Cancer Data Science Pulse

Data Standards

Dr. Tony Kerlavage, director of NCI’s Center for Biomedical Informatics and Information Technology (CBIIT), sat down to discuss one key component of racial inequality, the issue of health disparities, as it relates to Big Data. As noted by Dr. Kerlavage, representing our diverse U.S. population in research and in the workforce are key, but we also need better data.

This new blog installment shines a spotlight on the staff who are working to turn data and IT resources into solutions for addressing data-driven cancer research. This spotlight features Sherri de Coronado, program manager in the CBIIT Cancer Informatics Branch.

NCI initiatives are accumulating a wealth of data from the fields of genomics, proteomics, single-cell, radiology, molecular imaging, clinical findings, and more. The newly awarded Cancer Data Aggregator (CDA) is currently being designed and developed to allow scientists to crosstalk among these very diverse data sets, facilitating interoperability not only within the Cancer Research Data Commons but throughout the larger data ecosystem.

The quest to harmonize data has ushered in a new way of thinking about standardization. Now, rather than expecting everyone to adopt a particular model or standard, we’re seeking to leverage technology that can do some of this work for us. The DREAM Challenge was designed to make aggregating and mapping data to the correct lexicon of terms and metadata a nearly seamless step for researchers. Read more about the Challenge that’s currently underway and how we hope to address harmonization in the future.

This new blog installment shines a spotlight on the staff who are working to turn data and IT resources into solutions for addressing data-driven cancer research. Here we feature Mervi Heiskanen, Ph.D., program manager in the Cancer Informatics Branch at CBIIT. Much of her work focuses on data sharing and creating the tools and resources that help to make open data a reality.

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 world of clinical research standards, including the BRIDG Model that bridges research and healthcare, would truly not be what it is today without the significant and selfless contributions of Dr. Edward Helton.

Biomedical knowledge is typically centered around the variety of biological entity types, such as genes, genetic variants, drugs, diseases, etc. Collectively, we refer to them as "BioThings." The volume of biomedical data has grown explosively, thanks to the efforts of many different researchers and consortia. This explosive growth includes many different types of data using many different formats and standards, making it difficult to unify the disparate sources of data.

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.

Broad and equitable data sharing can be interpreted in many ways. For NCI's Office of Data Sharing, this means balancing the support of exciting science and innovation and the needs of research and participant communities with privacy and realistic expectations. This balance is possible when the policies we create acknowledge the benefits and challenges the public, research, and participant communities experience as they share their information to advance disease knowledge and improve healthcare.