The Development of Data Science: Implications for Education, Employment, Research, and the Data Revolution for Sustainable Development
Abstract
:1. Data Science as the Convergence and Bridging of Disciplines
2. Historical Development of Data Science and Some Contemporary Examples of Cross-Disciplinarity
2.1. Historical Prominence of Data Science in Recent Times
- in the design of an overarching semantic layer addressing data and analysis tools,
- in identifying suitable data sources and data patterns that correspond to the appearance of structured and unstructured data, and
- in the management of the information discovery lifecycle and discovery teams.
2.2. Practical Association of Disciplines and Sub-Disciplines
3. Open Data, Reproducibility and the Data Curation Challenge
4. Integration of Data and Analytics: Context of Applications
5. Short Review of Contemporary Data Science in Education and in Employment
5.1. Teaching and Learning for Data Science
5.2. Employment Requirements in Data Science
6. Data Science Methodology to Address: Selection Bias, Scale and Aggregation Effects, and Qualitative Evaluation of Decision-Making Impact
7. Benefits of Very High Profiling of Data Science
8. Important New Research Challenges from Data
9. Information Space Theory for Big Data Analytics in Internet of Things and Smart Environments
Context, Situation Theory, Completion Diagrams
10. Conclusions
Author Contributions
Conflicts of Interest
References
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Murtagh, F.; Devlin, K. The Development of Data Science: Implications for Education, Employment, Research, and the Data Revolution for Sustainable Development. Big Data Cogn. Comput. 2018, 2, 14. https://doi.org/10.3390/bdcc2020014
Murtagh F, Devlin K. The Development of Data Science: Implications for Education, Employment, Research, and the Data Revolution for Sustainable Development. Big Data and Cognitive Computing. 2018; 2(2):14. https://doi.org/10.3390/bdcc2020014
Chicago/Turabian StyleMurtagh, Fionn, and Keith Devlin. 2018. "The Development of Data Science: Implications for Education, Employment, Research, and the Data Revolution for Sustainable Development" Big Data and Cognitive Computing 2, no. 2: 14. https://doi.org/10.3390/bdcc2020014
APA StyleMurtagh, F., & Devlin, K. (2018). The Development of Data Science: Implications for Education, Employment, Research, and the Data Revolution for Sustainable Development. Big Data and Cognitive Computing, 2(2), 14. https://doi.org/10.3390/bdcc2020014