Debbie Wilson: Deliver More Efficient, Joined-Up Services through Improved Management and Sharing of Data/Information
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Improved data management and sharing through the use of harmonized data specifications and open standards can enable organizations to deliver services more efficiently with reduced costs. Specifications like INSPIRE define common modeling approaches for environmental data that allow data to be joined from different sources. Case studies show how the Met Office and Land Registry leveraged such standards to build new data services quickly and transform legacy systems. Adopting modular, model-driven approaches facilitates the rapid development and deployment of applications to meet new business and user needs.
Debbie Wilson: Deliver More Efficient, Joined-Up Services through Improved Management and Sharing of Data/Information
- 1. Deliver More Efficient, Joined-Up Services through Improved Management and Sharing of Data/Information“Deliver more, for less”Debbie WilsonBusiness Consultantdebbie.wilson@snowflakesoftware.com
- 2. Need for efficient, joined-up information servicesIncreased pressure both on Government, businesses and research communities to “deliver more, for less”2009 Budget announced that Government has to deliver an additional £5 billion on top of the £30 billion efficiency saving in 2010/2011 CSRHow can data providers and managers and service providers support their organisations to deliver efficiency savings?Improve access to existing data by making it more widely availableMake it accessible in open, self-describing formatsDevelop harmonised data specifications that can be re-used across the business/domain communityEnable your data to be joined-up with other data sources
- 3. Power of InformationLiving in an information/knowledge based economy where timely access to location-based information (i.e. “on-demand”) – via wide variety of channels is essentialGovernment data is a key component of the knowledge economy:Understanding impacts on environment, health and welfare, security, transport, leisure & recreation Effective evidence-based decision makingShare information with citizen to ensure engaged in policy-making process and can make more informed decisionsProvide base information which when integrated withother sources can provide new “value-add” information and services
- 4. Billions being spent collecting data to meet specific legislative and business requirementsAdditional costs are being incurred further downstream:Inefficiencies in existing data exchange processes
- 5. Data ProvidersCurrent StateThird Party UsersCommon Steps involved in Accessing DataOnline search to find out what data already exists (e.g. Google, FOI/EIR Registers, organisation websites, thematic portals)If cannot find data – create itIf data is available contact each data provider to: Get some test data to see if its fit for purpose Negotiate access to data (i.e. agree licensing T&Cs, & costs)If data online, register and download data If offline wait for data provider to supply dataOn receipt of data, transform, clean andintegrate data (~25-50% project budget!)Finally use it!Applications access data from local datastoresData (mainly held offline)
- 6. Data Providers Future StateThird Party UsersSDIDiscovery, Access and View ServicesMobile, Online, Desktop ApplicationsUser Authentication and Access Control (SSO) & Digital Rights ManagementDiscovery, Access &View ApplicationsFuture Steps involved in Accessing DataOnline search to find out what data already exists (e.g. INSPIRE or Member States GeoPortal (or Google)If cannot find data – create it (as probably doesn’t exist)If data is available log-in to: Evaluate data using view services Download data for local use or gain access to a service to directly access the data in an applicationUse it!Harmonised Data SpecificationsData accessible onlineApplications access data from remote datastoresMulti-Org. Data & Service Sharing Agreements
- 7. Efforts to Improve Data Management and Sharing SISEi2010Transformational GovernmentLisbon StrategyeGovernmentInformation Matters StrategyOGCPower of InformationUK Location StrategyW3CSEISJoined-upINSPIRE DirectiveISO 19100Harmonised Data SpecificationsOpen StandardsInteroperabilityPlatform Independent ModelsSemantic WebSpatial Data InfrastructureUMLLinked DataOntologiesImplementation ModelsXML/XLinkRDF/SPARQLKMLGML Application SchemasTheasuriRegistersWeb ServicesVocabulariesTransformational WFSSOAP/RESTWSDL
- 8. Efforts to Improve Data Management and Sharing SISEi2010Transformational GovernmentLisbon StrategyeGovernmentInformation Matters StrategyOGCPower of InformationUK Location StrategyAim to improve access to data and better integrate/ join-up data W3CSEISJoined-upINSPIRE DirectiveISO 19100Harmonised Data SpecificationsOpen StandardsInteroperabilityPlatform Independent ModelsSemantic WebSpatial Data InfrastructureUMLLinked DataOntologiesImplementation ModelsXML/XLinkRDF/SPARQLKMLGML Application SchemasTheasuriRegistersWeb ServicesVocabulariesTransformational WFSSOAP/RESTWSDL
- 9. Role of Harmonised Data SpecificationsMany communities are developing common data specifications and adopting open web service standards for sharing location-based dataEnvironment: INSPIRE Annex Themes Data SpecificationsAviation: Single European Sky Initiative (SESAR) – AIM and WXXMEarth Systems Science: Observations and Measurements, SensorML, TransducerMLMeteorology and Oceanography: CSML, NCMLHydrography: WaterMLGeotechnical and Geoenvironmental: GeoSciML, DIGGSTopographic and Cadastral Mapping: ExM (Eurogeographics), OS MasterMap (GB), NAS-AAA (Germany), NEN 3610, IMRO, IMKICH, TOP10NLBuilding and Urban Modelling:CityGML
- 10. INSPIRE Harmonised Data SpecificationsThe overarching aim of INSPIRE is to improve the interoperability of a set of core spatial objects that underpin wide range of environmental policyArticle 3(7): ‘interoperability’ means the possibility for spatial data sets to be combined, and for services to interact, without repetitive manual intervention, in such a way that the result is coherent and the added value of the data sets and services is enhanced.’To achieve this requires common agreement of the core concepts that need to be modelled and rules for achieving interoperabilityINSPIRE shall define harmonised conceptual data specifications for 34 themes across three Annexes
- 11. Scope of INSPIRE Data SpecificationsINSPIRE Data Specifications only define the conceptual models for core spatial (and temporal) object typesAdditional non-spatial information related to the spatial-object type has been deemed out of scopeThese object types must be defined elsewhere (e.g. Member States, domain communities or by Commission when developing new legislation – e.g. CAFE Directive)INSPIRE is only the starting point for providing interoperable, joined-up data
- 13. INSPIRE Harmonised Data SpecificationsHarmonised Data Specifications will also define the rules for capturing and encoding the various types of data to be exchanged and usedRules for assigning object identifiers to objectsRules for managing object lifecyclesRules for cross-referencing related objectsRules for types of spatial and temporal objects to be supportedRules for encoding formats to be used to exchange information (i.e. XML/GML)Rules for portrayalBest practice for managing multi-representationsBest practice for data transformation and multi-lingual support
- 14. But...how will this lead to more efficient, joined-up servicesDeveloping harmonised conceptual schemas for modelling different data components and using open data exchange formats means:Different information communities can be responsible for managing different object types for specific requirementsWhere common concepts traverse several domains they can adopt the same modelling patternsData providers can exchange their data in a format that better preserves its structure and relationshipsAllow data providers to express relationships to other data components through references to join data together Conceptual model can be automatically transformed into different encoding schemas (e.g. database models, GML schemas)Rapidly develop web services to exchange data with different communities and can develop new, innovative applications for end usersData is self-describing enabling users (machines and humans) to immediately understand and use it
- 15. Defined by ISO 19107 – temporal schema Defined by OGC Observations and MeasurementsDefined by OGC SensorML
- 16. Provides a link to a resource that describes location to which the weather observation applies
- 17. Case Study: Met OfficeMet Office currently provides ~650 meteorological products and services for public, Government, business and research customersMove away from simply delivering data to end-users to providing direct access services and decision-support applicationsOpenRoadsOpenRunwaySafeSeeTheir legacy systems were also struggling to meet current customer and internal business demandsAs part of their web services infrastructure refresh they were looking for flexible solutions for quickly and efficiently developing and deploying data services
- 18. Case Study: Met OfficeTheir legacy approach to product/service development was to develop a new data model and transformation scripts and processes for each new product/serviceThey are moving towards a model driven approach to product development based on a core set of conceptual models for different components of a forecast, nowcastor time-series observation datasetApplication specific schema for different services can rapidly developed by combining or extending generic model components together which can then be deployed as web services
- 19. Case Study: Met OfficeUsing GO Publisher WFS the Met Office were capable of integrating and translating their meteorological data on-the-fly to develop new web services which was deployed within a week of defining requirements for a new service and applicationGO Publisher saved Met Office hundreds of developer hours whichwere used to develop high-quality decision supportapplicationsAdopting model driven approach Met Office can now develop and deploy new customer-focused decision-support applications within monthsPublisher Desktop
- 20. Case Study: INSPIRE Annex I testing – Land RegistryFor more information about how we transformed and published Land Registry data to comply with INSPIRE Implementing Rules go to http://www.snowflakesoftware.com/tv/gpinspire/index.htm
- 21. ConclusionMoving towards using modular, conceptual data specifications and using open data exchange formats will enable organisations to move from simply moving data around to providing on-demand, real-time services which can be consumed simultaneously through multiple channelsINSPIRE provides the starting point for having more interoperable, joined up dataMore needs to be done within information communities to ensure that we model the related “business” information so that we can integrate all our dataIf we do achieve this we will end up in a situation where users will be able to discover and access and use a wide range of information more efficiently – but it does require us to change how we have been managing our data