INsight to Diverse Information using Graphs and Ontologies (INDIGO) will allow multiple stakeholders across program roles and engineering disciplines to easily find and visualize information represented in different modeling languages and formats, manipulated with different tools and environments, stored in multiple repositories, and distributed across multiple organizations. By combining description logic reasoning, subgraph pattern matching, and distributed ontology technologies, INDIGO will pull information from these disparate sources and present it in the context of the stakeholder that requested it and in a form that supports the activities they are responsible for performing. INDIGO will provide transformative new capabilities to support multi-disciplinary collaboration and multi-model visualization. INDIGO will deal with very large amounts of modeling data and associated information (such as analysis results) spread across multiple repositories. INDIGO will benefit stakeholders by helping them with understanding, verifying, and validating this information to support their respective efforts in the system development. Phase I established the feasibility of INDIGO and identified an initial transition path. The Phase II objectives are to 1) provide a set of functional capabilities to users; 2) meet quality attribute goals, and 3) mature INDIGO to TRL 6 by the end of Phase II.
Large international NASA programs such as Gateway and Artemis require collaboration between many diverse stakeholders, including subsystem vendors, integrators, and operators. These will face the model interoperability and data aggregation challenges addressed by INDIGO. Specifically, Phase II will integrate with NASA OpenMBEE, an open-source initiative that involves several NASA and commercial projects and users. INDIGO progress will be presented at NASA working groups to increase visibility.
The non-NASA markets are those with systems that are analogous to those in the NASA market, mission-critical cyber physical systems with significant functionality captured in software. The most near-term is the collection of Army efforts that comprise the Future Vertical Lift modernization priority and others implementing the DoD’s digital engineering strategy.