Orr, Scott Allan;
(2022)
Heritage Data Science.
In: Fouseki, Kalliopi and Cassar, May and Dreyfuss, Guillaume and Ang, Kelvin and Eng, Kah, (eds.)
Handbook on Sustainable Heritage.
(pp. 484-496).
Routledge: London, UK.
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Abstract
The so-called data revolution is rapidly transforming society, including the heritage sector. Building on the more-established area of heritage science, a framework for heritage data science is proposed as a transdisciplinary field that employs data-driven approaches with critical reasoning within the heritage domain, in awareness of its unique and pressing challenges, to inform engagement with heritage and its interpretation and long-term management. Several open challenges within the field are discussed, including data quality and integrity, transdisciplinary, and education.
| Type: | Book chapter |
|---|---|
| Title: | Heritage Data Science |
| ISBN-13: | 9781003038955 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.4324/9781003038955 |
| Publisher version: | https://doi.org/10.4324/9781003038955 |
| 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. |
| UCL classification: | UCL 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/10129189 |
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