Cancer Data Science Pulse

Data Commons
Illustration shows how different puzzle pieces come together to create a picture of a bridge. This offers an analogy for how different datasets come together through harmonization. Distributed data are aggravated and then integrated. This process allows individual data with different conceptual frameworks to be joined together (through large-scale indexing frameworks and consistent identifiers) to identify gaps and to allow for better analysis, both by humans and machines.

Cancer Data Harmonization—Setting Standards and Breaking Down Silos

Pooling data from numerous sources strengthens the power of the information, but only if it can be meaningfully connected. Dr. Melissa Haendel, Director of the Translational and Integrative Sciences Laboratory, Oregon State University (OSU), and Principal Investigator for the NCI Center for Cancer Data Harmonization, and Julie McMurry, Associate Director of the Translational and Integrative Sciences Laboratory, OSU, describe the basics of harmonization and how it can help in wrangling massive amounts of data to make them more valuable to research.

The NCI Cancer Research Data Commons (CRDC) provides biomedical researchers, tool developers, and data scientists with access to data from NCI programs through the nodes like the Proteomics Data Commons. The CRDC allows users to analyze, share, and store results, and is growing to include a wider range of data, including proteomics, imaging, and canine.

Proteomic Data Commons (PDC)—A Resource for Probing Today’s Cancer Questions

NCI’s Dr. Erika Kim and Dr. Chris Kinsinger discuss how the Proteomic Data Commons (PDC) aids cancer researchers in accessing and analyzing proteomic data. The PDC is an integral part of NCI’s Cancer Research Data Commons (CRDC) as it gives researchers access to three types of proteomic data: mass spectra, identified peptides, and protein reports, as well as clinical, biospecimen, and other metadata. The PDC is available for queries and analysis of publicly accessible datasets.

The NCI Cancer Research Data Commons (CRDC) provides biomedical researchers, tool developers, and data scientists with access to data from NCI programs through the Genomic Data Commons, NCI Cloud Resources, and Proteomics Data Commons. The CRDC allows users to analyze, share, and store results, and is growing to include a wider range of data, including proteomics, imaging, and canine.

Award of the Imaging Data Commons: Bringing Multi-modal Imaging Data to the Cancer Research Community

The Imaging Data Commons (IDC) has been awarded to a consortium led by investigators from the Department of Radiology at Brigham and Women’s Hospital and Harvard Medical School. The IDC will house multi-modal imaging data and make them available for use by the broader cancer research community.

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Toward FAIR&R Cancer Data Analysis

In an era of unprecedented growth in the size and variety of datasets and the number of software tools, there is an ever-increasing need for frameworks that connect and integrate data and tools within a secure and easy-to-use research ecosystem.

Stephen D. Jett, Ph.D.

Announcing the Release of the Imaging Data Commons Request for Proposals

NCI is initiating the development of an Imaging Data Commons (IDC) supported by funding provided through the Cancer MoonshotSM. Imaging plays a pivotal role in studying cancer, from diagnosis to fundamental research. Like the NCI Genomic Data Commons (GDC) and Proteomic Data Commons (PDC), the IDC will be a data node, a domain-specific repository, in the CRDC.

Gen3 Data Commons DCF Sandbox. DCF Sandbox: Explore, Analyze and Share Research Data. The Data Commons Framework (DCF) supports the management, analysis and sharing of many different types of biomedical data for the research community with the goal of accelerating research in the molecular basis for disease and matching targeted therapies that factor in each patient's unique biology. Prompt display to Login from Google. If you have questions about access or the registration process, please contact support@d

Introducing the Data Commons Framework

For this interview, the Center for Biomedical Informatics and Information Technology Communications Team interviewed Dr. Robert L. Grossman of the University of Chicago Center for Data Intensive Science to discuss the Data Commons Framework, a component of the NCI Cancer Research Data Commons.

FAIR Principles: Findable, Accessible, Interoperable, Reusable

We Face a New "Tragedy of the Commons." The Remedy is Better Metadata.

The data science community is awash with "FAIRness." In the past few years, there has been an emerging consensus that scientific data should be archived in open repositories, and that the data should be Findable, Accessible, Interoperable, and Reusable.

Data Commons Figure 08-09-2017

Towards a Cancer Research Data Commons

I recently joined NCI to help support strategic data sharing and informatics projects within the Center for Biomedical Informatics and Information Technology (CBIIT). Having worked on information management at another Institute for five years and the trans-NIH Big Data to Knowledge (BD2K) initiative since its inception, this is an exciting opportunity for me to continue to contribute to enhancing data science across the biomedical community.

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