Announcing the 2023 DataWorks! Prize Winners

In early 2023, ODSS partnered with the Federation of American Societies for Experimental Biology (FASEB) to launch the second annual DataWorks! Prize to highlight examples of innovative data sharing and reuse.

This year, 39 teams registered for the challenge to demonstrate their accomplishments. The 218 team members came from a wide variety of disciplines, including biochemistry, clinical research, genomics, immunology, molecular biology, neuroscience, and more.

Representatives from the grand prize-winning team will present at the Data Sharing and Reuse Seminar series on Friday, Feb. 9, 2024.

Grand Prize $100,000

CCC19

COVID-19 and Cancer: Catalyzing Collaboration

The COVID-19 and Cancer Consortium (CCC19) is a collaboration that collects data about patients with cancer who have been diagnosed with COVID-19.

Distinguished Achievement Award $50,000

IPop CATS

GeoPIPE: Reusing Open Data and Letting Data Flow

GeoPipe is pipeline for enriching open data streams with geospatial analyses and natural language processing.

 

Maryellen Giger’s Team

Sharable Curated, Diverse Medical Images at Scale

MIDRC is a collaboration to create an open curated, diverse commons for medical imaging AI research and a sequestered one for translation.

Exemplary Achievement Award $25,000

ASAP Discovery Consortium

An Open Pipeline for Antiviral Drug Discovery

To nucleate a global antiviral pipeline to prevent future pandemics, we created a new model for open science accelerated drug discovery.

 

Karen Yook’s Team

Making Data Useable While Publishing

microPublication Biology re-architects the publishing workflow by including curators to alleviate numerous obstacles in data reusability.

 

StrokeFAIR

StrokeFAIR: A Public Dataset and Analytical Tools

StrokeFAIR shares FAIR images, metadata, and analytical tools for acute brain stroke, democratizing avenues to perform reproducible reliable research.

Significant Achievement Award $12,500

Caltech Library

Naming Data Files Descriptively for Easier Reuse

A worksheet for creating file naming conventions to label research data descriptively and consistently.