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Lee Iverson - How does the web connect content?
 

Lee Iverson - How does the web connect content?

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    Lee Iverson - How does the web connect content? Lee Iverson - How does the web connect content? Presentation Transcript

    • Semantic Pragmatics Lee Iverson UK Museums and the Web
    • Connecting Museum Museum Users Users ??? ???
    • Why to connect?
      • Referral
        • Let users know about other museums
      • Enhancement
        • Improve information about your collection
      • Personalization
        • Improve relevance to each user
    • The Powerhouse
    • Becoming Connected
      • Expose own data
      • Find other data
      • Integrate
      • Engage with users
    • Exposing Data
      • Museums manage structured, authoritative data about collections
      • but
      • Museum web sites are dominated by presentation and control
      • Results:
        • Museum web data is hermetically sealed
        • User experience is completely controlled
    • Exposing Data
      • Give it away as structured data
        • Must decide private/public boundary
          • Creative commons licensing
        • Easy to do via web (hint: XML or RDF)
      • Benefits:
        • Aggregation possibilities
          • Museum to museum links possible
        • Consumers can repurpose data
        • New uses means new customers
    • How?
      • Add links to structure from:
        • Main page
        • Individual pages
          • Objects and exhibits
        • Visible links?
        • Meta links! (e.g. RSS)
      • Standardize
        • Which standards?
        • Which vocabularies?
    • Standards Strategy
      • Standard = agreement between min. 2 parties to do something in same way
      • Pragmatics:
        • Use existing standards as much as possible
        • Never standardize more than minimum
          • That which is necessary for essential functionality
        • Never standardize vaporware
        • Recognize defacto standards rather than create new ones
    • Is this the Semantic Web?
      • Maybe
        • Meaning vs. Presentation
        • Machine vs. Human
      • Maybe not
        • Where is the meaning ?
        • Where is the reasoning ?
    • Berners-Lee
      • “ I have a dream for the Web [in which computers] become capable of analyzing all the data on the Web – the content, links, and transactions between people and computers. A ‘Semantic Web’, which should make this possible, has yet to emerge, but when it does, the day-to-day mechanisms of trade, bureaucracy and our daily lives will be handled by machines talking to machines. The ‘intelligent agents’ people have touted for ages will finally materialize.”
      • – Tim Berners-Lee, 1999
    • Syntax vs. Semantics
      • In a certain sense structure and vocabulary is the semantics
      • Semantics:
        • Ability to interpret
        • Repurposability
        • Mirroring human interpretation
    • Finding Data
      • Linking to other museums and sites…
      • Spider and scrape
        • Tools: Calais?
        • Unreliable, expensive, needs moderation
      • Rely on structured data
        • RSS or Atom
        • You show me yours…?
    • Integration
      • Relate your content to theirs
        • Relate structure
        • Relate vocabulary
        • Relate context
      • It is possible!
        • Reciprocal Research Network
        • Straight from CMS
        • http://rrnpilot.org
    • Data for Integration
      • XML
      • Information model
      • One syntax
      • Schema from structure
      • Integration by structural integration
      • RDF
      • Data model
      • A few syntaxes
      • Schema from vocabulary
      • Integration by reference
    • RDFa
      • RDF in XHTML:
        • Best of both worlds
        • Microformat-like attributes on XHTML content
        • Need to match XML structure to RDF classes
        • Ordinary web pages can be “data web” pages
    • RDF
      • Resource description framework
      • Metadata language
        • Simple, unambiguous data model
        • Model built on reference , so statements can be detached from their referents
      • Foundation for:
        • RSS – RDF Site Summary
        • DAML+OIL and OWL ( Semantic Web )
    • RDF Model
      • RDF document is set of statements
      • Statement is triple :
        • Subject – a URI reference
        • Property – a URI reference
        • Object – a value (may be URI)
      • RDFS (RDF Schema)
        • Restrict subject/object values based on property
        • Property URI contains description of constraints
    • RDF Example
      • @prefix dc: <http://purl.org/dc/elements/1.1/> .
      • @prefix foaf: <http://xmlns.com/foaf/0.1/> .
      • <http://example.org/> dc:creator _:b .
      • _:b foaf:name &quot;Bob&quot; .
      • “ A person named Bob is the creator of http://example.org”
      http://example.org _:b dc:creator “ Bob” foaf:name
    • RDF Schema Example
      • <rdf:Property rdf:about=&quot;http://xmlns.com/foaf/0.1/name&quot;
      • rdfs:label=&quot;name&quot;
      • rdfs:comment=&quot;A name for some thing.&quot;>
      • <rdfs:range
      • rdf:resource=&quot;http://www.w3.org/2000/01/rdf-schema#Literal&quot;>
      • </rdfs:range>
      • <rdfs:isDefinedBy
      • rdf:resource=&quot;http://xmlns.com/foaf/0.1/&quot;>
      • </rdfs:isDefinedBy>
      • <rdfs:subPropertyOf
      • rdf:resource=
      • &quot;http://www.w3.org/2000/01/rdf-schema#label&quot;>
      • </rdfs:subPropertyOf>
      • </rdf:Property>
    • What About Semantics?
      • DAML+OIL or OWL provide:
        • Vocabulary of basic properties
        • Mappings from these properties to formal semantics
        • Language for defining new, semantically well-defined properties
        • Language for expressing logical inferences that can be made within vocabulary
    • What is an Ontology?
      • Formal (but uninformative):
        • “ A specification of a conceptualization”
      • Informal
        • “ A shared vocabulary designed to support the communication of the meaning of a certain class of resources”
        • “ An attempt to make semantics of a body of knowledge more explicit”
      • Technical:
        • “ A vocabulary and logical inference statements expressed in a formal language (e.g. OWL) for describing a set of resources”
    • A Simple Ontology Cat Dog Cheetah Species category-type category-type category-type Feline Canine Mammal kind-of kind-of kind-of kind-of kind-of disjoint disjoint disjoint hates
    • McBride’s 4 Steps for Widespread Adoption
      • Promote practical applications
      • Develop applications now
      • Simple and tolerant of error
      • Open source
    • Be Wary
      • Berners-Lee’s “Semantic Web” doesn’t yet exist
        • Nothing comes for free
        • Landay’s AI completeness theory
      • But…
        • The data web is useful
        • We can go there now!