Journal:FAIR and interactive data graphics from a scientific knowledge graph
| Full article title | FAIR and interactive data graphics from a scientific knowledge graph |
|---|---|
| Journal | Scientific Data |
| Author(s) | Deagen, Michael E.; McCusker, Jamie P.; Fateye, Tolulomo; Stouffer, Samuel; Brinson, L. Cate; McGuinness, Deborah L.; Schadler, Linda S. |
| Author affiliation(s) | University of Vermont, Rensselaer Polytechnic Institute, Duke University |
| Primary contact | Email: mdeagen at mit dot edu |
| Year published | 2022 |
| Volume and issue | 9 |
| Article # | 239 |
| DOI | 10.1038/s41597-022-01352-z |
| ISSN | 2052-4463 |
| Distribution license | Creative Commons Attribution 4.0 International |
| Website | https://www.nature.com/articles/s41597-022-01352-z |
| Download | https://www.nature.com/articles/s41597-022-01352-z.pdf (PDF) |
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This article should be considered a work in progress and incomplete. Consider this article incomplete until this notice is removed. |
Abstract
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 (e.g., 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 uniform resource identifiers (URIs) 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.
Keywords: FAIR, graph database, knowledge graph, materials science, research management
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This presentation is faithful to the original, with only a few minor changes to presentation, though grammar and word usage was substantially updated for improved readability. In some cases important information was missing from the references, and that information was added.
