FAIR and interactive data graphics from a scientific knowledge graph

Figure 2. Interactive views of sample data, meta-analyses, and stylized infographics. Charts shown here are specified by a SPARQL query (semantic context) as well as Vega-Lite specification (visual context). The snapshots of interactive data graphics shown here display a) mechanical tensile testing data curated from Bandyopadhyay et al. (2005), transformed into a layered composite view; b) a Weibull plot of dielectric testing data using custom y-axis scaling and the regression transform to estimate dielectric breakdown strength (DBS); c) a meta-analysis of nanocomposite filler materials in curated research articles per year of publication, highlighted to show the trend for graphene; d a meta-analysis of entity-resolved compound names (computed by the ChemProps API) versus curator-provided strings; e) an infographic showing a dataset with increasingly interactive views; and f) an explanatory graphic for viscoelastic data. These examples created for the materials science domain represent a small subset of the variety of datasets and visualizations made possible by using SPARQL queries and Vega-Lite specifications to capture interactive views of content from a knowledge graph database.

Deagen, Michael E.; McCusker, Jamie P.; Fateye, Tolulomo; Stouffer, Samuel; Brinson, L. Cate; McGuinness, Deborah L.; Schadler, Linda S. (2022). "FAIR and interactive data graphics from a scientific knowledge graph". Scientific Data 9: 239. doi:10.1038/s41597-022-01352-z. 

2022

Deagen, Michael E.; McCusker, Jamie P.; Fateye, Tolulomo; Stouffer, Samuel; Brinson, L. Cate; McGuinness, Deborah L.; Schadler, Linda S.

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