Techne

Ana Tam profile

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Ana Tam

University of the Arts London (2018 )
ana@anatam.co.uk

Thesis

Applying Graph Theory to Conservation Documentation

About

To manage and preserve our valued heritage objects and places, the conservation process requires the creation and use of a wide variety of records and documentation. This documentation in of itself is an invaluable resource for scholarship. However, a disproportionately large amount of conservation information published on websites and traditional databases are not accessible via searching or through machinereadable means. Inaccessible information is a two-fold problem using up resources at point of data entry andagain when a researcher seeks to retrieve it. Tackling this problem requires transitioning traditionalinformation systems to become compatible with the latest data standards and in the case of cultural heritage,this standard is known as the CIDOC CRM. This research will look into the use of graph theory and graph databases to achieve this. Graph theory is an area of mathematics that studies the interconnectedness of things. Graphs, in this sense, are made up of nodes and edges where the node is a piece of data and theedge is the relationship between two nodes. This diagrammatic model has also been called a Spider Map or Knowledge Map and serves as the fundamental basis for graph databases. Mapping information using graphs is a recognised standard for presenting information on the Semantic Web and is used by bioinformaticians to encode and model life science data. A graph-based, knowledge map approach will allow conservation professionals to visualise and understand existing levels of knowledge, where knowledge gapslie, how information is related to each other and what constitutes baseline context. It has the potential to aidthe identification of new areas of knowledge and can play a significant role in resource management anddecision-making. This research will contribute towards the further transmission of conservation information and begin to tackle the access and retrieval problem.