Towards A Spatiotemporal Event-Oriented Ontology Yong Liu Co-authors: Robert E. McGrath, Shaowen Wang, Mary Pietrowicz, Joe Futrelle, James Myers National Center for Supercomputing Applications (NCSA) University of Illinois at Urbana-Champaign 1205 W. Clark St. Urbana, IL 61801, USA

Why Do We Need an Event-oriented Ontology? (From Technology Perspective) Current GIS (Geographic Information System) and spatial database technology does not support complex thematic analytics operations and event-oriented modeling/analysis/visualization etc. Still driven by the Snapshot Paradigm The representation of events and processes is implicit rather than explicit Traditional data models used for GIS tend to model the thematic aspects of a given domain as directly attached attributes of geospatial entities Point, line, polygon and grid, Trianular Network (TIN), network This fundamentally limits what environmental and hydrological modelers can do within the GIS framework Current semantic analytics technology does not explicitly support analysis of spatial and temporal relationships Semantic analytics research has focused on thematic relationships between entities. Thematic relationships can be explicitly stated in RDF graphs, but many important spatial and temporal relationships (e.g., distance and elapsed time) are implicit and require additional computation. Perry & Sheth (2006) started to address this issue We need information systems that support events as the unit of analysis/modeling/visualization explicitly Event-oriented ontology (or data model) will help us to build such system Event (or Occurent) as the first-class entity Event-to-Event, Event-to-Object relationship can be explicitly analyzed

Why Event? From Coupled Natural and Engineered System Researchers Perspectives From Simulation Modeling Perspective (Reitsma and Albrecht, 2005) : Representing dynamic simulation model results with state-based data model means loss of information of the process (or at best can only be interpolated) But very different (or even wrong) events/processes can lead to the same end state There are many examples in the environmental/hydrological science literatures about such difficulties (Baird, 2004) Representing processes/events explicitly provides the opportunity to explore which process are dominant and whether our descriptions of those processes are correct From Situational Awareness And Decision Support Perspective: E.g. Flooding (During and Post-Disaster Information Management and Impact Analysis) Many events happen a heavy storm: Precipitation (storm) Flooding of basement Combined Sewage Overflow (CSO) event Operational event (open/close gates to release combined sewer and stormwater to the sewersheds) Sensor reading event (spike or malfunction of rain gage and streamflow gages reading) From Information Integration and Visualization Perspective: Event-based information integration across disciplinary boundary Spatio-temporal-thematic visual analytics of different events for sensor data (Beard et al. 2008) Event-based uncertainty analysis (Thorndahl et al. 2008)

What Have We Done About Event Ontologies Several ontologies describing events and related concepts have been investigated several have OWL ontologies (see our position paper) These ontologies have similar concepts, and can be combined into a single OWL ontology. E.g. If we agree that is a subclass of then we can reason that, …Ontology owl#Event can have an OWL property.../event.owl#hasFactor Note: BFO (Basic Formal Ontology: SPAN/SNAP) now has OWL: this would be a good top level. OWL expresses classification and some kinds of properties, but is not suited for temporal or quantitative relations. E.g., cant express a constraint like begintime must be earlier than endtime

Occurent (Event) As the First-class Entity Occurrent Continuant Named_Place Spatial_Occurrent Dynamic_Entity Water Sewershed sewer stormwater CSO Event Precipitation Is_discharged_by Spatial_Region located_atoccurred_at Domain Ontology rdfs:subClassOf used for integration rdfs:subClassOf relationship type Upper-level Ontology (after Perry et al 2006) Tunnel Gate Operation impacts is_caused_by [t1..t2]

Concluding Position Spatiotemporal Event-oriented ontologies can help move beyond keyword lists for classification Can help in scientific modeling and simulations Can facilitate knowledge-based reasoning and improve situational awareness during and after flooding Can provide new ways for information integration and visual analytics Current OWL can only have limited support for classification A hybrid system is under investigation Design of event-oriented ontologies is applicable to other cases EventWeb

Acknowledgements NCSA TRECC Digital Synthesis Framework for Virtual Observatory Project Jim Myers, Luigi Marini, Joe Futrelle, Alejandro Rodriguez, Terry McLaren, Bob McGrath, Peter Bajcsy, Rob Kooper, Wenwu Tang, etc. AESIS (Adaptive Environmental Sensing and Information Systems) Initiative at NCSA/UIUC Barbara Minsker, David Hill, Tarek Abdelzaher, Jin Heo, Seon Kim, David Fazio, Murugesu Sivapalan, etc. IACAT (Institute of Advanced Computing Applications and Technologies) Project Barbara Minsker, Don Wuebbles, Praveen Kumar, Jim Myers, Xiaowen Wu, etc.