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The Role of Heritage Data Science in Digital Heritage

Albuerne, A; Grau-Bove, J; Strlic, M; (2018) The Role of Heritage Data Science in Digital Heritage. In: Ioannides, M and Fink, E and Brumana, R and Patias, P and Doulamis, A and Martins, J and Wallace, M, (eds.) Digital Heritage - Progress in Cultural Heritage: Documentation, Preservation and Protection. EuroMed Proceedings, Part I. (pp. pp. 616-622). Springer: Cham, Switzerland. Green open access

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Abstract

The advance of all forms of digital and virtual heritage alongside numerous heritage science and management applications have led to the generation of growing amounts of heritage data. This data is increasingly rich, diverse and powerful. To get the most out of heritage data, there is an evident need to effectively understand, manage and exploit it in a way that is sensitive towards its context, responding to its singularities, and that can allow heritage to keep up with global changes regarding expansion of digital technologies and the increasing role of data in decision making and policy development. Through conversations with industry and academia, as well as through their personal research in the field of cultural heritage, the authors have identified a need for enhanced training for data scientists to prepare them for working in the heritage sector. This paper first proposes a definition of the term heritage data, so far missing from the literature, and then presents the academic rationale behind the identified need for targeted training in data science for cultural heritage.

Type: Proceedings paper
Title: The Role of Heritage Data Science in Digital Heritage
Event: EuroMed 2018, 7th International Conference, 29 October - 3 November 2018, Nicosia, Cyprus
Location: Cyprus
Dates: 28 October 2018 - 03 November 2018
ISBN-13: 9783030017613
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/978-3-030-01762-0_54
Publisher version: https://doi.org/10.1007/978-3-030-01762-0_54
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Heritage Data, Data Science, Cultural Heritage
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Bartlett School Env, Energy and Resources
URI: https://discovery.ucl.ac.uk/id/eprint/10059570
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