Linked Data Patterns


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Short presentation I gave at the Reading Semantic Web meetup about the Linked Data patterns book.

The talk outlined the major areas in which we can look for patterns and noted some areas for further work.

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Linked Data Patterns

  1. 1. Linked Data PatternsLinked Data Meetup, 25/02/2013@ldodds
  2. 2. What is a Design Pattern?...a general reusable solution to a commonly occurringproblem within a given context...... a description or template for how to solve a problem thatcan be used in many different situations...
  3. 3. Benefits of Design Patterns(General)● Simple focused discussion of a single issue● Encourage discussion of related or complementaryapproaches● Capture successful, oft-repeated designs (and failures)● Build a lexicon: a language for practitioners that improvescommunication
  4. 4. Benefits of Linked Data Patterns● Supplement existing publishing guides & tutorials● Provide clear guidance on common problems & questions● Help people avoid common pit-falls● Improve quality of published data● Lower barrier to entry
  5. 5.
  6. 6. Identifier Patterns● How do we partition a URI space?● How do we use existing keys to build URIs?● How can we make linking easier?● How can we work around lack of stable identifiers forcommon resources?
  7. 7. Modelling Patterns● How do we get the most from a graph based model?● How can we best handle semi-structured and/or multi-lingual data?● How can we describe complex relationships betweenresources?● How can we annotate relationships between resources?
  8. 8. Publishing Patterns● How do we best publish data on the web?● How do we link to other sources of data?● How can we annotate existing data?● How do we link documents and data?● How do we enhance data over time?● How do we remove data from the web?
  9. 9. Data Management Patterns● How can we organise data in a triple store?● What are the different ways in which we can partition agraph to make it easier to manage?● How can we annotate and describe collections of RDFstatements?● How can we track the sources of RDF statements?
  10. 10. Application Patterns● How do we build applications over RDF data?● How do we collect and aggregate data from across theweb (or an enterprise?● How do we validate RDF data?● How do we transform and merge data?
  11. 11. Future Work● Mixed architectures● Data conversion work flows● API design● Data discovery
  12. 12. Book:
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