The need for a significant transformation of health and healthcare has been recognized by numerous organizations, including the President's Council of Advisors on Science and Technology, National Research Council, Institute of Medicine, Computing Community Consortium, and the National Academy of Engineering. Additionally, a congressionally mandated review of Networking and Information Technology Research and Development emphasized the critical role that networking and information technology will play in spurring innovation to solve the nation's most pressing challenges, beginning with health and healthcare.

This workshop aims to tackle these needs through a collaboration between the National Science Foundation (NSF), the National Institutes of Health (NIH) and the Research Councils of the United Kingdom (RCUK). The workshop has the following three goals:

Goal 1To facilitate the development of novel computational approaches to health challenges. 

Due to advances in high throughput and connective computing, medicine is at the cusp of a transformation that will accelerate discovery, improve patient outcomes, decrease costs, and address the complexity of challenging health problems. This includes the utilization of diverse data to provide automated and augmented insight, discovery, and evidence-based decision support and health services. A main thrust of this transformation requires the use of novel computing and statistical methods to model, predict, and intervene on complex disease trajectories using health data. 

Goal 2: To guide computer scientists, data scientists, statisticians, computational scientists, and mathematicians in discovering and accessing NIH-funded US and RCUK-funded UK health datasets.

Access to quality health data is not obvious to non-traditional health researchers (e.g., computer science, mathematics, and statistics). Agencies with health missions, such as the NIH and components of the RCUK routinely collect high quality health data. These data are from diverse sources (e.g., genetics, behavior and earnings data). By design, the data are curated and made available for use the by researchers around the world. While the intention of funding agencies is for these data to be available, in reality most access comes from traditional health and medical research communities. Lack of access and understanding of these datasets by computational communities inhibits the growth of data science in the health/medical domain.

Goal 3: To support early-stage researchers in establishing interdisciplinary, international collaborations.

This workshop addresses these issues by bringing together computational and health researchers from the US and UK to increase awareness of available data sets to improve opportunities for discoverability and access and to enhance utilization of existing research datasets. The workshop will also address the related challenges in using existing datasets by computing, math and statistical researchers. These challenges will be addressed by bringing together computational researchers, health domain experts, database developers and super users. Finally, the workshop will enhance novel data science by facilitating new US-UK research collaborations.