• Deliver More Efficient, Joined-Up Services through Improved Management and Sharing of Data/Information

• “Deliver more, for less”

• Debbie Wilson• Business Consultant• debbie.wilson@snowflakesoftware.com

Need for efficient, joined-up information services

• Increased 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 CSR

• How 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

available– Make it accessible in open, self-describing formats– Develop harmonised data specifications that can be re-used

across the business/domain community– Enable your data to be joined-up with other data sources

Power of Information

• Living in an information/knowledge based economy where timely access to location-based information (i.e. “on-demand”) – via wide variety of channels is essential

• Government data is a key componentof the knowledge economy:– Understanding impacts on environment, health

and welfare, security, transport, leisure & recreation

– Effective evidence-based decision making

– Share information with citizen to ensure engagedin policy-making process and can make moreinformed decisions

– Provide base information which when integrated withother sources can provide new “value-add” information and services

• Billions being spent collecting data to meet specific legislative and business requirements

• Additional costs are being incurred further downstream:

Inefficiencies in existing data exchange processes

Issue Cost

Lack of understanding of what data is already available

Duplicated data collection

Under utilisation of existing data Missed opportunities for developing new/improved data

Data often held offline within individual departments

Large amounts of effort required to discover and gain access to data

Data often published in proprietary or binary formats

Reduces interoperability as requires data conversion and limits ability to develop web services

Lack of formal data modelling in GI community

Inconsistencies between similar data resulting in conversion, cleaning, matching.Difficult to link data together

Current StateData ProvidersThird Party Users

Common Steps involved in Accessing Data

1. Online search to find out what data already exists (e.g. Google, FOI/EIR Registers, organisation websites, thematic portals)

2. If cannot find data – create it3. If data is available contact each data

provider to: 1. Get some test data to see if its fit for

purpose 2. Negotiate access to data (i.e. agree

licensing T&Cs, & costs)4. If data online, register and download data 5. If offline wait for data provider to supply data6. On receipt of data, transform, clean and

integrate data (~25-50% project budget!)7. Finally use it!

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Future Steps involved in Accessing Data

1. Online search to find out what data already exists (e.g. INSPIRE or Member States GeoPortal (or Google)

2. If cannot find data – create it (as probably doesn’t exist)

3. If data is available log-in to: 1. Evaluate data using view services 2. Download data for local use or gain

access to a service to directly access the data in an application

4. Use it!

Power of Information

Transformational GovernmenteGovernment

i2010Lisbon Strategy

INSPIRE DirectiveUK Location Strategy

Information Matters Strategy

SEIS

SISE

Open Standards

OGC

Interoperability

Linked Data

RDF/SPARQLGML Application Schemas

SOAP/REST

Joined-up

Spatial Data InfrastructureSemantic Web

ISO 19100

Web ServicesTransformational WFS

KML

WSDL

Platform Independent Models

OntologiesUML

Vocabularies

Theasuri

Registers

Implementation Models XML/XLink

Harmonised Data Specifications

W3C

Efforts to Improve Data Management and Sharing

Power of Information

Transformational GovernmenteGovernment

i2010Lisbon Strategy

INSPIRE DirectiveUK Location Strategy

Information Matters Strategy

SEIS

SISE

Open Standards

OGC

Interoperability

Linked Data

RDF/SPARQLGML Application Schemas

SOAP/REST

Joined-up

Spatial Data InfrastructureSemantic Web

ISO 19100

Web ServicesTransformational WFS

KML

WSDL

Platform Independent Models

OntologiesUML

Vocabularies

Theasuri

Registers

Implementation Models XML/XLink

Harmonised Data Specifications

W3C

Efforts to Improve Data Management and Sharing

Aim to improve access to data and better integrate/

join-up data

Role of Harmonised Data Specifications

• Many communities are developing common data specifications and adopting open web service standards for sharing location-based data– Environment: INSPIRE Annex Themes Data Specifications– Aviation: Single European Sky Initiative (SESAR) – AIM and WXXM– Earth Systems Science: Observations and Measurements, SensorML, TransducerML – Meteorology and Oceanography: CSML, NCML– Hydrography: WaterML– Geotechnical and Geoenvironmental: GeoSciML, DIGGS– Topographic and Cadastral Mapping: ExM (Eurogeographics), OS MasterMap (GB),

NAS-AAA (Germany), NEN 3610, IMRO, IMKICH, TOP10NL– Building and Urban Modelling: CityGML

INSPIRE Harmonised Data Specifications

• The overarching aim of INSPIRE is to improve the interoperability of a set of core spatial objects that underpin wide range of environmental policy

Article 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 interoperability

• INSPIRE shall define harmonised conceptual data specifications for 34 themes across three Annexes

Scope of INSPIRE Data Specifications

• INSPIRE Data Specifications only define the conceptual models for core spatial (and temporal) object types

• Additional non-spatial information related to the spatial-object type has been deemed out of scope

• These 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

INSPIRE Harmonised Data Specifications

• Harmonised Data Specifications will also define the rules for capturing and encoding the various types of data to be exchanged and used– Rules for assigning object identifiers to objects

– Rules for managing object lifecycles

– Rules for cross-referencing related objects

– Rules for types of spatial and temporal objects to be supported

– Rules for encoding formats to be used to exchange information (i.e. XML/GML)

– Rules for portrayal

– Best practice for managing multi-representations

– Best practice for data transformation and multi-lingual support

But...how will this lead to more efficient, joined-up services • Developing 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 requirements– Where common concepts traverse several domains they can adopt the same

modelling patterns– Data providers can exchange their data in a format that better preserves its

structure and relationships– Allow 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 users– Data is self-describing enabling users (machines and humans) to immediately

understand and use it

Defined by ISO 19107 – temporal schema

Defined by OGC Observations and Measurements

Defined by OGC SensorML

Provides a link to a resource that describes location to which the weather observation applies

Case Study: Met Office

• Met Office currently provides ~650 meteorological products and services for public, Government, business and research customers

• Move away from simply delivering data to end-users to providing direct access services and decision-support applications

– OpenRoads– OpenRunway– SafeSee

• Their legacy systems were also struggling to meet current customer and internal business demands

• As part of their web services infrastructure refresh they were looking for flexible solutions for quickly and efficiently developing and deploying data services

Case Study: Met Office

• Their legacy approach to product/service development was to develop a new data model and transformation scripts and processes for each new product/service

• They are moving towards a model driven approach to product development based on a core set of conceptual models for different components of a forecast, nowcast or time-series observation dataset

• Application specific schema for different services can rapidly developed by combining or extending generic model components together which can then be deployed as web services

Case Study: Met Office

• Using 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 application

• GO Publisher saved Met Office hundreds of developer hours whichwere used to develophigh-quality decision supportapplications

• Adopting model driven approachMet Office can now develop and deploy new customer-focuseddecision-support applications within months

Data Store

SchemaTranslation

Schema Translation

WFS Client

WFS Client

SQL Query

SQL Query

Database Records

Database Records

GML

GML

Data Request

Data Request

Translation Configuration

Database table information

Graphical user interface is used to defined the translation from the storage model to the XML data model.

Translations are uploaded to the server.

GO Publisher can publish the same data in different XML formats for different clients.

Publisher Desktop

Case Study: INSPIRE Annex I testing – Land Registry

For 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

Conclusion• Moving 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 channels

• INSPIRE provides the starting point for having more interoperable, joined up data

• More needs to be done within information communities to ensure that we model the related “business” information so that we can integrate all our data

• If 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