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Richard Smith: Addressing the Problems of Addressing at British Transport Police
 

Richard Smith: Addressing the Problems of Addressing at British Transport Police

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  • Rules engines makes it easier to program allowing us to move from imperative models, to lists of production rules. Four generic index population rules are applied in two sessions, using NLPG then NSG. The checks are applied to the themes of BTP location types. This is because different groups will contain subtly different characteristics. Separating the rules into separate workflows keeps the rules within a narrow context, making the impact programme flow easier to manage. It also allows BTP to keep extending the index, dataset by dataset.
  • The system runs through the rules, picks the ones for which the condition is true, and then evaluates the corresponding actions, in this case populating the index. The interaction of the implicit rules can often be quite complex, particularly when the actions of rules impact the resulting conditions of other rules. Chaining rule-based tasks in different orders can lead to different results. Support for re-ordering is essential in order to systematically discover the flow that populates the index with optimal confidence. The addressing problem, plus many other problems, fit this production rule computational model.
  • Leveraging Intelligence The index enables users to understand, with confidence, that the same place can described in different ways in different data sources which means they can truly understand the nature of place. Information Re-Use The index enables the user to re-use different data. This means users can perform data level comparisons to define baseline and quantify data quality in data sources. Accuracy (fit for purpose) Use the index of information by updating and appending information from one source to enable yourself to automatically improve the content and accuracy of data sources. Rules-based Approach Managing production rules, not data models, enables the business people to use specialist knowledge. They can control and describe the rules without the expense and dependency on specialist skills or developers. Data Centric Intelligence Use the index information to define database views of the information, which you can control and administer once and deploy across the entire enterprise. Maintaining History Use changes in the index to control information archiving. This enables users to maintain historical views of information, as well as keep an auditable and versioned data source.

Richard Smith: Addressing the Problems of Addressing at British Transport Police Richard Smith: Addressing the Problems of Addressing at British Transport Police Presentation Transcript

  • Addressing the Problems of Addressing at British Transport Police Richard R. Smith, Force Information Manager, British Transport Police Bob Chell, Principal Consultant, 1Spatial Group Ltd
    • National Uniformed Police Force formed in 1826 (3yrs before the Metropolitan Police Service)
    • 10,000 miles of track
    • 3,000 railway stations and depots
      • National Rail network across England, Scotland and Wales
        • London Underground system
        • Docklands Light Railway
        • Glasgow Subway
        • Midland Metro tram system
        • Croydon Tramlink
        • International services operated by Eurostar
    Who are BTP?
  • Who are BTP?
    • Police the journeys of six million passengers
    • 400,000 tonnes of freight
    • Over 10,000 miles of track
    • We believe traveling is about more than just getting there.
    • It’s about ensuring safety and security all the way.
  • UK Location Strategy Place Matters. Everything happens somewhere. If we can get a better understanding on this we can make better use of resources, improve planning and advance our management of risk. There is too much data duplication, too little reuse, too few linkages across datasets to support policy implementation. This is particularly true for the emergency services, where inaccurate data can result in lives being put at risk.
  • Command and Control
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  • Non-Suspicious Death
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  • The Problems of Addressing A root cause of these inaccuracies is the multiple sources of event data and often conflicting address databases in use, such as NLPG, AL2 and PAF. There is an initiative (NESG) to produce a reliable, common address gazetteer for the emergency services, which will overcome many of these problems. However, there is an immediate need for individual forces to maintain their own address database or gazetteer now. This is for both incident response and to provide accurate mapping in support of intelligence generation, resource planning and many other activities.
  • Addressing the Problem British Transport Police (BTP) has recently embarked on a programme to automate the audit and repair of their incident database in relation to the NLPG and other address files. BTP have been able quantify the quality of data held within their Gazetteer, which is core to providing location information to any Officer responding to an Incident on the Railway. After the audit, the same technology will be used to provide ongoing validation and ensure data integrity and reliability.
  • The Impact on the Business
    • “ Right Information, Right Place, Right Time”
    • Assist in meeting National Targets
    This target excludes Major Incidents and incidents classed as Suspicious, RTC Level Crossing, Unexplained, Sudden Deaths and Work related deaths. To conclude police activity which disrupts train movement within an average of 90 minutes from receiving a report of a fatal incident. FATALITY MANAGEMENT TARGET OBJECTIVE NATIONAL TARGETS FOR ALL AREAS
  • Master Data Management BTP have achieved this by generating a baseline of information based on the NLPG and NSG against their Location Gazetteer. A rule-based approach has been taken to evaluate the data and build this baseline. In effect, they have generated a master index of their Location Gazetteer. This index provides a complete and consistently assembled view of what is happening and where.
  • Digital National Framework
  • BTP indexed with against NLPG Not Matched / Matched
  • BTP indexed with against NLPG and NSG Not Matched / Matched
  • BTP Location Gazetteer Names
  • Where Am I?
  • The NLPG and NSG
  •   Matching Process to Populate the Index DN8 4HZ POST_CODE DONCASTER POST_TOWN FIELDSIDE STREET RAILSTN TYPE THORNE NORTH RAILWAY STATION LOCATION VALUE ATTRIBUTE POST_CODE DONCASTER POST_TOWN STREET THORNE NORTH RAILSTN LOCATION VALUE ATTRIBUTE
  • BTP Impact Assessment The BTP Locations are first analysed to understand the quality (completeness and logical consistency) of the data. It allows us to make a baseline assessment of the information. Business rules check different address characteristics of the data, focussing on the address-related elements such as Street Name, Postcode and Post Town .
  • Index Population - Rules
    • These checks are applied to themes of BTP location types. Different groups will contain subtly different characteristics .
    • Grouping the data into themes also reduces the number of rules that BTP have to construct. This makes it easier to manage the rule base.
        • Stations (Railway, Disused, …) Tier 1 (Control Rooms, Metro, …) Tier 2 (Bridges and Crossings, …) Tier 3 (Signal Boxes, Sidings, …)
  • Populating the Index using Rules If NOT IN THE INDEX or PART OF THEME Then perform the necessary conditional checks If the checks are true then populate the index
  • Postcode Street Geo Postcode Geo Street Geo Geo Only Populating the Index with Confidence - Confidence +
  • Populating the Index using Workflow Workflow media player controls Cut, copy, delete and re-order tasks
  • BTP Baseline Assessment
  • Index Overview with Confidence
  • BTP Content, Update Less than 10% of the data matches the NLPG or NSG But we have matched 60-85% of the data, with confidence BTP NLPG
  • BTP Content, Append Less than 20% of the data even contains a Street Name… … similar characteristics for Postcode and Post Town ??? But we have matched 60-85% of the data, with confidence BTP NLPG
  • Advantages
    • Leveraging Intelligence
    • Information Re-Use
    • Accuracy (fit for purpose)
    • Rules-based Approach
    • Data Centric Intelligence
    • Maintaining History
  • Benefits
    • Reliable Data – Saving Time, Saving Lives
    • Location
      • Correct Allocation of Resources
      • Correct Incident Reporting
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  • Benefits
    • Reliable Data – Saving Time, Saving Lives
    • Location
      • Correct Allocation of Resources
      • Correct Incident Reporting
    • Addressing the Management of Police Information (MoPI)