An ethico-legal framework for social data science
Autor: | Iryna Lishchuk, Stefanie Hänold, Jeroen van den Hoven, Francesca Pratesi, René Louis Pierre Mahieu, Tina Krügel, Anna Monreale, Nikolaus Forgó, David van Putten, Dino Pedreschi |
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Přispěvatelé: | Law Science Technology and Society, Metajuridica, Faculty of Law and Criminology |
Jazyk: | angličtina |
Předmět: |
Open platform
business.industry Computer science Ethical data science Legal data science Research infrastructure Applied Mathematics Massive open online course Big data Context (language use) 02 engineering and technology Data science Computer Science Applications Management information systems Computational Theory and Mathematics Modelling and Simulation 020204 information systems Modeling and Simulation 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing business Information Systems |
Zdroj: | International Journal of Data Science and Analytics, 11(4) International Journal of Data Science and Analytics (2020). doi:10.1007/s41060-020-00211-7 info:cnr-pdr/source/autori:Forgó N.; Hänold S.; van den Hoven J.; Krügel T.; Lishchuk I.; Mahieu R.; Monreale A.; Pedreschi D.; Pratesi F.; van Putten D./titolo:An ethico-legal framework for social data science/doi:10.1007%2Fs41060-020-00211-7/rivista:International Journal of Data Science and Analytics (Print)/anno:2020/pagina_da:/pagina_a:/intervallo_pagine:/volume 11 (2020): 377–390. doi:10.1007/s41060-020-00211-7 |
ISSN: | 2364-4168 2364-415X |
DOI: | 10.1007/s41060-020-00211-7 |
Popis: | This paper presents a framework for research infrastructures enabling ethically sensitive and legally compliant data science in Europe. Our goal is to describe how to design and implement an open platform for big data social science, including, in particular, personal data. To this end, we discuss a number of infrastructural, organizational and methodological principles to be developed for a concrete implementation. These include not only systematically tools and methodologies that effectively enable both the empirical evaluation of the privacy risk and data transformations by using privacy-preserving approaches, but also the development of training materials (a massive open online course) and organizational instruments based on legal and ethical principles. This paper provides, by way of example, the implementation that was adopted within the context of the SoBigData Research Infrastructure. |
Databáze: | OpenAIRE |
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