289 search results for “data” in the Library website
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Data Carpentry with R for Social Sciences and Humanities
Workshop
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Data Carpentry with R for Social Sciences and Humanities
Workshop
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Data Carpentry with R for Social Sciences and Humanities
Workshop
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Data Carpentry with R for Social Sciences and Humanities
Workshop
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Gijsbert Boon -
Christos Athanasiadis -
Rogier CreemersFaculty of Humanities
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Arno Knobbe -
Mark de Rooij
Faculty of Social and Behavioural Sciences
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Sjoerd HuismanFaculty of Social and Behavioural Sciences
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Alberto CeriaFaculty of Social and Behavioural Sciences
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Yilin Jiang -
Arjen Doelman -
Arda Ergin -
Holger Hoos -
Stefan Manegold -
Jujia Zhao -
to FAIR2: Turning principles into practice for responsible, AI-ready data
Webinar with Q&A
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& Exchange: A national training and community platform for research data professionals
Webinar, discussion
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Gavin RobinsonFaculteit der Rechtsgeleerdheid
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Mitra Baratchi -
Marco Spruit -
Olivier Béquignon -
Mirjam van Reisen -
Martin KroonFaculty of Humanities
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Lifeng Han -
Ana Letícia Garcez Vicente -
I-Fan Lin -
Yumeng Wang -
Gamal Adel Elgamal -
Fabrizio Corriera -
Ella Has -
Gijs van Seeventer -
Hein Putter -
Zhong Li -
Sander van Rijn -
Gerard van Westen -
Yuliia Kazmina -
Tom Kouwenhoven -
Michiel DamICLON
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Serge RomboutsFaculty of Social and Behavioural Sciences
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Simon Portegies Zwart -
Nuno De Mesquita César de Sá -
Martin Berger -
Sebastian Fajardo Bernal -
Siuman Chung
Faculty of Social and Behavioural Sciences
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Stylianos Paraschiakos -
Michael Lew -
RDM Checklist
In short, data management can be defined as the creation, storage, maintenance, disclosure, archiving and sustainable preservation of research data. Increasingly the so called FAIR principles are referred to as a final goal: data should be made 'Findable, Accessible, Interoperable and Re-usable'.
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Text & datamining
Text and Data Mining (TDM) is increasingly applied in various academic disciplines to extract useful information from unstructured textual data using computational methods.