CeBIT Spatial@gov 2012 - Geoff West, Professor of Spatial Science, Cooperative Research Centre for Spatial Information and Curtin University
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CeBIT Spatial@gov 2012 - Geoff West, Professor of Spatial Science, Cooperative Research Centre for Spatial Information and Curtin University

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    CeBIT Spatial@gov 2012 - Geoff West, Professor of Spatial Science, Cooperative Research Centre for Spatial Information and Curtin University CeBIT Spatial@gov 2012 - Geoff West, Professor of Spatial Science, Cooperative Research Centre for Spatial Information and Curtin University Presentation Transcript

    • Spatial Data to SpatialKnowledge Using the Semantic Web Geoff West Science Director Program 3: Spatial Infrastructures
    • The Team• Prof Geoff West – Science Director, Program 3• Dr TO Chan - Program Director, Program 3• Ms Kylie Armstrong - Program Director (on leave)• Dr David A McMeekin – Senior Research Fellow• Mr Peter Loughrey – Industry Liaison
    • Research Consultation• Commenced January 2012• Initial discussions and landscape/literature search• Consultations with 43plers, jurisdictions, agencies, CSIRO, VANZI, ANZSM, Academia• Joint ANZLIC/CRCSI meeting, April 2012• CRCSI Conference, Brisbane, May 2012• GSDI 2012, Quebec, 2012• Further literature search of main journals/conferences• Research Strategy produced• Workshops in major cities combined with SM• Proposal generation• Overall 300+ individuals consulted
    • Some of the People Consulted• Sonny Tham – Amristar • Simon Cox, Ryan Fraser, Rob Atkinson,• Chris Gentle – Mercury David Lemon – CSIRO• Paul Farrell and Phil Poole - NGIS • Andre Zerger, Elizabeth McDonald – BOM• David Purnell – Whelans • Chris Pettit - AURIN• Simon Cope (freelance) • Phil Tickle, George Curran – CRCSI• Maurits van der Vlugt - Mercury • Mary Sue Severn – NZ CRCSI• Yasser Robi – Fugro • Franz Eilert – QSIF• Ralph Croker – SKM• Mark Judd – Geomatic Technology • Jace Carson – Uni Canterbury NZ• Michael Dixon, Dan Paull - PSMA • Peter Newton – Swinburne • Chris Bellman – RMIT• Brad Spencer - SIBA • Abbas Rajabifard, Stephan Winter – Uni• Jack De Lange – SIBA Melb• Simon Jellie – 43pl• Manu King, Scott Kennedy, Richard • Bruce Thompson (DSE) Murcott, Femke Reitsma – LINZ, NZ • Mike Bradford (Landgate)• Helen Owens, John Weaver – OSP • Cathy Crooks, Denise McKenzie – DSE• Drew Clarke, ANZLIC (ANZSM Demonstrator)• Alan Forghani – MDBA • Matt Higgins – QLD DNRM • Mark Wallace - DCS, Qld
    • Challenges• Many silos of SIs• Bigger diverse market emerging• SMEs need channels to show their wares• Users expect a great experience• Current mindsets
    • The ANZ SI Landscape DoD DSEWPC DOHA DRET DIISRTE LINZ AIHW OSP GA eResearc ARC CSIRO AIMSDSTO DIGO h BoM ANDS ASDD Auscope AURIN TERN Auscope MDBA ABS VANZi University Researchers ASDI Program 3 CommonwealthANZLiC crc•si NSW (LPI etc.) ANZSMICSM WA (Landgate, Health Data etc.) SIBA OGC Victoria (DSE etc.) AUS PSMA Products Local Queensland (DNRM AuthoritiesSIBA NZ ISO etc.) Private sector SSSI GITA Northern Tasmania Territory (LIST) Google Yahoo! Bing ACT SA
    • SI Capabilities
    • Next Generation Spatial Infrastructures - Desires• Easier access to point, vector, polygon, image, raster data• Better access to processes and applications• Smarter search and discovery tools• Ability to publish, sell and buy• Easily understandable licensing rules, terms of use• Better automatic integration of datasets• Better usability by hiding complexity
    • Evolution of The Web SIs now
    • Evolution of The Web SIs in five years
    • The Semantic Web• Automatic discovery of links between consumers, producers, data and processes• Smarts: Source: T. Berners-Lee (2000) Source: M. Coffey, (2007), The future is smart machines (and soup), http://blogs.nesta.org.uk/innovation/2007/07/the-future- is-s.html, [last accessed 30-Nov-2009].
    • Linking Data with RDFs www.example1.org/webapp1#jim = webapp1#jimCan do: webapp1:Jim owl:sameAs www.wikipedia.org/en/James_Hendler From: Hendler, J (2009), Web 3.0 emerging, IEEE Computer
    • Example: Spatial OntologiesSource: Chin-Te Jung, Chih-Hong Sun, (2010), Ontology-driven Problem Solving Framework for Spatial Decision Support Systems, Proc. GSDI 2010, Singapore.
    • Spatial Data Supply ChainAfter Maurits van der Vlugt (2012) Alignment Study of Spatial Data Supply Chains, Phase 1: Alignment Study of Spatial Data Supply Chains, CRCSI.
    • Spatial Data Supply Chain Smarts: URIs, RDFs, Ontologies, Automated reasoningAfter Maurits van der Vlugt (2012) Alignment Study of Spatial Data Supply Chains, Phase 1: Alignment Study of Spatial Data Supply Chains, CRCSI.
    • Linked Spatial Data Supply Chain• Single point(s) of truth• Integrating data• On demand delivery• Different “views” continuously updatable from multiple sources• Same information in many different forms• Automated updating and distribution• Automated input from sensors or volunteered geographic information (VGI)• Different user access paths After Maurits van der Vlugt (2012) Alignment Study of Spatial Data Supply Chains, Phase 1: Alignment Study of Spatial Data Supply Chains, CRCSI.
    • Processing Chains SQL, WFS WPS code SQL, Products WFS WPS code SQL, WFS WPS code SQL, WMS code OGC standards basedData stores Queries data and processing services
    • Ontologies Data Linking Data & Processes Vocabularies User 1 User 2 Metadata Catalogues Data Smarts - code Search Querying Data Integration Inference Modelling Visualisation Collocated data and Processing Data Modelling and prediction RDFs - links SM SISS Others HPC Data Local processing: Modelling SearchMetadata … … … … Data Landgate DSE LPI DERM LINZ PSMA Private Sector ABS GA BoM
    • Data Example of the Use of Linked Data Ontologies Vocabularies Data Metadata Catalogues Consumer wants to User 1 User 2 buy a house on the city edge Smarts - code Search Querying Data Integration How many bush fires have Inference Modelling Visualisation there been in the local area Collocated data and Processing Data in the past 5 years? Modelling and prediction RDFs - links SM SISS Others HPC Data Local processing: Modelling SearchMetadata … … … … Data Landgate DSE LPI DERM LINZ PSMA Private Sector ABS GA BoM
    • • Identified Research Activities: – Search for and discovery of web-based services – Federated data and models – Web service orchestration – Use of crowd sourced data and its integration with authoritative data – Querying big data including 3D and 4D data sets – Licensing, copyright and terms of use – Mapping to other marketplaces and NGSI• Drivers: – Web-based, usability, automation• Domains: – Artificial Intelligence, Semantic Web, Supply Chains
    • • Identified User Scenarios: – Federated Data Integration – Data Integration at the Jurisdictional Level – ANZLIC ASDI – The Spatial Marketplace – SLIP future – User query: How long since this area was last burnt or flooded? – Health – Urban Planning – Biomass Business – Disaster and Emergency Management
    • Mapping Scenarios to Research Research Activities Search and Federated Orchestrati Crowd Querying Licensing, Mapping to Discovery models on of web sourcing big data Copyright other services and including and Terms Market- authoritati 3D/4D of Use places and ve data datasets NSGIs Federated Data Integration   Data Integration at the    Jurisdictional Level The Spatial Marketplace      SLIP future     User Stories User query: Is this area     subject to flooding Health Urban Planning    Biomass Business        Disaster and Emergency       Management
    • From Drivers to Apps
    • Research Principles• Build a pool of spatial talent in Australia and New Zealand• Recognise and use the state of the art as it appears – agile approach• Recognise that the spatial landscape is continually changing• Embrace appropriate external developments such as SISS, eBay, Amazon and Google• Satisfy user stories by building on existing infrastructures – test beds
    • Research Outputs• Tools, techniques and methods for: – Smarter search and discovery – Seamless integration of datasets – Query-based processing of big data – Easier access to data, processes and applications – Easier publishing of data and processes – Helping users decide on licensing, terms of use• Integration of research outputs into applications and deployment• Research graduates and scientific publications
    • Overall Summary• Identified research activities from consultation and literature• Identified user stories from CRCSI participants• Generated a living proposal of the research with a staged approach• Adopting an agile approach with high levels of user involvement• First stage will cover Semantic Search and Federated Models• Second and further stages being formulated
    • Data Integration Maker Tool Agreement Isabel Cruz (2004) Geospatial data Integration – cruz.pdfIsabel Cruz - Ontology Alignment for the Semantic Integration of Heterogeneous Geospatial Data Sets - cruz-xiao-revised.pdf
    • Orchestration Different solutionsSource: Chin-Te Jung, Chih-Hong Sun, (2010), Ontology-driven Problem Solving Framework for Spatial Decision Support Systems, Proc. GSDI 2010, Singapore.
    • Example: Spatial OntologiesSource: Chin-Te Jung, Chih-Hong Sun, (2010), Ontology-driven Problem Solving Framework for Spatial Decision Support Systems, Proc. GSDI 2010, Singapore.
    • Ontology-based Problem SolvingSource: Chin-Te Jung, Chih-Hong Sun, (2010), Ontology-driven Problem Solving Framework for Spatial Decision Support Systems, Proc. GSDI 2010, Singapore.
    • Processing Chains SQL, WFS WPS code SQL, Products WFS WPS code SQL, WFS WPS code SQL, WMS code OGC standards basedData stores Queries data and processing services
    • Linking Data with RDFs www.example1.org/webapp1#jim = webapp1#jimCan do: Webapp1:Jim owl:sameAs www.wikipedia.org/en/James_Hendler From: Hendler, J (2009), Web 3.0 emerging, IEEE Computer