GeoWorld February 2013

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Geography Integrates Static and Dynamic Data for Operational Awareness DYNAMIC DECISION POINTS I n information technology, the whole certainly is greater than the sum of the parts. Federated systems comprised of individual components aggregated and integrated together to form a solution now are the norm and provide competitive advantage. One of the greatest challenges to integrating two or more systems together is ���nding a common language, and integration based on ontology is becoming more common as a method for transcending disparate data models. In simple terms, BY ERIK SHEPARD an ontology is a meta-model that describes higher-level concepts in a common way. For example, ���coke,��� ���soda��� and ���pop��� all describe the same carbonated, highly sugared beverage, but are used colloquially: ���soda��� in New England, ���pop��� in the Midwest and ���coke��� in the South (whether it���s Pepsi, Mountain Dew or Coca Cola, it���s still ���coke���). An ontology may de���ne a ���soft drink,��� and then individual applications will map ���soda��� to ���soft drink��� or ���pop��� to ���soft drink��� as part of the integration layer. Geography Is the Platform Erik Shepard is director and principal of Waterbridge GeoDesign Inc.; e-mail: erik@ 30 Geography is well known as the integrative discipline: human geography bridges psychology, sociology and political science; while physical geography and biogeography serve to link geology, physics, biology and chemistry. Indeed, geography can serve as the platform to integrate statics and dynamics to achieve operational awareness (i.e., situational awareness). From a static perspective, an organization typically has an abundance of ���basemap��� data: land parcels, road centerlines, hydrography and orthophotography. Of course, nothing in the world is truly static���all these things change through time, but, to many organizations, a quarterly or yearly subscription for update means that change happens very slowly. Organizational boundaries such as service territories also evolve very slowly. Such contextual data effectively serve as a static backdrop. In terms of dynamic data, virtually all business data are dynamic. Asset-management systems are G E O W O R L D / F E B R U A R Y 2 O 1 3 continually updated with new assets going into service, assets being retired, or assets upgraded or changed. The asset-management system also is typically the repository for asset-inspection schedules, maintenance strategies, condition histories and risk pro���les. This allows for questions that explore assets within reliability tolerances or repeated outages costing money in lost service or ���nes. The asset-management system likely will have a simple representation of place, based on latitude and longitude, but the assets also will exist in a context of projected map space and relationships to other layers such as through network topology. Dynamic Systems Customer-information systems are highly dynamic, with customers initiating or cancelling service regularly. Customers also exist in a context of place��� most often georeferenced by service address. A service address outside the context of place doesn���t mean much, but when mapped against a road centerline, it can be layered alongside the basemap data and asset repository. A geographic platform can provide the road centerline and georeferenced address as well as the boundaries of the customer property, locations of rights of way and other useful data. Field crews also are highly dynamic, with service routes differing each day. Crews are typically routed to customer locations, so the context of service address and road centerline for navigation becomes important. The ability to map the ���eld-crew location with respect to past and future jobs, combined with the service address to which the ���eld crew has been routed and the assets on which the crew will be working, is essential to operations. Other types of non-business-owned data also can qualify as dynamic, and provide insight and operational effectiveness. Two commonly purchased services for spatially distributed organizations are weather and traf���c. Weather can indicate severe storm potential from wind, ice or snow, and it can change in minutes or hours. Understanding weather potential can inform how ���eld crews are distributed ahead of a storm to minimize service interruption. Traf���c has time implications to dispatch crews to respond to unplanned outages, or whether or not a ���agman is required for a particular job. The common element in each of these, whether latitude and longitude against a base map, network connectivity or address georeferencing (whether the data are static or dynamic), is that they have locations in space and time. The geographic platform that an organization deploys can integrate these otherwise disparate systems to facilitate operational awareness.

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