Use Cases of Applied Ontology in Semantic Web and Big Data

Please capture Use Cases of Applied Ontology in Semantic Web and Big Data on this page.

This has been inspired by the many projects and work that got presented during the course of Ontology Summit 2014: "Big Data and Semantic Web Meet Applied Ontology" and Ken Baclawski (one of the Summit co-champions) proposed that a page like this be created, and be linked to from the OntologySummit2014_Communique.

This will, hopefully, serve as an ongoing registry of such references that the community can continue to build on.

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... please insert below (kindly provide links and identify the poster and principal(s) of each entry for reference and follow-up purposes.)

• Question by Christoph Lange: Are we aiming at collecting means or ends on this page, or both? My understanding of "use case" is that it is about ends, i.e. problems that ontologies help to solve. However in the list below I see a lot of things that rather look like means to me, e.g. "reuse" or "bridge axioms". In what I have so far contributed from Track B I focused on ends rather than means.
  • Response by Ken Baclawski: Perhaps it would be good to subdivide the use cases according to their intent. The ones in Track D were supposed to be about how the ontology community can involve other communities that are concerned with Big Data (very generally defined). They were not supposed to be about actually solving the problems that ontologies help to solve. In other words, the problem being solved is to improve communication between communities, not solving the problems of the communities. However, some of the use cases did cross the line from the one problem to the other problem.

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From the Ontology Summit 2014 Discourse

• Answering questions over a broad domain of knowledge
  • Chris Welty presented Watson as an example (Track B synthesis)

• Building complex interactive web applications
  • MikeBergman presented the Open Semantic Framework (OSF) as an example, where knowledge represented in terms of a uniform RDF data model translates into widgets of web applications, in which ontologies inform interface displays, define component behaviors, guide visualization template selection and content filtering, and help to navigate and organize web portals (Track B synthesis)

• Represent complex knowledge with little ontological commitment
  • MikeBergman (Open Semantic Framework) and JoseMariaGarcia (Linked Services Initiative) pointed out that RDF is a useful knowledge representation model for them. It does not enforce a strong ontological commitment but still allows to link informal descriptions of things to more formal descriptions. (Track B synthesis)

• (From OntologySummit2014 Track-D) Harvest from data partners
  • Rather than build it yourself, make use of collaborators. You still have a lot of work to do converting, formalizing the input and integrating the sources. But the result can be very high quality and it has a builtin user community.
  • Nathan Wilson Presentation gave an example from the EOL community.
  • Mark Fox Presentation
  • Rosario Uceda-Sosa Presentation gave an example of harvesting data and metadata from cities.
  • Ruth Duerr Presentation combined input from native communities in the Arctic.
  • Dan Brickley Presentation described how Schema.org is combining the vocabularies of millions of content providers on the web.

• (From OntologySummit2014 Track-D and Track A Synthesis) Modular development
  • It is much easier to reuse a smaller ontology - part of the Track A theme on reuse. One can combine several of them to create an ontology that satisfies most of your requirements.
  • Ruth Duerr Presentation used this to develop an ontology for sea ice.

• (From Semantic Content Reuse -Track A and from OntologySummit2014 Track-D) Reuse
  • Every speaker in the two Track A sessions had examples of this use case.
  • Every speaker in the two Track D sessions had examples of this use case.

• (From OntologySummit2014 Track-D) Formalize existing informal models
  • Eric Chan Presentation formalized the OODA loop and then extended and generalized it.
  • Ruth Duerr Presentation formalized techniques for describing sea ice conditions.
  • Mark Fox Presentation described specific examples of measurements and indicators, especially the student faculty ratio, that are being formalized.

• (From OntologySummit2014 Track-D) Develop ontology with extension points
  • Eric Chan Presentation developed a framework for observation and decision making

but rather than immediately specializing it to a particular domain, he built his framework with extension points to allow ease of reuse.

• • Malcolm Chisholm Presentation described a framework that is intended to be extended with ontologies.
  • Dan Brickley Presentation described how Schema.org can be extended. This is related to the Vocabulary Pipeline use case.

• (From OntologySummit2014 Track-D) Involve communities
  • This is similar to the Harvest from data partners use case, but was shown separately to emphasize that community involvement is important even if the communities do not directly contribute to the ontology.
  • Ruth Duerr Presentation used this in her work on the ontology of sea ice.
  • Dan Brickley Presentation described how Schema.org was created by an industry collaboration involving a number of large companies.

• (From OntologySummit2014 Track-D) Governance framework
  • This framework uses relatively deep inference using axioms and rules to ensure data quality.
  • The OOR Initiative included gatekeeping and governance as one of the requirements.
  • Malcolm Chisholm Presentation
  • Mark Fox Presentation was also concerned with governance to ensure data quality.

• (From OntologySummit2014 Track-D) Vocabulary pipeline
  • Dan Brickley Presentation

• (From OntologySummit2014 Track-D) Pattern matching
  • Dan Brickley Presentation

• (From OntologySummit2014 Track-D) Information ecosystem
  • Rosario Uceda-Sosa Presentation
  • The SAOCE Presentation describes how PurpleSemanticMediaWiki can be used to create a semantic information ecosystem for collaborative development of documents, ontologies and standards.

• (From OntologySummit2014 Track-D) Bridge axioms
  • Use axioms both at the data and metadata levels to bridge the gap between the semantics of data from different sources.
  • Mark Fox Presentation
  • Rosario Uceda-Sosa Presentation
  • Nathan Wilson Presentation described how one needs bridge axioms not only for relating different ontologies but also to relate different versions of an ontology over time. This is especially true for the ontology of life which has changed dramatically over many centuries.

• Ontologies and design patterns to integrate data from independent sources
  • This is similar to the Track D "Bridge axioms", but relies on mappings from integrating ontologies, and/or common design patterns (Track A presentations)
  • Pascal Hitzler presentation
  • Michel Dumontier presentation
  • Kingsley Idehen presentation

... initial input from Ontology Summit 2014 Track Champions