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Data science landscape : towards research standards and protocols

Author: Usha Mujoo Munshi; Neeta Verma
Publisher: Singapore : Springer, 2018.
Series: Studies in big data, v. 38.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
The edited volume deals with different contours of data science with special reference to data management for the research innovation landscape. The data is becoming pervasive in all spheres of human, economic and development activity. In this context, it is important to take stock of what is being done in the data management area and begin to prioritize, consider and formulate adoption of a formal data management  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Data science landscape.
Singapore : Springer, 2018
(OCoLC)1009183389
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Usha Mujoo Munshi; Neeta Verma
ISBN: 9789811075155 9811075158
OCLC Number: 1027220915
Notes: Includes indexes.
Description: 1 online resource (xvii, 339 pages) : illustrations
Contents: Chapter 1. Data Science Landscape --
Tracking the Ecosystem --
Chapter 2. Open Data Infrastructure for Research and Development --
Chapter 3. Managing Research Data by R & D community in Nuclear Data Science in India --
Chapter 4. Big Data in Astronomy and Beyond --
Chapter 5. Preserving for a More Just Future: Tactics of Activist Data Archiving --
Chapter 6. Little Data from Big Data for Disaster Risk Reduction in India --
Chapter 7. Data Marketplace as a Platform for Sharing Scientific Data --
Chapter 8. ICSSR Data Service: A National Initiative for Sharing of Social Science Research Data --
Chapter 9. Prismatic Consumer Insights through Big Data: A Case Study of National Consumer Helpline --
Chapter 10. Big Data in the Context of Smart Cities: Exploring Urban Planning and Governance --
Chapter 11. Crowd sourcing for Municipal Governance --
Chapter 12. Effective Business Development for In-Market IT Innovations with Industry-driven API Composition --
Chapter 13. The Data that Get Forgotten --
Chapter 14. Big data and Predictive Analytics: A facilitator of Talent Management --
Chapter 15. Privacy Preserving Data Mining Techniques for Hiding Sensitive Data --
A Step Towards Open Data --
Chapter 16. Role of Credible Data in Economic Decision Making --
Chapter 17. Big Data in the International System: Indian, American and Other Perspectives --
Chapter 18. Evolving an Industrial Digital Ecosystem --
A Case of Leather Industry --
Chapter 19. Applying Big Data Analytics in Governance to Achieve Sustainable Development Goals (SDGs) in India --
Chapter 20. Open Data: India's Initiative for Researchers, Research and Innovation --
Chapter 21. Data Science Management: Some Perspectives.
Series Title: Studies in big data, v. 38.
Responsibility: Usha Mujoo Munshi, Neeta Verma, editors.

Abstract:

The edited volume deals with different contours of data science with special reference to data management for the research innovation landscape.  Read more...

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