Data Science Landscape

Towards Research Standards and Protocols

Автор: Usha Mujoo Munshi, Neeta Verma

Език:

Корици: С твърди корици

Издател: Springer Verlag, Singapore

Наличност: Външен склад

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The edited volume deals with different contours of data science with special reference to data manag...

Информация за книгата

Автор

Usha Mujoo Munshi, Neeta Verma

Език

Английски език

Корици

Книга - С твърди корици

Издадена

2018

страници

339

EAN

9789811075148

ISBN

981107514X

Enbook ID

18381786

Издател

Springer Verlag, Singapore

Теглоt

6623

Размери

155 x 235 x 25

Пълно описание

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.

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Data Science Landscape

Towards Research Standards and Protocols

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