# Core-001

> **NIH NIH UL1** · UNIVERSITY OF CINCINNATI · 2020 · $581,484

## Abstract

The ability to generate, share, and analyze data is fundamental to the operation of the Center for Clinical and
Translational Science and Training (CCTST) and participation in wider CTSA networks. Effective fulfillment of
these principles requires robust data infrastructure and well-formulated policies and procedures, but more
importantly, the development of a highly participatory, informatics- and data-literate research community that
embraces best practices alongside innovation. We believe that fulfillment of these data-centric objectives will
allow greater discovery, inference, understanding, and translation of knowledge for improved health and
wellness. To achieve these objectives, we will focus on the development and implementation of disciplinebased
local learning systems to improve data aggregation, data utilization, and informatics literacy, with a
focus on our own health care systems [University of Cincinnati (UC) Health and Cincinnati Children’s Hospital
Medical Center]. We expect to identify, aggregate, uniformly represent, and make interoperable health care
data from a variety of basic and translational science realms, clinical systems, and community sources. We
also expect to broadly provide the means for all Cincinnati stakeholders to more effectively access and utilize
these biomedical data, and to widely disseminate knowledge derived from such data that is relevant to
improving health and health care. Finally, we expect to maximally increase literacy for understanding and using
informatics approaches for all Cincinnati stakeholders, to enable our workforce and community to best utilize
data for improving health and health care. The resulting programs will be accessible across our spectrum of
stakeholders, and their products will be available to all community and CTSA participants. These programs will
leverage existing data, technology, and people, and the programs will logically organize and build upon these
components to synergistically and continually identify new data, analysis, and technology needs, and to cocreate
new informatics solutions for our health care research concentrations. We will be building on our past
accomplishments to strengthen this construct and address the challenges of efficient, universal access to
biomedical data for knowledge engineering and application.

## Key facts

- **NIH application ID:** 10123708
- **Project number:** 2UL1TR001425-05A1
- **Recipient organization:** UNIVERSITY OF CINCINNATI
- **Principal Investigator:** JAMES E. HEUBI
- **Activity code:** UL1 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $581,484
- **Award type:** 2
- **Project period:** — → —

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10123708

## Citation

> US National Institutes of Health, RePORTER application 10123708, Core-001 (2UL1TR001425-05A1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10123708. Licensed CC0.

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