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Page 1: May 2012 Oracle Spatial User Conferencedownload.oracle.com/otndocs/products/spatial/pdf/osuc2012... · • Planning work to avoid conflict, ... to ensure a collaborative approach

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May 2012 Oracle Spatial User Conference

Page 2: May 2012 Oracle Spatial User Conferencedownload.oracle.com/otndocs/products/spatial/pdf/osuc2012... · • Planning work to avoid conflict, ... to ensure a collaborative approach

May 23, 2012 Ronald Reagan Building and International Trade Center

Washington, DC USA

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Andrew Howles & Jo Shannon IS Principal Architect General Manager, Operations

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Automated Data Quality Processes in Ordnance Survey’s GDMS

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OVERVIEW •  Centrally managed, authoritative database •  Incorporates 5 corporate national datasets •  Supports national data capture and maintenance •  Contains in excess of 500 million features

CHALLENGES / OPPORTUNITIES •  Need to integrate disparate data sets •  Need to extract 32 million features and submit 313,000

changed features per day •  Need to support multiple users in the same geographic area •  Automated data validation to achieve product ready

database ORACLE SOLUTIONS •  Oracle Spatial Database, Partitioning, RAC, Dataguard •  Oracle Workspace Manager •  Oracle Application Server & Weblogic •  Oracle BPEL & Worklist Application •  Oracle Enterprise Service Bus •  Oracle Identity Management

RESULTS •  Consolidation of raster, vector, network data in 5.3TB

sized central repository •  Single source database for product derivation •  Seamless working – removal of tile based restrictions •  Resilient production environment achieving 99.5%

availability

Ordnance Survey Geospatial Data Management System

Insert application screenshot here

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Agenda

•  Introductions • Ordnance Survey and GDMS business context • Oracle technology in GDMS • Radius Studio technology in GDMS • Challenges • Next steps • Conclusions • Q&A

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Introductions

•  To the Presenters: – Andrew Howles, Ordnance Survey –  Jo Shannon, 1Spatial

•  To the Geospatial Data Management System (GDMS): – Enterprise geospatial data factory – end-to-end planning, collection,

management, validation, and publication to product stores – Multi-vendor service-oriented architecture built on the Oracle

technology stack – Went live in July 2011

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Ordnance Survey business context

•  Self-funding government agency; remit covers Great Britain (England, Scotland and Wales) – 243,241 sq km / 93,956 sq miles

•  Datasets maintained on a national basis – common specifications to ensure consistency in terms of precision, accuracy and content

•  Close collaboration with Land Registry of England and Wales, and Registers of Scotland

•  Integrated data capture for field surveyors, HQ-based editors, and external suppliers

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Ordnance Survey business context

•  Digital geospatial data products over 90% of Ordnance Survey’s business

•  Over 450 million unique feature identifiers (TOIDs) introduced by OS MasterMap® in 2001 – hooks to which information can be linked: –  emphasis on geographic information –  integration of addresses, boundaries, road

centre-lines and network topology with topographic base

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GDMS programme context

•  Seamless data maintenance solution •  Intelligent and integrated maintenance

data model •  Separation of product data •  Automated data validation •  650+ production users in Ordnance

Survey and other organisations •  Platform for new product development

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GDMS programme context

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GDMS programme context

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GDMS programme context

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GDMS programme context

• Main unit is the feature •  Features are composed of components including:

–  identity –  lifecycle –  location –  classification –  relationships –  history

• Model prescribes around 150 specification rules

GDMS real-world object model – Geobase-04

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GDMS programme context

•  500 million features and growing (+ history) •  4,000 data maintenance jobs per day •  32 million feature extractions per day •  313,000 features updates per day •  650+ users inside and outside Ordnance Survey •  99.5% availability

Non-functional characteristics

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GDMS programme context

•  Mainstream architecture patterns: –  n-tier solution –  service-oriented approach (business logic) –  workflow layer (orchestration logic)

•  Heterogeneous software environment – best of breed COTS components from diverse vendors:

–  1Spatial, BAE Systems, ESRI, Intergraph, Microsoft, Oracle, Safe Software, Snowflake Software

•  Long transaction management, disconnected editing •  Scalable infrastructure on commodity hardware, selective virtualisation

Architectural principles

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GDMS programme context Logical architecture

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GDMS programme context

• Member of the Intergraph Consortium along with Snowflake Software

Role of 1Spatial within the Intergraph Consortium

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Role Of Oracle in GDMS

Real Application Clusters

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Workspace Manager in GDMS Key to Transaction Integrity

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Workspace Manager in GDMS Acetate Overlay Model

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Workspace Manager in GDMS Data Conflict

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Workspace Manager in GDMS Logical Inconsistency

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Role of Radius Studio

•  Spatial data integration platform •  Knowledge Store • Rules based spatial analysis • Web application & web services • GRID processing •  Extensible – built-ins, datastores

What is

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Role of Radius Studio Rules based processing paradigm

Action Pattern Fact

Data Rule

Report

Reconcile

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Role of Radius Studio Examples of Rules

FACT

PATTERN Railway points must be within 0.8 metres of at least 1 rail object

ACTION

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Challenges

•  Schema design choices can cause physical data conflict to arise in instances where there is no logical conflict

1. Physical realisation of the logical model

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Challenges 1. Physical realisation of the logical model

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Challenges 1. Physical realisation of the logical model

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Challenges

•  Schema design choices can cause physical data conflict to arise in instances where there is no logical conflict

• Our advice: When optimising your schema, don’t just think about performance but consider conflict avoidance as well

1. Physical realisation of the logical model

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Challenges

• Complex data requirements mean simple A versus B type decisions are not suitable for conflict resolution: –  logical semantics of spatial data – e.g. topological structuring –  version metadata

2. Conflict resolution

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Challenges 2. Conflict resolution

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Challenges 2. Conflict resolution

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Challenges 2. Conflict resolution

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Challenges 2. Conflict resolution

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Challenges 2. Conflict resolution

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Challenges 2. Conflict resolution

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Challenges 2. Conflict resolution

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Challenges 2. Conflict resolution

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Challenges 2. Conflict resolution

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Challenges

• Complex data requirements mean simple A versus B type decisions are not suitable for conflict resolution: –  logical semantics of spatial data – e.g. topological structuring –  version metadata

• Our advice: Understand the implications of your data model and schema for the process of conflict resolution

2. Conflict resolution

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Challenges

•  Planning work to avoid conflict, where possible, is better than being in a conflict resolution situation

3. Work planning

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Challenges 3. Work planning

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Challenges 3. Work planning

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Challenges

•  Planning work to avoid conflict, where possible, is better than being in a conflict resolution situation

• Our advice: Investigate and understand the implications of work planning processes with respect to susceptibility to conflict, and agree an appropriate approach with users of the system

3. Work planning

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Challenges

•  Building innovative systems with cutting edge technologies and designs, means you will be charting new territory and encountering unexpected challenges.

• Our advice: Develop a trusted relationship with suppliers to ensure a collaborative approach to resolving issues as they arise.

4. Charting new territory

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GDMS next steps

• Data quality improvement for existing products •  Strategic data enhancements to support new products:

–  additional intelligence (lifecycle, attribution, cross-referencing) –  increasing 3D capabilities –  additional networks

• Operational improvements: – Oracle Database upgrade to 11.2.0.3 – Mid-tier upgrade to WebLogic

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Conclusions

• Cutting edge development requires a strong architectural vision and well managed requirements

• Core technologies must support the non-functional requirements out of the box

• Getting the business processes right is as important as building the right systems

• Understanding the logical data model’s physical implications is critical

• Collaborative supplier relationships are key to success

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“If successful the Ordnance Survey's new geospatial database and data management system will define a best practice for the collection, distribution and use of geospatial data.”

International Data Corporation, 2007

• GDMS operational since July 2011 •  1.2 million Ordnance Survey units of change committed to date • Data, system and process enhancements now in progress for

delivery of new products

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Q&A