Tuesday, 27 November 2007

Geospatial Knowledge Infrastructures Workshop

I managed to catch some of the Geospatial Knowledge Infrastructures Workshop today, part of the eSI programme and hosted by the Welsh eScience Centre. Here are my quick notes...

Rob Lemmens from International Institute for Geo-Information Science and Earth Observation talked about end-user tools. He outlined the different approaches of corporate/national Spatial Data Infrastructures (SDIs) which is a centralised approach and Web 2.0 which is community driven. SDIs are based on stricter rules for annotation and accuracy tends to be higher than Web 2.0 tools, although this is changing. Rob outlined the need for a semantic interoperability framework (combination of ontologies, their relationships and methods for ontology-based description of info sources - data sets, services etc) and a semantic interoperability infrastructure (comprises framework and the tools to maintain and use the framework as well as the information sources produced within this framework). Rob's presentation also included a slide outlining the characteristics of an ontology which was a good representation and a demonstration of ontology visualisation (same tool which ASSERT is using for clustering?). Rob concluded by summarising what the geospatial community can learn and take from Web 2.0, for example tagging/tag clouds, tools for building ontologies (community tagging e.g Google Image Labeller), instant feedback (e.g. password strength bars when selecting a new password) - on the negative side, community-driven tagging can lead to weak semantics. Rob suggests combining the best of both SDI and Web 2.0 worlds - map the SDI and Web2.0 ontologies to create dynamic annotations of geo sources, thus improving discovery.

Ulrich Bugel from Fraunhofer Institut IITB presented on ontology based discovery and annotation of resources in geospatial applications. Ulrich talked about the ORCHESTRA project (http://www.eu-orchestra.org/) which aims to design and implement an open service-oriented architecture to improve interoperability in a risk management setting (e.g. how big is the risk of a forest fire in a certain region of the Pyrenees in a given season?). This question has spatial references (cross-border, cross-administration); temporal references (time series and prognostics); thematic reference (forest fire); and conceptual reference (what is risk?). ORCHESTRA will build a service network to address these sorts of question. Interoperability is discussed on 3 levels - syntactic (encodings), structural (schemas, interfaces), semantic (meaning). The project has produced the Reference Model for the ORCHESTRA Architecture (RM-OA), drawing on standards from OGC, OASIS, W3C, ISO 191xx, ISO RM-ODP. Many iterations of the Reference Model which led to Best Practice status at OGC. The ORCHESTRA Architecture comprises a number of semantic services: Annotation Service automatically generates meta-information from sources and relates them to elements of an ontology; Ontology Access Service enabling high-level access and queries to ontologies; Knowledge Base Service; Semantic Catalogue Service.

Ian Holt from Ordnance Survey presented on geospatial semantics research at OS. OS has one of the largest geospatial databases, unsurprisingly, with 400 million features and over 2000 concepts. Benefits of semantics research: quality control, better classification; semantic web enablement, semi-automated data integration, data and product repurposing; data mining - i.e. benefits to OS and to customers. OS has developed a topographic domain ontology which provides a framework for specifying content. www.ordnancesurvey.co.uk/ontology. Developed ontologies for hydrology; administrative geography; buildings and places. Working on addresses; settlements; and land forms. Supporting modules on mereology, spatial relations, network topology. Conceptual ontology- knowledge represented in a form understandable by people vs computational topology - knowledge represented in a form understandable by computers. A controlled natural language called Rabbit has been developed - structured English, compilable to OWL. OS is also part of the OWL 1.1. task force to develop a controlled natural language syntax. A project currently underway developing plug in for Protege with Leeds University - allows natural language descriptions and in the back end, will translate into an OWL model. The first release is scheduled for December with further release planned for March 08. Ian also talked about experimental work to semantically describe gazetteers - an RDF version (downloadable?) to represent the data and OWL ontology to describe the concepts. This work includes administrative regions and work underway to include cities etc. Through their work, OS has experienced some problems with RDF - e.g. may degrade performance (they have >10 billion triples); how much is really needed?. Ian described some work on semantic data integration e.g. "find all addresses with a taxable value over £500,000 in Southampton" so looking at how to merge ontologies (i.e. creating another ontology rather than interoperability between the two). Ian briefly covered some lessons learned - ontologies are never perfect and can't offer complete descriptions of any domain; automatic tools are used as far as possible. Ian also describe work on linking ontologies to databases using D2RQ which maps SPARQL queries to SQL, creating "virtual" RDF. Conclusions : domain experts need to be at the centre of the process; technology transfer is difficult - benefits of semantics in products and applications must be clarified.

Alun Preece from Cardiff University presented on an ontology-based approach to assigning sensors to tasks. The idea is to bridge the gap between people out in the field needing to make decisions (e.g. disaster management) and the data/information produced from networks of sensors and other sources. Issues tackled: data orchestration (determine, locate, characterise resources required); reactive source deployment (repurpose, move, redeploy resources); push/pull data delivery. The approach is ontology-centric and involves semantic matchmaking. Work on proof of concept - SAM (Sensor Assignment for Missions) software prototype and integration with a sensor network. This work is funded by US/UK to support military application - intelligence, surveillance and reconaissance (ISR) requirements. The work uses ontologies to specify ISR requirements of a mission (e.g. night surveillance, intruder detection) and to specify the ISR capabilities provided by different asset types. Uses semantic reasoning to compare mission requirements and capabilities and to decide if requirements are satisfied. For example, if a mission requires Unmanned Aerial Vehicles (UAV), the ontology would specify different types of UAV and the requirements of the mission (e.g. high altitude to fly above weather, endurance) and the semantic matchmaking (exact, subsuming, overlapping, disjoint) then leads to a preferred choice. The project has engaged with domain experts to get the information into the ontology and to share conceptualisations. Alun showed the Mission and Means Framework Ontology which is a high-level ontology which is fleshed out with more specific concepts.

Slides from the workshop will be uploaded to http://www.nesc.ac.uk/action/esi/contribution.cfm?Title=832

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