New York University is responsible for overall coordination and management of the effort to develop and implement the platform. The NYU team is the primary agency contact.

Elsevier provides the information infrastructure—the curated corpus of documents such as publications and patents—that provides the basis on which to run the algorithm, optimizes the search space, applies the existing algorithms to search and discover specific datasets, and produces metadata to feed into the validation process and the API, dashboards, and Jupyter Notebooks.

IDIES ingests and processes the metadata output from the ML algorithms into a database that can be validated in the validation tool, then feeds the validated output to the API. IDIES developed the validation tool so that the agencies or their designated collaborators can validate the output. IDIES also developed SciServer, a collaborative, web-based science platform.

Texas Advanced Computing Center designed, developed, and is implementing the API to disseminate the validated metadata received from JHU. TACC also has enabled the front-end tool implementation by enabling the web connector for Tableau software for visualization in a dashboard. TACC will be developing a browser-based dashboard.

University of Maryland, College Park is developing a website that describes the methodology, approach, and relevant materials for the user community. They will jointly host one or more workshops for researchers to react to the findings and measurement.

University of Texas at San Antonio is validating the ML output for some agencies. They will also work to support ML model development and the researcher engagement at conferences. Their team will play an important role in analyzing and promoting the progress and success of the project.