[GitHub repo]({{ site.gh-repo }}) | This is a fork of Démonstrateur Sparnatural des Archives nationales de France | Original GitHub repo | SPARQL endpoint to use: http://51.159.140.210/graphdb/repositories/sparnatural-demo-anf | Our fork of draw.io
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The Archives of Ontario, the GLAM Incubator and Profs. Anastasia Kuzminykh and Shion Guha at the University of Toronto will collaborate to create a proof of concept that explores the possibilities and potential benefits of a graph-based data model for archival description, using the International Council on Archives’ new Records in Contexts (RiC) standard and Linked Open Data (RDF data format). The traditional archival finding aid, with its static and inflexible hierarchies, fails to represent the complexity and nuanced reality of record creation, accumulation, use and re-use over time.Recent efforts to overcome this limitation have turned to entity-relationship based models developed by the graph theory of knowledge representation, with its infinitely flexible and extensible subject-predicate-object expressions of data (semantic triples). The overall objective of this project is to develop a data model, to select and model a small-scale sample of data drawn from the Archives of Ontario’s datasets, and to thereby test the possibilities and potential benefits for internal staff and public end-users. This work represents a paradigm shift for archival description: it promises a vastly improved ability to represent the reality of record creation, to manage the complexity of digital metadata, to allow machine-readable encoding of meaning that enables complex logical inferences and search capabilities, and to connect currently siloed datasets with related data across the world. In short, this proposed project will break new ground in the Canadian archival sector.
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Live demo | JavaScript library for executing SPARQL query and transforming resulted JSON for visualization in D3.js. | GitHub repo