Health data originate from a wide variety of heterogeneous data sources which include medical literature, Electronic Medical Records (EMRs), medical imaging data, time series data from ICU/in-hospital sensors, insurance claims data, wearable sensors, mobile health applications data, omics data, etc., just to name a few. However, unlike many other domains much of these information remain in paper form, lack common standards, are not shared and frequently hampered by the lack of fool-proof de-identification for patient privacy. Much of healthcare data remains hidden as unstructured data in the form of clinical notes, imaging reports, patient narratives, and so on. 
Effective integration and management of these multiple heterogeneous data sources and mining them for actionable insights requires inter-disciplinary research across multiple domains of computer and medical sciences. The goal of this workshop is to bring together researchers cross-cutting the fields of data management and medical informatics to discuss the unique challenges in health care data management and to propose novel and practical solutions for next generation ``data driven" healthcare systems. 
The workshop is intended to facilitate cross-disciplinary research collaboration to develop innovative solutions for healthcare data management and mining, effectively breaking the ``data silos" barrier across the diverse health data sources. We also intend to discuss potential of creating common datasets for future research which can be made available publicly by addressing concerns such as privacy.