• Research Category Research & Development Services & Subcontracts
• Solicitation Number S23-093
• NCI OA Contract Number 75N91019D00024 – NCI-FFRDC

Description

Today, many data science efforts seek to leverage established technologies and operationalize data infrastructure platforms to meet the Findable, Accessible, Interoperable and Reusable (FAIR) data principles. While established technologies can be engineered to accept data from more researchers, improve dashboards, and refine search capabilities, these technologies fail to improve the quality, standardization, and timeliness of data availability for data collected across thousands of labs and health care institutions. Experimental efforts often fail to collect the fidelity of data provenance, calibration information, experimental protocol information, and context needed to reliably test for experimental reproducibility. Furthermore, established technologies are limited in their ability to integrate data from multiple sources and support intuitive multi-source exploration or data analysis (including through Artificial Intelligence/Machine Learning (AI/ML)). Critical biomedical data usage by appropriate stakeholders can be impeded by access limitations, a lack of interoperability across hundreds of siloed data platforms, and a lack of robust, reusable methods to protect data privacy and security. At its crux, these limitations make it difficult to leverage data from thousands of labs, health care institutions, and research centers because each entity tends to manage data using incompatible biomedical dialects.

The RFP seeks to revolutionize data integration and usability approaches by making it easier to connect biomedical research data from thousands of sources and overcome barriers caused by incompatible data dialects. The BDF Toolbox project will advance data fabric capabilities to address the challenges around data integration, data usability, and incompatible biomedical dialects. Areas of technical emphasis include:

• Automated data collection to lower barriers to high-fidelity, timely access to computationally ready research data across labs and health record systems.
• AI-assisted curation to prepare, connect, and harmonize multi-source data for analysis at scale.
• Intuitive exploration to enable advanced, intuitive, human-centered data exploration and dashboards for use by diverse stakeholders and decision-makers across disciplines and health literacy levels.
• User testing to evaluate data fabric tools across diverse users – including researchers, clinicians, and patients - to create tools that will be enthusiastically adopted.

Objectives to be achieved include but are not limited to the following:

• Lowering the barriers to data collection,
• Providing reusable approaches to support multi-source data preparation for analysis at scale,
• Providing intuitive dashboards for data exploration usable by diverse users in the cancer community,
• Facilitating evaluation of data usability by diverse stakeholders in the cancer community.

Proposal Instructions

To be considered for award, offers must be received at the location specified above by CLOSE OF BUSINESS (COB) ON 14 NOVEMBER 2023. Offers must be clearly identified with the Solicitation/RFP Number listed above. Award(s) are intended to be either Cost Reimbursable or Time and Material type. For the full solicitation package, please reach out to Josh Wynne and/or Connor Cigrang (josh.wynne@nih.gov / connor.cigrang@nih.gov).