東華大學圖書館 |

Data science landscape = towards research standards and protocols /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Data science landscape/ edited by Usha Mujoo Munshi, Neeta Verma.
其他題名:	towards research standards and protocols /
其他作者:	Munshi, Usha Mujoo.
出版者:	Singapore :Springer Singapore : : 2018.,
面頁冊數:	xvii, 339 p. :ill., digital ;24 cm.
內容註:	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.
Contained By:	Springer eBooks
標題:	Big data. -
電子資源:	http://dx.doi.org/10.1007/978-981-10-7515-5
ISBN:	9789811075155

Data science landscape = towards research standards and protocols /
Data science landscapetowards research standards and protocols /[electronic resource] :edited by Usha Mujoo Munshi, Neeta Verma. - Singapore :Springer Singapore :2018. - xvii, 339 p. :ill., digital ;24 cm. - Studies in big data,v.382197-6503 ;. - Studies in big data ;v.38..

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.

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.

ISBN: 9789811075155

Standard No.: 10.1007/978-981-10-7515-5doiSubjects--Topical Terms:

2045508
Big data.

LC Class. No.: QA76.9.B45 / D383 2018

Dewey Class. No.: 005.7

Data science landscape = towards research standards and protocols /
LDR:04525nmm a2200301 a 4500 001 2136874
003 DE-He213
005 20180927105803.0
006 m d
007 cr nn 008maaau
008 181117s2018 si s 0 eng d
020 $a 9789811075155 $q (electronic bk.)
020 $a 9789811075148 $q (paper)
024 7 $a 10.1007/978-981-10-7515-5 $2 doi
035 $a 978-981-10-7515-5
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.B45 $b D383 2018
082 0 4 $a 005.7 $2 23
090 $a QA76.9.B45 $b D232 2018
245 0 0 $a Data science landscape $h [electronic resource] : $b towards research standards and protocols / $c edited by Usha Mujoo Munshi, Neeta Verma.
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2018.
300 $a xvii, 339 p. : $b ill., digital ; $c 24 cm.
490 1 $a Studies in big data, $x 2197-6503 ; $v v.38
505 0 $a 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.
520 $a 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.
650 0 $a Big data. $3 2045508
650 0 $a Database management. $3 527442
650 0 $a Internet of things. $3 2057703
650 1 4 $a Computer Science. $3 626642
650 2 4 $a Big Data. $3 3134868
650 2 4 $a Database Management. $3 891010
650 2 4 $a Big Data/Analytics. $3 2186785
700 1 $a Munshi, Usha Mujoo. $3 1572959
700 1 $a Verma, Neeta. $3 3308684
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a Studies in big data ; $v v.38. $3 3308685
856 4 0 $u http://dx.doi.org/10.1007/978-981-10-7515-5
950 $a Engineering (Springer-11647)