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Introduction to APIs and Linked Data


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Talk given at Open Knowledge Foundation 'Opening Up Metadata: Challenges, Standards and Tools' Workshop, Queen Mary University of London, 13th June 2012.

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Introduction to APIs and Linked Data

  1. 1. Introduction to APIs and Linked Data Adrian Stevenson Senior Technical Innovations Coordinator Mimas, University of Manchester, UK @adrianstevenson
  2. 2. Benefits of APIs for GLAMs• Cross-searching• Improved resource discovery• Data not trapped in silos• Findability on the Web – Google• Data re-use• Bringing data together - integration• Enhanced services – e.g. Mashups 2
  3. 3. Metadata• What is it? - Data about data• How do you create it? – Catalog card, text editor, Word, Excel, Access, XML Editor….• Do you use standards? – EAD – Encoded Archival Description – Not using standards may have implications for interoperability & sustainability• How do you move it around? – CDs, Email attachments, FTP, APIs 3
  4. 4. What is an API?• „Application Programming Interface‟ – “API is an online interface that allows distributed systems to communicate with one another and exchange information” – “APIs are carefully thought out pieces of code created by programmers .. that allow other applications to interact with their application” 4
  5. 5. APIs• Allow machine readability of data – Typically over the Web• Provide other systems with access to content or functions• Many types – e.g. – Google, Facebook, Flickr, twitter APIs …. – OAI-PMH – Linked Data API, SPARQL – Others include SOLR, SRU, Z39.50, SOAP, …. 5
  6. 6. APIs are Machine to Machine• API is software-to-software interface, not a user interface• E.g. Cinema ticket websites use API: – Sends credit card info to remote application – Remote application sends response back to ticket website saying OK to issue the tickets• User see one interface 6
  7. 7. Historypin 7
  8. 8. Mashups 8Data from
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  10. 10. Twitter API 10
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  12. 12. Open Expenses 12
  13. 13. OAI-PMH• Open Archive Initiative Protocol for Metadata Harvesting• Mechanism for repositories and services to share metadata over the Web• Facilitates cross-searching• Works by use of 6 „verbs‟ – E.g. ListMetadataFormats, ListRecord, GetRecord … – – PMH/2.0/hub?verb=GetRecord&identifier=gb141vbh&metadataPrefix=o ai_dc 13
  14. 14. OAI-PMH: GetRecord 14
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  16. 16. Linked Data“The term Linked Data refers to a set of best practices for publishing and connecting structured data on the Web.”“the Semantic Web is the goal or end result… Linked Data provides the means to reach that goal”From „Linked Data: The Story So Far‟ - Heath, Bizer and Berners-Lee 2009 16
  17. 17. The goal of Linked Data isto enable people to sharestructured data on theWeb as easily as they canshare documents today.Bizer/Cyganiak/Heath Linked Data Tutorial,
  18. 18. Linked Data Design Issues• URIs• LD Design Issues• Triples
  19. 19. URIs and HTTP• “A Uniform Resource Identifier’ (URI) provides a simple and extensible means for identifying a resource” – W3C RFC 3986• HTTP URIs may be „de-referenced‟on the Web• HTTP URIs are used for “real world” things • •
  20. 20. RDF• Resource Description Framework – a language for representing information about resources on the Web – RDF can be used to represent things identified on the Web, even when they cannot be directly retrieved on the Web• Describes relations using „triples‟•
  21. 21. Triples• Triples statements – „Things‟ have „properties‟ with „values‟ – Subject – Predicate - Object Keith Richards Is Member Of The Rolling Stones Repository Provides Access To Archival Resource• Triples are the basis of RDF and Linked Data
  22. 22. Archives Hub Model
  23. 23. From RDF to Linked Data• If something is identified, it can be linked to• We take items from our datasets and link them to items from other datasets BBC Copac VIAF DBPedia GeoNames Archives Hub
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  28. 28. Key Benefit of Linked Data• Web 2.0 mashups work against a fixed set of data sources • Hand crafted by humans • Don‟t integrate well• Linked Data promises an unbound global data space • Easy dataset integration • Generic „mesh-up‟ tools
  29. 29. Benefits for GLAMs• Cross-searching• Improved resource discovery• Data not trapped in silos• Findability on the Web – Google• Data re-use• Bringing data together - integration• Enhanced services 32
  30. 30. Linked Data Challenges• Dirty data, URI persistence• Steep learning curve• Complexity• How sustainable are the data sources?• How scalable are triple stores?• Can you track the provenance of data sources?• Licensing 33
  31. 31. Contact Adrian StevensonMimas, University of Manchester, 34
  32. 32. CC License• This presentation available under creative commons Non Commercial-Share Alike: