Modelling Linked Data for Conservation : A Call for New Standards

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2022

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KULA : Knowledge Creation, Dissemination, and Preservation Studies ; vol. 6 no. 3 (2022)

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Erudit

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©, 2022RyanLieu, AlbertoCampagnolo




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Ryan Lieu et al., « Modelling Linked Data for Conservation : A Call for New Standards », KULA: Knowledge Creation, Dissemination, and Preservation Studies, ID : 10.18357/kula.232


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Conservation documentation serves an invaluable role in the history of cultural property, and conservators are bound by professional ethics to maintain accurate, clear, and permanent documentation about their work. Though many well-documented schemata exist for describing the holdings of memory organizations, none are designed to capture conservation documentation data in a semantically meaningful way. Conservation data often includes deeply detailed observations about the physical structure, materiality, and condition state of an object and how these characteristics change over time. When included with descriptive catalog metadata, these conservation data points typically manifest in seldom-used fields as free-text notes written with inconsistently applied standards and uncontrolled vocabularies. Beyond the traditional scope of descriptive metadata, conservation treatment documentation includes event-oriented data that captures a sequence of steps taken by the conservator, the addition and removal of material, and cause-and-effect relationships between observed conditions and treatment decisions made by a conservator. In 2020, the Linked Conservation Data Consortium conducted a pilot project to transform unstructured conservation data into linked data. Participants examined potential models in the library field and ultimately chose to conform to the Comité International pour la Documentation (CIDOC) Conceptual Reference Model (CRM) for its accommodation of event-oriented data and detailed descriptive attribution. Project technologists worked with real report data from four institutions to create XML data models and map newly structured data to the CRM. The pilot group then imported CRM-modelled datasets into a discovery environment, developed queries to reconcile the divergent datasets, and created knowledge maps and charts in response to a small set of predetermined research questions. Feedback from conservators attending workshop activities revealed a shared need for conservation data standards and guidelines for those developing documentation templates and databases. Project outcomes signalled the necessity of further developing conservation vocabularies and ontologies to link datasets between institutions and from adjacent domains.

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