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Science of translational science research platform
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README.md
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README.md

Science of Translational Science Research Platform

Problem statement

Finding resources of translational relevancy across the CTSA program. This platform aims to reveal and connect expertise, services, educational resources, datasets, software tools, and other translational artifacts.

Project description

Organizations expend substantial effort maintaining local databases of effectively the same data - people, publications, grants, etc. and the challenge of scholar disambiguation and longitudinal data collection and tracking remains unsolved. The Science of translational science platform performs large-scale data integration from a large variety of sources using both structured and unstructured information. These data elements are indexed using semantic technologies for querying and discovery. A user interface will allow querying and exploration. Finally, widgets will be built to deliver context-specific content to CTSA hubs, CLIC Forums, the Compeititions review software, etc.

A shared data environment in the form of a warehouse of research data was strongly endorsed by participants in the most recent PEA Community meeting. Collaborative population and maintenance of common data would reduce local hub effort, improve data quality, and serve as an exemplar of collaborative activity for the CTSA program and NIH programs overall. Substantial effort has been spent on this topic by hubs establishing priorities and developing manual and semi-automated processes which can help to guide efforts toward automation.

The 4DM Project (Drug Discovery, Development and Deployment Map) created by NCATS has generated substantial interest in understanding the interdependencies of translational research and the entities involved. The 4DM prototype will be extended to incorporate relevant backing data from the data warehouse to display when selecting a vertex in the visualization graph. Ultimately, we can leverage these data for a variety of purposes at hubs, including workflows for improved data quality, process efficiency, automation, benchmarking, etc.

We will use the Science of Translational Science Platform to demonstrate addressing the common CTSA need of longitudinal scholar data tracking and reporting.

Alignment to program objectives

TODO see here

Contact person

We require a contact person for each project for administrative purposes. Each project should also have a CD2H Program director assigned.

Point person (github handle) Site Program Director
David Eichmann (@eichmann) Iowa Melissa Haendel (@mellybelly)

Leads

Project scientific leadership, should be 1-3 persons.

Lead(s) (github handle) Site
David Eichmann (@eichmann) Iowa

Team members

See team.md file.

Repositories

TO DO

Deliverables

We expect at 6 months to complete a landscape analysis of data, tools, and workflows and establish an operational warehouse with a core set of common data and multiple hubs in active use. We will engage in active requirements gathering with the community and with NCATS, as well as leverage the personas to help ensure better UX overall. We will develop a disambiguation environment available to the community and in use by multiple CTSA hubs and two 4DM prototypes: one wrapping CTSAsearch services, and one mapping 4DM-style user interfaces onto CTSAsearch.

Get involved

TO DO

Working documents

TO DO

Documentation may be natively in GitHub using the wiki or .md files in the appropriate folder, or in Google Drive. Documentating projects in Github

The project Google drive folder is accessible to onboarded participants.

Slack room

The project slack room is accessible to onboarded participants. You will not automatically be added to Slack, please join via the link above. Once there, add the scits-platform channel.

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