Ping Wang

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Ping Wang
Contact Info
Emailwangp5@cs.rpi.edu

Ping graduated with her Ph.D in Computer Science from RPI in May of 2012.

She was a member of the Tetherless World Constellation and worked on numerous projects within the lab from January 2011 till she graduated.

Her research interests include Semantic eScience, Linked Data and Provenance on the Web.

Publications:
Patton, E.W., Seyed, P., Wang, P., Fu, L., Dein, J., Bristol, S., and McGuinness, D.L. 2013. SemantEco: A semantically powered modular architecture for integrating distributed environmental and ecological data. Future Generation Computer Systems
Wang, P., Fu, L., Patton, E.W., McGuinness, D.L., Dein, J., and Bristol, S. 2012. Towards Semantically-enabled Exploration and Analysis of Environmental Ecosystems. In Proceedings of 8th IEEE International Conference on eScience (October 8-12 2012, Chicago, IL).
Lebo, T., Wang, P., Graves, A., and McGuinness, D.L. 2012. Towards Unified Provenance Granularities. In Proceedings of International Provenance and Annotation Workshop 2012 (June 18-22 2012, Santa Barbara, California).
Wang, P., Fu, L., Patton, E.W., McGuinness, D.L., Dein, J., and Bristol, S. 2012. SemantEco Extension for Natural Resource Managers.
Wang, P. 2012. Semantically Enabling Next Generation Environmental Informatics Portals.
Wang, P., Zheng, J., Fu, L., Patton, E.W., Lebo, T., Ding, L., Luciano, J.S., and McGuinness, D.L. 2011. Next Generation Environmental Informatics as exemplified by the Tetherless World Semantic Water Quality Portal. In Proceedings of AGU Fall Meeting 2011 (December 5-9 2011).
Patton, E.W., Wang, P., Zheng, J., Fu, L., Lebo, T., Ding, L., Liu, Q., Luciano, J.S., and McGuinness, D.L. 2011. Assessing Health Effects of Water Pollution Using a Semantic Water Quality Portal. In Proceedings of 10th International Semantic Web Conference (October 23-27 2011, Bonn, Germany).
Wang, P., Zheng, J., Fu, L., Patton, E.W., Lebo, T., Ding, L., Liu, Q., Luciano, J.S., and McGuinness, D.L. 2011. A Semantic Portal for Next Generation Monitoring Systems. In Proceedings of 10th International Semantic Web Conference (October 23-27 2011, Bonn, Germany).
Zheng, J., Wang, P., Patton, E.W., Lebo, T., Luciano, J.S., and McGuinness, D.L. 2011. A Semantically-Enabled Provenance-Aware Water Quality Portal. In Proceedings of the Environmental Information Management Conference 2011 (September 28-29 2011, Santa Barbara, CA, USA).
Wang, P., Zheng, J., Fu, L., Patton, E.W., Lebo, T., Ding, L., Liu, Q., Luciano, J.S., and McGuinness, D.L. 2011. TWC-SWQP: A Semantic Portal for Next Generation Environmental Monitoring (Technical Report).

Presentations:

Project Collaborator

FUSE LogoForesight and Understanding from Scientific Exposition (FUSE)
Principal Investigator: Deborah L. McGuinness
Description: Technical emergence refers to the process whereby innovative ideas, capabilities, applications, and even entirely new fields of study arise, are tested, mature, and, if conditions are favorable, demonstrate feasibility and impact. IARPA’s Foresight and Understanding from Scientific Exposition (FUSE) Program is sponsoring advanced research and development (R&D) to develop automated systems that aid in the systematic, continuous, and comprehensive assessment of technical emergence using information derived from the published scientific, technical, and patent literature.
Health on the Web
Principal Investigator: Deborah L. McGuinness and Joanne S. Luciano
Description: The Tetherless World Constellation's Health on the Web's primary goal is to explore the next generation web technology needed to improve health.
SemantAQUA LogoSemantic Water Quality Portal (SemantAQUA)
Principal Investigator: Deborah L. McGuinness
Co Investigator: Joanne S. Luciano
Description: We present a semantic technology-based approach to emerging environmental information systems. We used our linked data approach in the Tetherless World Constellation Semantic Water Quality Portal (TWC-SWQP). Our integration scheme uses a core domain ontology and integrates water data from different authoritative sources along with multiple regulation ontologies to enable pollution detection and monitoring. An OWL-based reasoning scheme identifies pollution events relative to user chosen regulations. Our approach also captures and leverages provenance to improve transparency. In addition, semantic water quality portal features provenance-based facet generation, query answering and data validation over the integrated data via SPARQL. We introduce the approach and the water portal, and highlight some of its potential impacts for the future of environmental monitoring systems.