Research
The Center for Translational Data Science at the University of Chicago is leading the datasharing intatives through data commons, data ecosystems, and energizing research with tools to integrate and analyze research data at scale. Many of current research activities are focused in the following areas:
Create and manage frictionless data meshes that are easy for researchers to use; for developers to develop code for; and for operators to set up, configure and operate.
Expand support for non-graphical data models (e.g. OMOP and FHIR)
Automate data ingestion and partly automate data curation
Provide more visualization options for simplifying data exploration
Enable research progress in specific topic areas including the relationship between viruses & disease and cancer omics.
Create new tools for applying machine learning and artificial intelligence approaches to data housed in data commons and data meshes. This includes applying AI/ML to images, data labeling, improving search, and knowledge extraction.
Develop Digital Twin simulations for cells and tissues.
DATA COMMONS
JCOIN - Justice Community Opioid Innovation Network
This project deploys bi-directional data sharing, analytics and modeling capacities to provide new scientific insights into interventions at the intersection of opioid use and justice contexts that will ultimately lead to reductions in opioid overdose. These capabilities include using advanced methods that provide best-in-class data storage, management and security with added value to these trials through products of forecasting, rapid real time assessments, explication and exploration of trial findings and cost-effectiveness analysis.
https://jcoin.datacommons.io/
Visit pubmed to see JCOIN articles published by researchers at the University of Chicago
IBD
The IBD Data Commons permits rapid, secure sharing of data as well as the ability to compute over those data in the cloud and establish reproducible QC and analytic pipelines.
https://ibdgc.datacommons.io
Visit pubmed to see IBDGC articles published by researchers at the University of Chicago
Clinical Trials
The Clinical Trial Data Commons (CTDC) further expands access to clinical trial data that are advancing our understanding of the relationship between tumor molecular characterization, treatment, response and progression. The CTDC aggregates data from multiple precision medicine studies that tailor treatment to the specific tumor in an individual patient.
The data in the CTDC is structured and queryable using the CTDC data model and data dictionary. Submitted data are processed and then harmonized to maintain data and metadata consistency, integrity and availability to the CTDC users and the rest of the Cancer Research Data Commons.
accessclinicaldata.niaid.nih.gov
Visit pubmed to see CTDC articles published by researchers at the University of Chicago
HEAL
The Helping to End Addiction Long-term Initiative, or NIH HEAL Iniative, is an aggressive, trans-agency effort to speed scientific solutions to stem the national opiod public health crisis. Almost every NIH Institute and Center is accelerating research to address this public health emergency from all angles.
WEBSITE -Still under development
Visit pubmed to see HEAL-initative articles published by researchers at the University of Chicago
The PCDC works with international leaders in pediatric cancers and the National Cancer Institute to develop and apply uniform data standards that facilitate the collection, combination, and analysis of data from many different sources. By harmonizing existing clinical research data and leading international efforts to standardize data collection, we are breaking down long-standing barriers that have held back advancements in research on rare diseases.
https://commons.cri.uchicago.edu
Visit pubmed to see PCDC articles published by researchers at the University of Chicago
Kids First
The goal of the NIH Gabriella Miller Kids First Pediatric Research Program (Kids First) is to help researchers uncover new insights into the biology of childhood cancer and structural birth defects, including the discovery of shared genetic pathways between these disorders. Kid First uses Gen3’s Data Commons Framework Services.
https://data.kidsfirstdrc.org/
Visit pubmed to see Kids First articles published by researchers at the University of Chicago
BloodPAC
The BloodPAC Data Commons (BPDC) is the leading repository for liquid biopsy data and serves to accelerate the process of scientific discovery, especially over large or complex datasets, standardize data submission to develop common approaches for data harmonization and to provide the infrastructure and necessary frameworks to do analysis securely in place
The Commons serves as a source of valid scientific evidence to support submissions to regulatory agencies, supply data for agencies and organizations making decisions about reimbursement and provide a rich data source for researchers.
https://www.bloodpac.org/data-commons
Visit pubmed to see BloodPac articles published by researchers at the University of Chicago
VADC (Veterans Affairs Data Commons)
The VADC provides researchers access to relevant de-identified VA data for medical research purposes. The VADC is streamlined to host research data and a co-localized database that serves as a foundation for future expanded data access, computational capabilities, and cloud-based bioinformatics research. The VADC is built on the University of Chicago, Center for Translational Data Science (CTDS) developed Gen3 open source architecture and is a cloud-based software platform for managing, analyzing, synchronizing and sharing datasets.
https://va.data-commons.org/
Visit pubmed to see VADC articles published by researchers at the University of Chicago
AnVIL
The NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-Space, or AnVIL, provides an updated model for genomic data sharing, providing a cloud environment for the analysis of large genomic and related datasets.
By providing a unified environment for data management and compute, AnVIL eliminates the need for data movement, allows for active threat detection and monitoring, and provides elastic, shared computing resources that can be acquired by researchers as needed.
The platform provides a compute environment with secure data and analysis sharing capabilities alongside standards based sharing of containerized tools and workflows. The Gen3 data commons framework provides data and metadata ingest, querying, and organization.
https://gen3.theanvil.io/
Visit pubmed to see AnVIL articles published by researchers at the University of Chicago
