Studies foundational data management and knowledge discovery challenges prevalent in design, analysis and organization of data. This area can be applied in a variety of domains including data management in resource constrained environments, enterprise and multimedia databases, active and secure databases and knowledge discovery algorithms.
- Prof. Henry Etlinger
- Prof. Xumin Liu
- Prof. Rajendra Raj
- Prof Carlos Rivero
- Prof Carol Romanowski
- Prof. Leon Reznik
Selected Research Projects
Automatic service composition for efficient delivery of customized business processes
This project proposes an efficient and effective approach that supports dynamic business process development. Our approach addresses the limitations of the current service composition technologies by developing an innovative Web service ontology that allows automatic discovery and composition of Web services in an efficient way.
This project focuses on leveraging historical emergency data to support emergency management. In particular, this multi-disciplinary work covers a historical analysis of emergency data to increase overall understanding of the interaction between events, critical infrastructure, and First Responder resources, thus improving decision making by emergency managers based on optimal allocation policies and logistics.
Efficient Deployment and Delivery of Web Services in a Mobile Environment
This project addresses the performance issues of hosting and delivering web services in a mobile environment. We identify and investigate the important factors that affect the performance of a mobile server and propose a dynamic request handling strategy to improve concurrency performance of a mobile server. We propose an efficient framework that uses broadcasting to deliver services (single or composite) to optimize average access time.
Data quality (DQ) evaluation and assurance
The project develops a comprehensive data quality (DQ) evaluation and assurance methodology and tools focusing on an integration of various factors affecting DQ in CPS systems including accuracy, reliability, timeliness, security, and safety into a single methodological and technological framework.
This project seeks to develop principles, policies and architectures for integrating real-time fusion of emergency management data from multiple sources.
Quality issues for data-intensive applications.
This project is exploring methods and metrics for measuring data quality, as well as related ethical issues.