The Role of Heritage Data Science in Digital Heritage

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.

The Matrix: connecting and re-using digital records and archives of archaeological investigations

“…Rather than just depositing more archived data, the need is to better characterise the indexing of subject matter (meta)data for what has been loosely termed 'heritage data' through good RDM. It follows that to enable a better understanding of how different types of heritage data could be reused, it is necessary to better understand the nature and character of what is meant by the much vaunted phrase 'heritage data'(Albuerne et al 2018). Such 'heritage data characterisation' should enable researchers to better qualify, and ideally quantify, what research questions have, or have not, been addressed.…”