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Data science landscape: towards research standards and protocols

Contributor(s): Munshi, Usha Mujoo [Editor] | Verma, Neeta [Editor].
Material type: materialTypeLabelBookSeries: Studies in big data. Publisher: Singapore Springer 2018Description: xvii, 339 p. Includes index.ISBN: 9789811075148.Subject(s): Big data | Database management | Internet of thingsDDC classification: 005.7 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 system including citation protocols for use by research communities in different disciplines and also address various technical research issues. The volume, thus, focuses on some of these issues drawing typical examples from various domains. The idea of this work germinated from the two day workshop on “Big and Open Data – Evolving Data Science Standards and Citation Attribution Practices”, an international workshop, led by the ICSU-CODATA and attended by over 300 domain experts. The Workshop focused on two priority areas (i) Big and Open Data: Prioritizing, Addressing and Establishing Standards and Good Practices and (ii) Big and Open Data: Data Attribution and Citation Practices. This important international event was part of a worldwide initiative led by ICSU, and the CODATA-Data Citation Task Group. In all, there are 21 chapters (with 21st Chapter addressing four different core aspects) written by eminent researchers in the field which deal with key issues of S&T, institutional, financial, sustainability, legal, IPR, data protocols, community norms and others, that need attention related to data management practices and protocols, coordinate area activities, and promote common practices and standards of the research community globally. In addition to the aspects touched above, the national / international perspectives of data and its various contours have also been portrayed through case studies in this volume. https://www.springer.com/gp/book/9789811075148
List(s) this item appears in: Data Science
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Table of contents

Data Science Landscape: Tracking the Ecosystem
Pages 1-31
Open Data Infrastructure for Research and Development
Pages 33-43
Managing Research Data by R&D Community in Nuclear Data Science in India
Pages 45-57
Big Data in Astronomy and Beyond
Pages 59-66
Preserving for a More Just Future: Tactics of Activist Data Archiving
Pages 67-78
Little Data from Big Data for Disaster Risk Reduction in India
Pages 79-97
Data Marketplace as a Platform for Sharing Scientific Data
Pages 99-105
ICSSR Data Service : A National Initiative for Sharing of Social Science Research Data
Pages 107-125
Prismatic Consumer Insights Through Big Data : A Case Study of National Consumer Helpline
Pages 127-140
Big Data in the Context of Smart Cities : Exploring Urban Planning and Governance
Pages 141-150
Crowd Sourcing for Municipal Governance
Pages 151-164
Effective Business Development for In-Market IT Innovations with Industry-Driven API Composition
Pages 165-181
The Data that Get Forgotten
Pages 183-198
Big Data and Predictive Analytics : A Facilitator for Talent Management
Pages 199-204
Privacy Preserving Data Mining Techniques for Hiding Sensitive Data : A Step Towards Open Data
Pages 205-212
Role of Credible Data in Economic Decision Making
Pages 213-234
Big Data in the International System: Indian, American, and Other Perspectives
Pages 235-245
Evolving an Industrial Digital Ecosystem: A Transformative Case of Leather Industry
Pages 247-272
Applying Big Data Analytics in Governance to Achieve Sustainable Development Goals (SDGs) in India
Pages 273-291
Open Data: India’s Initiative for Researchers, Research, and Innovation
Pages 293-303
Data Management, Sharing and Services: Issues of Attitude Towards Data Citation and Role of Data Stakeholders
Pages 305-309
UK-India Research and Innovation Collaboration: Taking Forward Collaboration on Big Data and E-infrastructure
Pages 311-316
The Urgent Need to Overcome a Generation Gap in Public Data Management Practices for Digitalized India
Pages 317-319
Data Security in Cloud-Based Applications
Pages 321-326


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 system including citation protocols for use by research communities in different disciplines and also address various technical research issues. The volume, thus, focuses on some of these issues drawing typical examples from various domains.
The idea of this work germinated from the two day workshop on “Big and Open Data – Evolving Data Science Standards and Citation Attribution Practices”, an international workshop, led by the ICSU-CODATA and attended by over 300 domain experts. The Workshop focused on two priority areas (i) Big and Open Data: Prioritizing, Addressing and Establishing Standards and Good Practices and (ii) Big and Open Data: Data Attribution and Citation Practices. This important international event was part of a worldwide initiative led by ICSU, and the CODATA-Data Citation Task Group.
In all, there are 21 chapters (with 21st Chapter addressing four different core aspects) written by eminent researchers in the field which deal with key issues of S&T, institutional, financial, sustainability, legal, IPR, data protocols, community norms and others, that need attention related to data management practices and protocols, coordinate area activities, and promote common practices and standards of the research community globally. In addition to the aspects touched above, the national / international perspectives of data and its various contours have also been portrayed through case studies in this volume.


https://www.springer.com/gp/book/9789811075148

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