#heweb10 - How I learned to stop worrying and love the semantic web

Four Design Patterns - or How I learned to stop worrying and love the semantic web
TPR / 11:45 am / Monday
Brian Panulla @bpanulla

Why new web?

The SW is INFRASTRUCTURE.

  • a parallel information architecture for smarter apps
  • web content, pages and sites DO NOT need to change to be made ready for the 3.0 Webs

Three things the semantic web is NOT (kinda)

  • it is NOT semantic HTML (thats a collision of terminology … this is a different semantic)
    • Zeldman says WRITE semantic HTML (use lists, use container p, use headers properly, don’t use presentational markup, don’t use br for padding and no tables for non-tabular data)
  • it’s NOT Warmed-over Artificial Intelligence
  • it’s NOT magic

Who cares?

(showing XKCD comic #773 about things on the front page of university websites — vs thins people go to the site looking for).  Everything on the right is semantic stuff!

Semantics

  • explicit meaning of symbols
    • words - usage, connotation
    • images - symbolism
  • become really useful when shared
  • semantics differs from SYNTAX
    • rules of how symbols (words, letters, pictures) can be arranged.
      • I love Sushi.
      • I (heart symbol) sushi.
      • I love Sushi, but not in that way.
      • And who or what is “Sushi”?

Technology Primer

  • RDF: Resource Description Framework
    • RDF is fundamental knowledge representation
      • declares resources
      • specifies properties of resources
    • What is a resource?
      • EVERYTHING is a resource… even properties.
    • URIs
      • resources are identified by a Uniform Resource Identifier (URI)
        • https://www.psu.edu/owl/list.owl#CollegeOfIST
        • https://2010.highedweb.org/sessions.rdf#TPR9
      • can also be round in your XHTML DTD and html tag’s xmlns attribute
    • Triples
      • RDF is expressed as triples:
        • Example 1
          • subject (“Penn State”)
          • predicate (“is a”)
          • object (“University”)
        • Example 2
          • subject (“Brian Panulla”)
          • predicate (“presented at”)
          • object (“High Ed Web Conference”)
      • Triples to Graphs
        • see how data is related
  • Web Ontologies
    • where schemas describe structure, ontologies describe meaning or intended use
    • OWL adds more expressiveness and many aspects of formal logic to RDF
  • On Design Patterns
    • Inspired by book Design Patterns: Elements of Reusable Object-Oriented Software
    • Architectural patterns like MVC

LINKED DATA

  • Linked Data:  Use Cases
    • Publish/Syndicate complete information sets
    • Embedded explicit semantics, unique identifiers
    • have minimal impact to other Web information publishing
    • may be static or dynamically generated
    • EXAMPLES
      • GeoNames (geonames.org)
      • DBPedia (dbpedia.org)
      • Open Rubrics
    • The Linked Data Cloud
      • https://richard.evganiak.de/2007_10_lod (not sure on this URL …. )
    • Weaknesses
      • access control can be difficult for sensitive or confidential
      • damaging to proprietary intellectual property
    • Alternatives
      • serialized data: XML, JSON, CSV (common, structural not semantic)
      • microdata

MICRODATA

  • Best Buy and Overstock have started tagging their products in RDFa
  • Weaknesses
    • XHTML required for RDFa validation
      • new DOCTYPE
      • XML MIME type
  • Alternatives
    • microformats (not discoverable)
    • HTML5 Data attributes - application-level semantics only
    • HTML5 Microdata - easier to read, more verbose elements

CONSUMER

  • Manipulate linked data in a rich client
  • generate multiple presentational forms
  • i.e. Open Rubric Builder
  • Weaknesses
    • processing/bandwidth resources constrained
    • client libraries still maturing
    • constraints of accessibility requirements
  • Alternatives
    • AJAX, AHAH, JSON

SEMANTIC WEB APPLICATIONS

  • Domains where schemas/models change rapidly or data is sparse
  • Semantics of relational model inadequates (e.g. inferencing, inheritance)
  • Domains emphasizing relationships
    • social networks
    • taxonomies
  • Triple Stores
    • database tuned for graphs of RDF statements
    • sometimes a Quad Store (provenance)
    • Popular - Jena, AllegroGraph, Virtuoso
  • Weaknesses
    • bad for opaque objects with few relationships
    • large sets of homogenous objects
  • Alternatives
    • RDBMS
    • NoSQL (document dbs, key/value stores, graph databases)

SPARQL

  • query language for RDF docs
  • grabs all subjects, predicates and objects from RDF document
  • queries are similar to mysql

Higher Education Use Cases

  • Degree Requirements based on class listings
  • Talk to Brian about other use cases … we ran out of time!!

Tweet
Share StumbleUpon It! Del.icio.us reddit

Like this post? Be sure you've subscribed to the .eduGuru RSS feed or email to get all the latest news and articles.


heweb10

Read Related Posts on .eduGuru:

  1. #heweb10 - Learning to love the API
  2. Everything I Wanted to Learn About My Career I Learned From Twitter
  3. Authenticity: What I learned on my winter vacation

This post was written by:

Lacy Tite

Lacy Tite - who has written 10 posts on .eduGuru

Lacy is a web developer for Vanderbilt University (Go 'Dores!) in the  University Web Communications office (which is responsible for the Vanderbilt homepage and all top level pages - as well as providing development, design, content management, communication strategy assistance to the entire Vanderbilt community.)  Follow Lacy: twitter | VU project blog | delicious


Leave a Reply

Spam protection by WP Captcha-Free