Implementing a Linked Data Application

Simply learning how to interpret and manipulate Linked Data could stop with the topics outlined above. The extent to which a language-lab-like platform for learning Linked Data should encompass tools for implementing Linked Data applications is an open question. Whether as part of a tool platform or merely as topics of study, however, the learner should acquire knowledge of the following:

  • Publishing RDF-compatible data on the Web

10 thoughts on “Implementing a Linked Data Application

  1. Hello! I‘m from Shang Hai Library, China. My colleagues and I are very interested in Linked Data and the related technologies. It’s very great that there is a project like this.
    What I mainly focus on currently is the consuming technologies of Linked Data, such as, how to mashup Linked Data from different datasets, how to create RDF Links automatically between them with the tools like SILK, and how to create mappings between different vocabularies with something like R2R Framework.
    I also want to know how the semantic search engine based on Linked Data going to work.

  2. There are many ways to publish RDF data, but the application doesn’t stop at publishing and storing. A summary of types of linked data applications should be provided and each type with at least one example. Here again, I think the examples should contain all steps and codes necessary for learners to replicate and reuse. Linked data is very different from what most people with basic web skills are familiar with, which also requires the examples to be “playable” in order for learners to see what’s under the hook.

  3. Gregg Kellogg comments:
    * Documentation for Ruby adaptations of parallel projects, such as RDF::RDFa, RDF::RDFXML, RDF::Turtle, and SPARQL
    * A potentially useful demonstration project is:
    (It won’t work now, due to the change in the GitHub API). If the library that I use to access the GitHub API were updated, it could probably be resurrected easily enough.
    * I actually developed the GitHub-LOD demo as part of an introductory talk I gave on Ruby RDF:
    * On the RDF WG, Nick Humphrey is a contributor, and uses it for his DBPedia-Lite project:

  4. I like what Cuijuan Xia says – focusing on low-hanging fruit like (s)mashups, this is exactly what we’ve been doing – exploiting vocabulary alignments to dynamically mash data. Easy to do and can offer students a compelling example of why linked data might just be worth the effort.

    Also like the mention of Drupal – you can really use it as an LOD front-end in which pages become concepts. Also could be good to mention the semantic mediawiki extension.

  5. For Digital Libraries and Information Retrieval courses, one or two robust, “hands-on” example applications would be very helpful – covering publishing, storage and other aspects of implementation, as suggested above. I agree with the idea of a diverse library of “playable examples.” Also, “sandbox” applications (implementation walk-throughs?) would be very useful. Students can learn a lot by experimenting and breaking things where there is no risk. It’s a good method for self-assessment on complex material. I could see various content areas pointing to hands-on examples such as a Digital Library application or a retrieval application, where the language is practiced as it is learned, as in a language-lab.

  6. The final version of the Inventory of Learning Topics, with modifications in light of comments received, is posted here:

    The project sponsors are grateful for the input received so far, and they invite additional comments on the page linked above. All additional input will inform future implementation plans for the Learning Linked Data project.

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