Adjusting to the GDPR: The Impact on Data Scientists and Behavioral Researchers.

GDPR behavioral big data data protection information quality (InfoQ) privacy and policy

Journal

Big data
ISSN: 2167-647X
Titre abrégé: Big Data
Pays: United States
ID NLM: 101631218

Informations de publication

Date de publication:
09 2019
Historique:
pubmed: 30 4 2019
medline: 3 3 2020
entrez: 30 4 2019
Statut: ppublish

Résumé

Rapid growth in the availability of behavioral big data (BBD) has outpaced the speed of updates to ethical research codes and regulation of data privacy and human subjects' data collection, storage, and use. The introduction of the European Union's (EU's) General Data Protection Regulation (GDPR) in May 2018 will have far-reaching effects on data scientists and researchers who use BBD, not only in the EU, but around the world. Consequently, many companies are struggling to comply with the Regulation. At the same time, academics interested in research collaborations with companies are finding it more difficult to obtain data. In light of the importance of BBD in both industry and academia, data scientists and behavioral researchers would benefit from a deeper understanding of the GDPR's key concepts, definitions, and principles, especially as they apply to the data science workflow. We identify key GDPR concepts and principles and describe how they can impact the work of data scientists and researchers in this new data privacy regulation era.

Identifiants

pubmed: 31033336
doi: 10.1089/big.2018.0176
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

140-162

Auteurs

Travis Greene (T)

College of Technology Management, National Tsing Hua University, Hsinchu, Taiwan.

Galit Shmueli (G)

Institute of Service Science, National Tsing Hua University, Hsinchu, Taiwan.

Soumya Ray (S)

Institute of Service Science, National Tsing Hua University, Hsinchu, Taiwan.

Jan Fell (J)

Institute of Service Science, National Tsing Hua University, Hsinchu, Taiwan.

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Classifications MeSH