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Making sense of the Big Data that is your roadstreet network

October 17, 2017 - A municipal road network is complex. Not just in the quantity of streets and intersections, but of all the information that “hangs off” every section of road. Some are obvious such as the pavement type, or light poles. Others are less obvious such as the median barrier, or culvert headwalls. Some are even invisible like storm sewer pipes or traffic sensors. Add onto that a plethora of intangible pieces of data like collision history, pavement condition, speed limits, 911 address points, emergency detour routes, and the list goes on and on. Much of the data that comprises this information is also highly complex and it’s bound to only get deeper with the advent and increased adoption of small, cheap and long-lasting sensors that can give second-by-second light intensity levels, or asphalt moisture content readings or even instantaneous loads by passing vehicles. Road authorities will be collecting data faster than they can interpret and make use of it, if they aren’t there already. A robust foundation is needed to serve as a system of record which can store the countless different types of data, provide a transparent linkage to various business systems in the environment, give non-GIS and non-road network professionals access to read, edit and input data, and most importantly make sense of it all so they can get better at delivering their service that we all depend on as users of the road network. This webinar will investigate how a spatially and linearly enabled road management system can accommodate all of these requirements while making road network information accessible to more people in the environment. We will also investigate how spatial Business Intelligence tools can interpret the data to gain useful and actionable insight into a highly complex road network.