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Linked dataresearch
 

Linked dataresearch

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Talk at the University of Chile.

Talk at the University of Chile.

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  • Linked data is mainly composed of its Publication, i.e. making your linked data available to the public, and Consumption, for others to consume and use it.
  • Very difficult to integrate data from disparate sources

Linked dataresearch Linked dataresearch Presentation Transcript

  • http://www.enakting.org/
    Linked Data Research @ EnAKTing, Univ. of Southampton   
    Tope Omitola, Univ. of Southampton
    Seminar at Univ. of Chile, Santiago, Chile, 3rd Aug. 2011
    1
  • Items
    What is Linked Data?
    What is EnAKTing?
    Our Areas of Work
    Future Work
  • Data Silos on the Current Web
    API
    HTML
    HTML
    XML
  • What is Linked Data?
    The current Web is a Web of Documents.
    Data, data, everywhere: We are surrounded by data: School performance, car fuel efficiency, etc.
    Data help us to make better decisions.
    You can discern the shape and structure of an entity by looking at the data it generates.
    Data shapes conversations and markets.
  • What is Linked Data?
    Linked Data: Framework where data is a first class citizen on the Web.
    Evolving the current Web into a Global Data Space.
    TimBL: 4 principles of Linked Data:
    Use URIs as names for things, Use HTTP URIs, When someone looks up a URI, provide useful information, using the standards (RDF, SPARQL), Include links to other URIs, so that they can discover more things.
  • What is Linked Data?
    RDF: standard mechanism for specifying the existence and meaning of connections between items.
    RDF links things, not just documents, and they are typed.
  • The Web of Linked Data
    Link everything. No silos.
    Thing
    Thing
    Thing
    Thing
    Thing
    Thing
  • Linked Data
    Advantage comes from linking the RDF(s) together.
    8
  • Linked Data
    In summary:
    Linked Data provides: RDF.
    A standardized data access mechanism, HTTP.
    Hyperlink-based data discovery, using URIs.
    Self-descriptive data, through using shared vocabularies.
  • Publishing your data as Linked Data: Some Things to Consider
    How do you choose a good URI to name things?  There are guidelines for this. Examples:http://dbpedia.org/resource/Wildlife_photography  . Tope Omitola @ Univ of Southampton:http://id.ecs.soton.ac.uk/person/24123 . Sebastian Rios may be this:http://id.dii.uchile.cl/srios.
    Describing a Data Set using: voiD(the Vocabulary of Interlinked Datasets).
    Choosing and Using Vocabularies to Describe Data (SKOS, RDFS, OWL).
    Sourcing datasets: Where do you get the datasets from (e.g. Semantic Web search engines, manual search, etc).
    Choice of join points:  When you have different datasets, where do you join them together.
    Data normalization: using RDF make things easier.
    Alignment of datasets.
  • Alignment of datasets
    11
  • Consuming Linked Data
    How do you visualize linked data sets.
    Linked Data browsers, e.g. Disco, Tabulator.
    Linked Data Search Engines, e.g. Sig.ma, Falcons, Sindice.
    Domain-specific Applications and Mashups, e.g. dayta.me(from Southampton), US Global Foreign Aid Mashup.
  • Government Linked Data
    Explosion of Government Linked Data efforts and projects.
    data.gov, data.gov.uk, data.gov.au
    Examples
  • Examples of Government Linked Data (csv)
  • Examples of Government Linked Data (rdf)
  • What is EnAKTing?
    EPSRC-funded project.
    Addressing 3 key research problems; (1) how to build ontologies quickly that are capable of exploiting the potential of large-scale user participation, (2) how we query an unbounded web of linked data, (3) how to visualise, explore, browse and navigate this mass of data.
    Project Leaders: Prof. Sir Tim Berners-Lee, Prof. Dame Wendy Hall, and Prof. Nigel Shadbolt.
  • Issues we are focusing on
    Findability of appropriate data sources.
    SEARCH: Look at the data sources.
    EXTRACT: Slicing of data sources.
    INTEGRATE: Unifying the views.
    EXPLORE: Answering the questions.
                                                            
  • Our solutions/apps
    backlinks.psi.enakting.org is a service to discover back-links in the Web of Data for the UK Public Sector Information domain.
    geoservice.psi.enakting.org is a service to support the discovery of geographical resources in the Web of Data querying containment relations.
    http://sameas.org/   The Web of Data has many equivalent URIs.This service helps you to find co-references between different data sets.
    http://4sreasoner.ecs.soton.ac.uk/ Scalable Reasoning in 4store; 4sr is a branch of4store where backward chained reasoning is implemented.
  • Our solutions/apps
  • Our solutions/apps
    http://bagatelles.ecs.soton.ac.uk/psi/   brings together a number of public sector information catalogues, such asdata.gov ,data.gov.uk ,data.gov.au.
    http://void.rkbexplorer.com/ : void store :voiD documents describe the contents of data sets within the Web of Data, enabling discovery and reuse ofLinked Data resources. This service simply gathers a number of voiD documents and stores them in a repository, making it easy for clients and applications toquery these descriptions in order to identify which datasets may be of relevance for a particular need or request, or tofind endpoints which may contain a given URI.
    http://apps.seme4.com/see-uk/ : Visualization tool for some UK data
  • Our solutions/apps
  • Our solutions/apps
    http://www.hyperthing.org/:Hyperthing tells whether your requested URI is a thing or a document.
    Visor: a tool for end user data exploration
    http://www.enakting.org/provenance/voidp/voidp: A Vocabulary (Ontology)  for Data and Dataset Provenance.
    http://data.southampton.ac.uk/ :  Open Data Service for the University of Southampton.
  • Some Future Work
    Stream Reasoning.
    Dynamic Data Discovery.
    More work on the HCI, Data Consumption side.