Publication type: Conference paper
Type of review: Peer review (publication)
Title: Applied data science in Europe : challenges for academia in keeping up with a highly demanded topic
Authors: Stadelmann, Thilo
Stockinger, Kurt
Braschler, Martin
Cieliebak, Mark
Baudinot, Gerold
Dürr, Oliver
Ruckstuhl, Andreas
Proceedings: Proceedings of the 9th European Computer Science Summit
Conference details: 9th European Computer Science Summit, Amsterdam, Niederlande, 8-9 October 2013
Issue Date: 2013
Language: English
Subjects: Data science; INIT; Multi-disciplinary; Fintech
Subject (DDC): 004: Computer science
020: Library and information sciences
Abstract: Google Trends and other IT fever charts rate Data Science among the most rapidly emerging and promising fields that expand around computer science. Although Data Science draws on content from established fields like artificial intelligence, statistics, databases, visualization and many more, industry is demanding for trained data scientists that no one seems able to deliver. This is due to the pace at which the field has expanded and the corresponding lack of curricula; the unique skill set, which is inherently multi-disciplinary; and the translation work (from the US web economy to other ecosystems) necessary to realize the recognized world-wide potential of applying analytics to all sorts of data. In this contribution we draw from our experiences in establishing an inter-disciplinary Data Science lab in order to highlight the challenges and potential remedies for Data Science in Europe. We discuss our role as academia in the light of the potential societal/economic impact as well as the challenges in organizational leadership tied to such inter-disciplinary work.
Fulltext version: Published version
License (according to publishing contract): Licence according to publishing contract
Departement: School of Engineering
Organisational Unit: Institute of Applied Information Technology (InIT)
Appears in collections:Publikationen School of Engineering

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