FAIR and Interactive Data Graphics from a Scientific Knowledge Graph
Author
Deagen, Michael E.; McCusker, Jamie; Fateye, Tolulomo; Stouffer, Samuel; Brinson, L. Cate; McGuinness, Deborah L.; Schadler, Linda S.Other Contributors
Date Issued
2022-05Degree
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Attribution-NonCommercial-NoDerivs 3.0 United StatesFull Citation
Deagen, Michael E., Jamie P. McCusker, Tolulomo Fateye, Samuel Stouffer, L. Cate Brinson, Deborah L. McGuinness, and Linda S. Schadler. "FAIR and Interactive Data Graphics from a Scientific Knowledge Graph." Scientific Data 9, no.1, May 2022: 1-11.Metadata
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https://www.nature.com/articles/s41597-022-01352-z; https://doi.org/10.1038/s41597-022-01352-z; https://hdl.handle.net/20.500.13015/6436Abstract
Graph databases capture richly linked domain knowledge by integrating heterogeneous data and metadata into a unified representation. Here, we present the use of bespoke, interactive data graphics (bar charts, scatter plots, etc.) for visual exploration of a knowledge graph. By modeling a chart as a set of metadata that describes semantic context (SPARQL query) separately from visual context (Vega-Lite specification), we leverage the high-level, declarative nature of the SPARQL and Vega-Lite grammars to concisely specify web-based, interactive data graphics synchronized to a knowledge graph. Resources with dereferenceable URIs (uniform resource identifiers) can employ the hyperlink encoding channel or image marks in Vega-Lite to amplify the information content of a given data graphic, and published charts populate a browsable gallery of the database. We discuss design considerations that arise in relation to portability, persistence, and performance. Altogether, this pairing of SPARQL and Vega-Lite—demonstrated here in the domain of polymer nanocomposite materials science—offers an extensible approach to FAIR (findable, accessible, interoperable, reusable) scientific data visualization within a knowledge graph framework.;Department
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Nature Scientific DataRelationships
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