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The Development of Data Science: Implications for Education, Employment, Research, and the Data Revolution for Sustainable Development
Fionn Murtagh, Keith Devlin
Department of Computer Science
School of Computing and Engineering
Research output
:
Contribution to journal
›
Article
›
peer-review
8
Citations (Scopus)
Overview
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Dive into the research topics of 'The Development of Data Science: Implications for Education, Employment, Research, and the Data Revolution for Sustainable Development'. Together they form a unique fingerprint.
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Business & Economics
Sustainable Development
42%
Education
34%
Employability
32%
Methodology
28%
Data Aggregation
27%
Provisioning
23%
Scale Effect
22%
Research Issues
21%
Mathematics
20%
Big Data
18%
Unification
18%
Decision Support
18%
Policy Making
17%
Empirical Data
16%
Social Sciences
15%
Mathematics
Sustainable Development
100%
Education
62%
Methodology
15%
Data Aggregation
12%
Scale Effect
11%
Decision Support
10%
Ethics
9%
Context
8%
Universities
8%
Social Sciences
8%
Unification
7%
Policy
6%
Relevance
6%
Requirements
5%
Engineering & Materials Science
Data Science
77%
Sustainable development
50%
Education
48%
Ethical aspects
12%
Social sciences
11%
Data Analytics
10%
Big data
8%
Agglomeration
8%