Copyright © 2015 Open Geospatial Consortium.
5 SVG
Scalable Vector Graphics URI
Unique Resource Identifier URL
Uniform Resource Locator URL
Uniform Resource Name WFS
Web Feature Service WKT
Well Known Text
WMS Web Map Service
4.2 UML notation
Some diagrams that appear in this standard are presented using the Unified Modeling Language UML static structure diagram, as described in Subclause 5.2 of [OGC 06-
121r3].
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Copyright © 2015 Open Geospatial Consortium.
5 ER Topic overview
Incident management plays a crucial role in many application domains including Homeland Security, Law Enforcement and Public Safety LEAPS, and Emergency and
Disaster Management EDM. An Incident Management System IMS needs to facilitate rapid, agile and effective engagement of first responders at national, state and
local jurisdictional levels to respond to emergency incidents that may pose an immediate security threat to human life andor the flow of commerce. The current systems face the
following challenges.
Y Analysts and operators need to quickly triage, fuse, connect dots, detect patterns, infer insights, and make sense of the flow of incident information to get an
unambiguous Common Operational Picture using symbology that makes sense to the users.
Y Users need to integrate and interpret incidents, observations, mutual aid requests, alerts, symbologies, taxonomies, etc. generated across a multi-agency, multi-
jurisdictional spectrum. Y There is limited interoperability between agencies due to different protocols,
taxonomies, models and symbolic representations stovepipes are still there. The current data-centric implementations are mainly based on syntactic and structural
approaches and thus imposes a huge cognitive burden on the users to make sense of the large volume and varieties of information.
Data model standardization relies upon homogeneous data description and organization. This imposes strict adherence to a standard that is defined at the syntactic-schematic
level. Achieving consensus in definition of the data model is difficult and the final model is less flexible. Modelers struggle between producing simple models where it is easier to
gain consensus but harder to achieve desired business reality versus those seeking richer models that are closer to reality but have unwanted complexity.
Data-centric approaches using for example XML Schema, or JSON increase the chance for multiple interpretations and misinterpretations of data. Data interpretation requires
knowledge of the semantics e.g., meanings, significance, relevance, etc. and surrounding context. Data-centric approaches are unable to capture these semantics and
context, which are in turn required for automated fusion, analytics, and reasoning.
To address these challenges in the domain of symbology mediation related to EDM, we adopted a knowledge-centric approach. The knowledge-based approach employs a
standards-based formal, sharable framework RDF, OWL, SPARQL that provides a conceptual domain model to accommodate various business needs. Among these
standards, there are:
