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Learning about text and data mining: The future of Open Science

Oudenhoven, Martine and Pontika, Nancy (2017). Learning about text and data mining: The future of Open Science. Open Science Conference, Berlin, Germany.

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The volume of digital data is doubling every two years. In the world of science, the cumulative total of articles published since 1665 is estimated to be more than 50 million. There is a wealth of knowledge hidden in this huge amount of articles, but reading and analysing all of them manually is not humanly possible. Text and data mining (TDM) can provide a solution. It can process millions of texts quickly and reveal patterns and trends that can lead to new discoveries in various fields, for example in research analytics, medicine, agriculture and social sciences. The European project OpenMinTeD [] helps to solve these problems with a new platform on text and data mining.

Item Type: Other
Copyright Holders: 2017 The Author(s)
Project Funding Details:
Funded Project NameProject IDFunding Body
OpenMinTeDNot SetEuropean Union FP7
Extra Information: Open Science Conference: 21 to 22 March 2017, Berlin
Keywords: text and data mining; OpenMinTeD; e-infrastructure; barriers
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
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Item ID: 49006
Depositing User: Nancy Pontika
Date Deposited: 29 Mar 2017 10:11
Last Modified: 12 Dec 2018 08:58
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These details should be considered as only a guide to the number of downloads performed manually. Algorithmic methods have been applied in an attempt to remove automated downloads from the displayed statistics but no guarantee can be made as to the accuracy of the figures.

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