Visible to the public  TWC: Medium: Collaborative Proposal: Policy Compliant Integration of Linked DataConflict Detection Enabled

Project Details

Lead PI

Co-PIs

Performance Period

Sep 01, 2012 - Jan 31, 2017

Institution(s)

University of Maryland Baltimore County

Award Number


Outcomes Report URL


The ubiquity of computing technology and the Internet have created an age of big data that has the potential to greatly enhance the efficiency of our societies and the well-being of all people. The trend comes with problems that threaten to prevent or undermine the benefits. An immediate concern is how to fuse, integrate and analyze data while respecting privacy, security and usage concerns. A second issue is allowing data to remain distributed, enabling its owners to maintain and control quality as well as to enforce security and privacy policies. A final underlying challenge is helping to produce sound and useful results by assuring that systems understand the meaning of the data being integrated and analyzing access and usage policies. For some domains, like health informatics and clinical research, solving these problems will have a significant impact on society.

This project explores an approach to solving these problems by developing a policy-compliant integration system for linked healthcare data. The system models data, schemas and policies using open Web standards such as Semantic Web languages, federates queries to independent Linked Data stores based on content, provides policy enforcement by modifying incompliant queries, and uses formal methods to guarantee correctness of key components.

This project provides new approaches to solving one of the most significant problems our society faces in the 21st century: benefiting from the integration of distributed linked data while respecting security, privacy, and usage requirements. The prototype tools and systems are incorporated into our educational activities and made available to others via appropriate open source licenses.