The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (Jun 2022)

MINOR HISTORICAL CENTRES ONTOLOGY ENRICHMENT AND POPULATION: AN HAMLET CASE STUDY

  • E. Colucci,
  • A. M. Lingua,
  • M. Kokla,
  • A. Spanò

DOI
https://doi.org/10.5194/isprs-archives-XLIII-B4-2022-31-2022
Journal volume & issue
Vol. XLIII-B4-2022
pp. 31 – 37

Abstract

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The main topic of this work focuses on the semantic, historical and spatial documentation of Minor Historical Centres (MHC) with a focus on (semi-abandoned alpine) hamlets. The key point is the possibility to standardise spatial information in the domain of MHC and their related cultural, architectural, built and landscape heritage. This work analyses the notions of historical centre and ancient area, which took different meanings and evolved over the centuries. MHC are historical part of cities, villages and hamlets (urban, rural, minor or abandoned) with cultural, social and economic values. Thus, MHC need to be preserved, documented and safeguarded. The spatial and semantic documentation is a fundamental tool for increasing their knowledge. In these places, many actors and stakeholders are involved in different activities, and for this reason, they need to share common knowledge and use a unique language. In this regard, spatial ontology is of relevant interest and usability. Ontologies are conceptual structures that formalise specific knowledge and create a unique and standard thesaurus that ensures semantic interoperability. This paper is part of a PhD research targeted at developing an ontology containing helpful information to manage, share and collect data on MHC due to the lack of an interoperable structure to formalise such knowledge. The main aim is to populate and enrich the already developed ontological structure with data of a mountain semi-abandoned hamlet: Pomieri. The methodological workflow is validated, enriching and populating the ontology, adding classes and instances with information and unstructured data of a real data case study.