Course 5: Building Linked Data Applications

This learning pathway describes how a Linked Data application is built.

You can study the materials of this learning pathway at your own pace, as there is no predetermined start or end date.

1. Learning outcomes

By the end of this learning pathway you should have an understanding of:

Examples of Linked Data applications and how they can be used.
Different architectural patterns that can be used to build a Linked Data application.
How development frameworks can be used to implement a Linked Data application.
How Web APIs can be used to access data from, or for use in, a Linked Data application.

2. Characterization and Architecture of Linked Data Applications

Learn about the different classifications amd architectures of Linked Data applications.

Watch Part I of the webinar 'Creating Linked Data Applications' (47 minutes):

View the slides of this webinar:

Read Parts I & II of Chapter 5 'Building Linked Data Applications':

3. Linked Data Application Development Frameworks

Learn about various Linked Data Application Development Frameworks, such as the Information Workbench.

Watch Part II of the webinar 'Interaction with Linked Data' (55 minutes):

View the slides of this webinar:

Read Parts III, IV & V of Chapter 5 'Building Linked Data Applications':

4. Test your knowledge

How much have you learned from this learning pathway? Test your knowledge by completing the following exercise.

Execute this set of sample quiries in order to develop Linked Data applications based on our music data example using the Information Workbench.

5. Further reading

If you are interested in more learning materials and resources about building Linked Data applications, here are some suggestions that are relevant to this particular pathway:

[1] Hausenblas, M. (2009). Linked Data Applications. Technical Report, DERI, Galway.

[2] Martin, M. and Auer, S. (2010). Categorisation of Semantic Web Applications. International Conference on Advances in Semantic Processing (SEMAPRO 2010), Florence, Italy.

[3] http://data.gov.uk/apps

[4] http://data.gov.uk

[5] http://catalog.data.gov/dataset

[6] http://www.bbc.co.uk/blogs/bbcinternet/2012/04/sports_dynamic_semantic.html

[7] https://sites.google.com/a/researchspace.org/researchspace

[8] https://confluence.ontotext.com/display/ResearchSpace/RS+Infrastructure

[9] http://www.cidoc-crm.org

[10] https://www.youtube.com/watch?v=HCnwgq6ebAs

[11] http://www.openphacts.org/open-phacts-discovery-platform

[12] Williams A., Harland L., Groth P. et al. (2012). Open PHACTS: Semantic interoperability for drug discovery. Drug Discovery Today, 17 (21-22), 1188-1198.

[13] http://www.fluidops.com/ecloudmanager

[14] http://www.ontotext.com/owlim

[15] http://jena.apache.org/documentation/tdb

[16] https://code.google.com/p/cumulusrdf

[17] http://www.franz.com/agraph/allegrograph

[18] http://virtuoso.openlinksw.com

[19] https://code.google.com/p/rdf3x

[20] http://www.fluidops.com/information-workbench

[21] http://musicbrainz.fluidops.net

[22] http://musicbrainz.fluidops.net/resource/mo:MusicArtist

[23] http://www.fluidops.com/information-workbench/iwb-download

[24] http://help.fluidops.com/help/topic/iwb.help-2.5/help.html