A substrate for modular, extensible data-visualization


As the scope of scientific questions increase and datasets grow larger, the visualization of relevant information correspondingly becomes more difficult and complex. Sharing visualizations amongst collaborators and with the public can be especially onerous, as it is challenging to reconcile software dependencies, data formats, and specific user needs in an easily accessible package. We present substrate, a data-visualization framework designed to simplify communication and code reuse across diverse research teams. Our platform provides a simple, powerful, browser-based interface for scientists to rapidly build effective three-dimensional scenes and visualizations. We aim to reduce the limitations of existing systems, which commonly prescribe a limited set of high-level components, that are rarely optimized for arbitrarily large data visualization or for custom data types. To further engage the broader scientific community and enable seamless integration with existing scientific workflows, we also present pytri, a Python library that bridges the use of substrate with the ubiquitous scientific computing platform, Jupyter. Our intention is to lower the activation energy required to transition between exploratory data analysis, data visualization, and publication-quality interactive scenes.


@articleMatelsky_2020 doi: 10.1186/s41044-019-0043-6 url: https://doi.org/10.1186/s41044-019-0043-6 year: 2020 month: feb publisher: Springer Science and Business Media LLC volume: 5 number: 1 author: Matelsky Jordan K. and Downs Joseph and Cowley Hannah P. and Wester Brock and Gray-Roncal William title: A substrate for modular extensible data-visualization journal: Big Data Analytics

Contact Us

Ashley Llorens

Physical Address
7701 Montpelier Road
Laurel, MD 20723

The Intelligent Systems Center is located at the Montpelier Campus of the Johns Hopkins Applied Physics Laboratory.
Click here for a map, directions and other visitor information.