Toward cultural significance awareness in HIS: a data model approach

Abstract

PurposeThe purpose of this paper is to address the challenging issue of developing a quantitative approach for the representation of cultural significance data in heritage information systems (HIS). The authors propose to provide experts in the field with a dedicated framework to structure and integrate targeted data about historical objects' significance in such environments.Design/methodology/approachThis research seeks the identification of key indicators which allow to better inform decision-makers about cultural significance. Identified concepts are formalized in a data structure through conceptual data modeling, taking advantage on unified modeling language (HIS). The design science research (DSR) method is implemented to facilitate the development of the data model.FindingsThis paper proposes a practical solution for the formalization of data related to the significance of objects in HIS. The authors end up with a data model which enables multiple knowledge representations through data analysis and information retrieval.Originality/valueThe framework proposed in this article supports a more sustainable vision of heritage preservation as the framework enhances the involvement of all stakeholders in the conservation and management of historical sites. The data model supports explicit communications of the significance of historical objects and strengthens the synergy between the stakeholders involved in different phases of the conservation process.

Digital representation strategies to reveal the cultural significance of Canadian Post-war Architecture

“…The latter is particularly challenging as Cultural values are not necessarily positive, "not intrinsic; mutable, not static; multiple and often incommensurable or in conflict" [20] as they depend on the observed object, the observing subject and the context of their interaction [21]. As indicated in previous research [22], communicating such knowledge requires the adoption of a dedicated taxonomy to contextualize and enable multiple representations of the collected data.…”