Large scale clinical data are an essential resource for biomedical research as they can provide data on millions of patience, which allows for greater strength and reliability in research. The valuable data found within these existing real-world, large-scale clinical datasets may reduce the need for some traditional intentional trials on patients. However, accessing large scale clinical data can be challenging due to complexities in understanding and navigating the datasets, associated costs and license restrictions, among other barriers.

The Center for Clinical Observational Investigations (CCOI) will remove barriers to accessing data for researchers through a multi-prong approach. One method used in this multi-pronged approach are Dataset Profiles, which highlight, summarize, and aggregate information about and within a dataset. This provides key details to help researchers to understand the information provided by a dataset. One method NLM is using , NLM curated a list of nationally and internally available clinical datasets. Then used informatics, data science, and statistical analysis, NLM cataloged metadata such as participants, demographics, diseases, etc. into Dataset Profiles.

NLM seeks to continue evolving the resources available through CCOI. This includes continuing to add new Dataset Profiles, create additional views for comparison and enhancing the resources available to NIH researchers.