Real-time Linked Dataspaces

Edward Curry is a research leader at the Insight Centre for Data Analytics at the National University of Ireland Galway. His research interests are predominantly in open distributed systems, particularly in the areas of incremental data management (e.g. dataspaces), approximation and unstructured events types, with a special interest in applications for smart environments and data ecosystems. Edward has published over 160 scientific articles in journals, books, and international conferences.

• 1 Real-time Linked Dataspaces: A Data Platform for Intelligent Systems within Internet of Things-based Smart Environments.- 2 Enabling Knowledge Flows in an Intelligent Systems Data Ecosystem.- 3 Dataspaces: Fundamentals, Principles, and Techniques.- 4 Fundamentals of Real-time Linked Dataspaces.- 5 Data Support Services for Real-time Linked Dataspaces.- 6 Catalog and Entity Management Service for Internet of Things-based Smart Environments.- 7 Querying and Searching Heterogeneous Knowledge Graphs in Real-time Linked Dataspaces.- 8 Enhancing the Discovery of Internet of Things-based Data Services in Real-time Linked Dataspaces.- 9 Human-in-the-Loop Tasks for Data Management, Citizen Sensing, and Actuation in Smart Environments.- 10 Stream and Event Processing Services for Real-time Linked Dataspaces.- 11 Quality of Service-Aware Complex Event Service Composition in Real-time Linked Dataspaces.- 12 Dissemination of Internet of Things Streams in a Real-time Linked Dataspace.- 13 Approximate Semantic Event Processing in Real-time Linked Dataspaces.- 14 Enabling Intelligent Systems, Applications, and Analytics for Smart Environments using Real-time Linked Dataspaces.- 15 Autonomic Source Selection for Real-time Predictive Analytics using the Internet of Things and Open Data.- 16 Building Internet of Things-enabled Digital Twins and Intelligent Applications using a Real-time Linked Dataspace.- 17 A Model for Internet of Things Enhanced User Experience in Smart Environments.- 18 Future Research Directions for Dataspaces, Data Ecosystems, and Intelligent Systems.