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The cloud roadmap for MapRoad data validation

The cloud roadmap for MapRoad data validation. GIS Ireland 2012 Barry Doyle, Roscommon County Council and Chris Tagg, 1Spatial. MapRoad Background.

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The cloud roadmap for MapRoad data validation

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  1. The cloud roadmap for MapRoad data validation GIS Ireland 2012 Barry Doyle, Roscommon County Council and Chris Tagg, 1Spatial

  2. MapRoad Background • GIS application used by Local Authorities to manage road related data such as the road itself, road condition data, road maintenance data, accident data, bridge data, and traffic data. • Desktop based \ Runs on top of MapInfo. • Functionality available through a number of modules. • To be used for the planning, creation, estimation of Works Programmes. • Developed, Implemented, Supported by LGMA (Previously LGCSB).

  3. Road Network Module • Main module used to manage and maintain the Road Schedule. (Roads taken in charge by the Council). • Roads are represented as road segments, with nodes identifying start and end points. • Attribution stored against road segments and nodes.

  4. Project Drivers • Recognition of need to improve accuracy of Road schedule. • Various issues identified including: • Accuracy issues (Originally digitised from OSi 6” map series) • Connectivity issues (Road to Road / Road to node) • Geometric issues • Support evidence based grant submissions. • Upgrade to MapRoad 2.3.

  5. Online Validation Service Input MapRoad INitial Validation Quantitative benefit analysis Baseline assessment Kickbacks, spikes, dup points Continuous network Accurate alignment Geometric correction Network Connectivity Osi RoadLine Alignment Final Validation

  6. Results • Automated workflow reduced number of non-conformances from 12, 312 to only 161

  7. Benefits • Validation • Service gives a picture of data prior to any processing • Can be used to identify internal process issues and define business cases • Identification of all issues and errors • MapRoad specific • Geometric • Identification of errors that couldn’t be identified manually • Time and resource savings • Auto-correction • Re-alignment with OSi large scale vectors

  8. Benefits • Future Proof • Utilisation for other purposes e.g. INSPIRE • Easy integration with OSi PRIME2 • Flexible • Rules can be added or modified within a relatively short timeframe • The cloud approach • No implementation costs (hardware / software /development) • Subscription cost model

  9. Barry Doyle bdoyle@roscommoncoco.ie Chris Tagg chris.tagg@1spatial.com

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