SCH: Workshop on Data Science, Learning, and Applications to Biomedical and Health Sciences
This proposal is for the Transatlantic Data Science Workshop. 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. A main thrust of this transformation requires the use of novel computing and statistical methods to model complex disease trajectories using health data. Unfortunately, access to quality health data is not obvious to non-health and medical science researchers. In addition to lack of access, significant challenges exist in the analysis of 'big data' in the health domain. Investigators in the fields of computer science, mathematics, statistics, and computational sciences may offer expertise in addressing said challenges. This workshop brings together members of multiple scientific communities from the United States (NSF and National Institutes of Health: NIH) and the United Kingdom (Research Council of the United Kingdom: RCUK) and has two primary objectives: 1) to improve access to US and UK health data and to expose challenges surrounding health data research to computer science, mathematics, statistics, and computational science communities, and 2) to foster the development of novel computational and mathematics methodologies in health data science research by bringing together US and UK communities of health domain experts and computational researchers.
The Transatlantic Data Science Workshop includes facilitating the development of novel computational approaches in the health domain using data from two major health data funding agencies (RCUK and NIH). The computational community will be exposed to the challenges and needs in health data research, resulting in opportunities to advance data science research. Analytics challenges surrounding health data research may include data quality and provenance, search, query processing, and visualization and modeling. The first day of the workshop will be devoted to an in-depth exploration of the challenges that are experienced in conducting health data research with six major health datasets. The second day will offer an opportunity for researchers to work in small groups to discuss and develop novel computational techniques and methodologies to tackle such challenges in the health domain. The proposed workshop should aid in the development of novel computational techniques to address challenges in health data research.
