Science to Open New Science Frontiers"
This edited book 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.
Book Overview:
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.
Weight: 326g
Dimension: 235 x 155 (mm)
ISBN-13: 9783030510251
Edition number: 1st ed. 2020
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