Spatial Data to Spatial Knowledge 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

• Chris Gentle – Mercury

• Paul Farrell and Phil Poole - NGIS

• David Purnell – Whelans

• Simon Cope (freelance)

• Maurits van der Vlugt - Mercury

• Yasser Robi – Fugro

• Ralph Croker – SKM

• Mark Judd – Geomatic Technology

• Michael Dixon, Dan Paull - PSMA

• Brad Spencer - SIBA

• Jack De Lange – SIBA

• Simon Jellie – 43pl

• Manu King, Scott Kennedy, Richard Murcott, Femke Reitsma – LINZ, NZ

• Helen Owens, John Weaver – OSP

• Drew Clarke, ANZLIC

• Alan Forghani – MDBA

• Simon Cox, Ryan Fraser, Rob Atkinson, David Lemon – CSIRO

• Andre Zerger, Elizabeth McDonald – BOM

• Chris Pettit - AURIN

• Phil Tickle, George Curran – CRCSI

• Mary Sue Severn – NZ CRCSI

• Franz Eilert – QSIF

• Jace Carson – Uni Canterbury NZ

• Peter Newton – Swinburne

• Chris Bellman – RMIT

• Abbas Rajabifard, Stephan Winter – Uni Melb

• Bruce Thompson (DSE)

• Mike Bradford (Landgate)

• Cathy Crooks, Denise McKenzie – DSE (ANZSM Demonstrator)

• 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

Program 3

crc•si

BoM

DoD DRET

OSP

DIISRTE

ABS

CSIRO ARC DSTO

ANZLiC

VANZi

PSMA

ANZSM

DIGO GA eResearc

h

AURIN Auscope

WA (Landgate, Health etc.)

Victoria (DSE etc.)

Queensland (DNRM etc.)

NSW (LPI etc.)

LINZ

Northern Territory

Tasmania (LIST)

DSEWPC

MDBA TERN

DOHA

AIHW AIMS

SA ACT

ASDI

Google Bing

University Researchers

Yahoo!

Local Authorities

Data

Private sector

The ANZ SI Landscape

Commonwealth

Auscope

ICSM

SIBA AUS

SIBA NZ

SSSI

OGC

ISO

GITA

ANDS

Products

ASDD

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: 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].

Source: T. Berners-Lee (2000)

Linking Data with RDFs

www.example1.org/webapp1#jim = webapp1#jim

From: Hendler, J (2009), Web 3.0 emerging, IEEE Computer

Can do: webapp1:Jim owl:sameAs www.wikipedia.org/en/James_Hendler

Example: Spatial Ontologies

Source: Chin-Te Jung, Chih-Hong Sun, (2010), Ontology-driven Problem Solving Framework for Spatial Decision Support Systems, Proc. GSDI 2010, Singapore.

Spatial Data Supply Chain

After 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 reasoning

After 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

Data stores Queries OGC standards based

data and processing services

Pro

ducts

WFS

WFS

WFS

WMS

WPS

WPS

WPS

SQL,

code

SQL,

code

SQL,

code

SQL,

code

Linking Data & Processes

Landgate DSE LPI PSMA DERM

…

User 1 Catalogues

Ontologies Vocabularies

Metadata

Data

Metadata

HPC

ABS BoM GA Private Sector

…

Collocated data and Processing Modelling and prediction

Data

Data

Data

Data

RDFs - links

Modelling Local processing: Search

Querying

Visualisation Inference

Data Integration

Smarts - code

Search

Modelling

LINZ

… …

SISS SM Others

User 2

SISS SM Others

Querying

Visualisation Inference

Data Integration

Smarts - code

Search

Modelling

Example of the Use of Linked Data

Landgate DSE LPI PSMA DERM

…

User 1 Catalogues

Ontologies Vocabularies

Metadata

Data

Metadata

HPC

ABS BoM GA Private Sector

…

Collocated data and Processing Modelling and prediction

Data

Data

Data

Data

RDFs - links

Modelling Local processing: Search

LINZ

… …

User 2 Consumer wants to

buy a house on the

city edge

How many bush fires have

there been in the local area

in the past 5 years?

• 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 Discovery

Federated models

Orchestration of web services

Crowd sourcing and authoritative data

Querying big data including 3D/4D datasets

Licensing, Copyright and Terms of Use

Mapping to other Market-places and NSGIs

Use

r St

ori

es

Federated Data Integration

Data Integration at the Jurisdictional Level

The Spatial Marketplace

SLIP future

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 Agreement Maker Tool

Isabel Cruz - Ontology Alignment for the Semantic Integration of Heterogeneous Geospatial Data Sets - cruz-xiao-revised.pdf

Isabel Cruz (2004)

Geospatial data

Integration –

cruz.pdf

Orchestration

Source: Chin-Te Jung, Chih-Hong Sun, (2010), Ontology-driven Problem Solving Framework for Spatial Decision Support Systems, Proc. GSDI 2010, Singapore.

Different solutions

Example: Spatial Ontologies

Source: Chin-Te Jung, Chih-Hong Sun, (2010), Ontology-driven Problem Solving Framework for Spatial Decision Support Systems, Proc. GSDI 2010, Singapore.

Ontology-based Problem Solving

Source: Chin-Te Jung, Chih-Hong Sun, (2010), Ontology-driven Problem Solving Framework for Spatial Decision Support Systems, Proc. GSDI 2010, Singapore.

Processing Chains

Data stores Queries OGC standards based

data and processing services

Pro

ducts

WFS

WFS

WFS

WMS

WPS

WPS

WPS

SQL,

code

SQL,

code

SQL,

code

SQL,

code

Linking Data with RDFs

www.example1.org/webapp1#jim = webapp1#jim

From: Hendler, J (2009), Web 3.0 emerging, IEEE Computer

Can do: Webapp1:Jim owl:sameAs www.wikipedia.org/en/James_Hendler