Transcript An Internet of Places Making Location Data Pervasive Paul Watson Giuseppe Conti* Federico Prandi* www.1spatial.com © 1Spatial 2010.

An Internet of Places
Making Location Data Pervasive
Paul Watson
Giuseppe Conti*
Federico Prandi*
www.1spatial.com
© 1Spatial 2010. All rights reserved.
* Fondazione Graphitech
Role of Spatial Information
 Location critical to our understanding
and model of the world
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Navigation
Land & Property Management
Environment & Natural Resources
Asset Management
Retail (Logistics/Store Planning)
Defence & Intelligence
Insurance
 £100 billion of business per annum
underpinned by spatial data in UK
alone
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Internet of Places
Point
MultiPoint
LineString
MultiLineString
Polygon
Polygon (holes)
MultiPolygon
Collection
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Use Case
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Objectives
 Spatio-temporal fabric for Web content
 Discover content from all sources – real-time/static
 “Spatialise” existing Web content
 Allow spatio-temporal data to merge with other data
 Bridge structured, semi-structured and unstructured data
 Change metaphor from keyword search to virtual exploration
 Manufacture (join) spatio-temporal data on-demand
 Present spatio-temporal data useably (devices)
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Dependencies
 Common data model for spatio-temporal and all other data
 Semantic spatio-temporal search (space – time – task)
 Flexible data enrichment services
 Flexible data adaptation services
 Orchestration services
 Augmented reality & Semantic 3D GeoBrowsers
 many commonalities with SOA-based spatial data supply chain
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Semantic Web - Vision
 The Semantic Web provides a
common framework that allows
data to be shared and reused
across application, enterprise, and
community boundaries. (2001)
 The first step is putting data on the
Web in a form that machines can
naturally understand, or converting
it to that form. This creates what I
call a Semantic Web – a web of
data that can be processed directly
or indirectly by machines. –
Weaving the Web (2000)
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RDF & SPARQL
Subject
Predicate
Object
 RDF - Machine-readable, triples (subject-predicate-object – all
URI’s)
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Subject:Cambridge – Predicate:isInCounty – Object:Cambridgeshire
Single uniform data model for all information
Look up every URI in an RDF graph over the Web
Information merges naturally
Set RDF links between data from different sources
Represent scattered information in a single model
Schema languages (RDF-S & OWL) allow tightly structured data,
unstructured data or anything in between
 SPARQL - W3C Query language and protocol to select parts of
RDF graphs
 globally unambiguous queries
Linked Data Relationship to Semantic Web
 Futureproofing data
access
 Compatibility with
machine reasoning
(RIF, OWL)
 “Upgrade” existing
data sources with
new “firmware”
Why Linked Data?
 Equally applicable to unstructured, semi-structured, and structured data
and content
 Elimination of internal data 'silos'
 Automatic Integration of internal and external data
 Easy linking of enterprise, industry-standard, open public and public
subscription data
 Complete data modelling of any legacy schema
 Flexible and easy updates and changes to existing schema
 An end to the need to re-architect legacy schema resulting from changes to
the business or M & A
 Report creation and data display based on templates and queries, not
requiring manual crafting
 Flexible data access, analysis and manipulation - user level
 Internal linked data stores can be maintained by existing DBA procedures
and assets
Linking Open Data cloud diagram
Web Information Retrieval
Limitations of Keyword Search
 Requires that search can be expressed in pre-arranged
keywords e.g. Olympic Games
 Inadequate for concepts which are not readily expressible in
keywords, like time & space e.g. events within 10 miles of
Cambridge city centre, in the last 30 mins
 Returns whole documents
 Not “joined up” – manual integration
 Rudimentary presentation – not contextual
 But – contrast the traditional SDI approach
(Cathedral not Bazaar)
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GeoCrawling & Indexing
Tags
Africa
Precipitation
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Flexible Semantic Search – finding tags
Materials
Hazardous
Alkali Metals
Relevant ontology set
Inferred from user’s task
Phosphorous
Chlorine
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Recognising Implicitly Spatio-temporal Content
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Geoparsing
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Federated Search - DNS
Dynamic
Sensors
Social
Data Expiry
Master
Static
B2B
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Presentation
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Content Adaptation
Rich client
Navigation
Raster Only
Thin client
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Conceptual Architecture
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unlocking data,
empowering
business
thank you for listening