# Data Science Resource > **NIH NIH U2C** · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · 2022 · $234,135 ## Abstract DATA SCIENCE RESOURCE SUMMARY The HHEAR Data Science Resource (DSR) will accelerate research in environmental health sciences by creating a community-vetted HHEAR ontology that is used to power the HHEAR data portal, and more broadly to facilitate connections between a wide range of environmental health data. The DSR provides ontology expertise, ontology identification and mapping criteria, community outreach and engagement, and overall semantic guidance to support the HHEAR Data Center's data portal that provides findable, accessible, interoperable, and reusable exposure and health data. The DSR focuses on interoperable terminology connecting to and leveraging best-in-class vocabularies, including the evolution of our current CHEAR ontology into an HHEAR ontology as needed for the broader scope and new study support. Indeed, our experiences in building the CHEAR ontology inform and guide our plans for HHEAR. We also aim to actively lead and continue to build an exposome and health community striving toward best practice data and metadata vocabularies and standards, with reuse and link as appropriate. The resource contributes semantic leadership, processes, tools, and semantic design and infrastructure evolution consulting to support finding, prioritizing, analysis for gaps/coverage, and effectively using appropriate vocabulary and use cases. Guided by experts in data science, bioinformatics, and domains, we will actively co-lead and participate in community working group(s) with the aim of creating open-source, community-driven annotated collections of data and metadata standards. Ultimately, these goals have the potential to provide a community-driven and community-accepted language for exposure science. Further, the methodologies are being designed with a goal of living beyond this program, providing guidance for future participants and communities. The ontology and the process facilitates the goals of the HHEAR Program in expediting progress in exposome-related research, analyses, and collaborations, most notably by having unambiguous use of terminology and processes for updates. The DSR's specific aims are to provide the program-wide HHEAR ontology along with criteria for evaluating and cataloging relevant standards. We will co-lead community engagement and outreach, and support the DRMC in ontology usage of the Data Center's robust data harmonization and access portal. Leveraging our existing infrastructure and expertise will overcome the need for a long implementation process fraught with challenges—we have already encountered and overcome many such challenges in implementing the CHEAR DC, and will be able to flexibly respond to the needs of the HHEAR Network. ## Key facts - **NIH application ID:** 10424419 - **Project number:** 5U2CES026555-05 - **Recipient organization:** ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI - **Principal Investigator:** Deborah L McGuinness - **Activity code:** U2C (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2022 - **Award amount:** $234,135 - **Award type:** 5 - **Project period:** 2015-09-30 → 2024-05-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10424419 ## Citation > US National Institutes of Health, RePORTER application 10424419, Data Science Resource (5U2CES026555-05). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10424419. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*