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Efficient Data Management for Putting Forward Data Centric Sciences

  • Genoveva Vargas-SolarEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 767)

Abstract

The novel and multidisciplinary data centric and scientific movement promises new and not yet imagined applications that rely on massive amounts of evolving data that need to be cleaned, integrated, and analysed for modelling, prediction, and critical decision making purposes. This paper explores the key challenges and opportunities for data management in this new scientific context, and discusses how data management can best contribute to data centric sciences applications through clever data science strategies.

Notes

Acknowledgement

This work has been partially funded by the project MULTIPOINT, the cooperation contract Clouding Things and the COST EU Actions KEYSTONE.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Univ. Grenoble Alpes, CNRS, Grenoble INP, LIG-LAFMIAGrenobleFrance

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