Academic IT support for Data Science
Citation
Price, S, 2016, ‘Academic IT support for Data Science’. in: Yiannis Salmatzidis (eds) EUNIS 2016 Proceedings: European University Information Systems 22nd Annual Congress. Aristotle University of Thessaloniki, Greece, Thessaloniki, pp. 283-285
Abstract
Globally, over 500 universities now offer data science courses at undergraduate or postgraduate level and, in research-intensive universities, these courses are typically underpinned by academic research in statistics, machine learning and computer science departments and, increasingly, in multidisciplinary data science institutes. Much has been written about the academic challenges of data science from the perspective of its core academic disciplines and from its application domains, ranging from sciences and engineering through to arts and humanities. However, relatively little has been written about the institutional information technology (IT) support challenges entailed by this rapid growth in data science. This paper sets out some of these IT challenges and examines competing support strategies, service design and financial models through the lens of academic IT support services.
Full details in the University publications repository