Modeling and Inference with Ontologies
Aims: Understanding Web Ontology Language (OWL) modelling with a possible emphasis on its theoretical foundation (within Description Logic); and building a simple model for a real-world scenario using OWL.
Background:
OWL ontologies are basically descriptions of certain enterprises, reminiscent to a database modelling of an enterprise; the advantage of ontologies over databases is the ability to model not only basic individual information but rather semantic connections between entities in the enterprise (e.g., that a certain class of entities is a sub-class of a different class of entities). This gives the user the ability to infer *new* information from existing one (and not only to extract the already existing information).
Ontologies are one of the technologies of the Semantic Web and are currently used extensively in domains such as medicine, biology, and in the general area of digital humanities including archives.
The project will offer students the opportunity to learn some basic concepts behind the rich and fundamental theory of ontologies, namely Description Logic (which are weak versions of first-order logic), and the use of ontology frameworks (for example, Protege) in real (or artificial) data sets.
A successful project will (1) Investigate and understand some basic concepts of the logical theory of Description Logic: syntax and semantics; (2) Define a developed an OWL ontology for a particular chosen domain using the the Protege tool; Or work and possibly extend an existing model, exemplifying sophisticate inferencing in the model; (3) Show the applicability of the ontology as to store and infer new information from existing one. (4) There are two options for this project that a student can take: Option 1: the more logical one; Option 2: the more ontology-engineering one. Both options will have some parts from option 1 and 2, but with a different emphasis.
Early Deliverables
Project plan with tasks and milestones.
An overview of ontologies: what they are, basic technical concepts (RDF,RDFS and basic OWL).
Option 1: An overview of Description Logic that supports ontological reasoning.
Option 2: Gathering of requirements from a user, or justifying such requirements from the perspective of a potential user.
Initial experiments with Protege. And building a preliminary model for the chosen domain. (The project intends to utilise Protege but other available or developed tools for ontology engineering are certainly legitimate.
Final Deliverables
An ontology of the knowledge domain associated with the data set.
Option 2: a web front-end for the data set based on the ontology.
Option 1: A discussion of Description Logic with explicit examples in the ontology constructed.
Option 1: Investigate inferencing algorithms in Description Logic and their run-time complexity.
At least a partial encoding of the data set in the ontology.
Option 1: Exemplifying sophisticated inferencing using Protege (or other selected tools): using restrictions (quantifiers).
Option 2: The report will include examples of usage of the system.
Option 2: The report will include discuss the perceived advantages and disadvantages of using ontology frameworks for representing and querying the chosen data set
Suggested Extensions
Option 2: Connect the ontology to other existing ontologies in related areas.
Option 2: User-friendly interfaces for data representation and querying.
Option 2: Investigate inferencing algorithms in Description Logic and their run-time complexity.
Option 1: User-friendly interfaces for data representation and querying.
Option 1: User-friendly interfaces for data representation and querying.
Option 1: a web front-end for the data set based on the ontology.
Reading
Option 2: Semantic Web for the Working Ontologist. Dean Allemang and Jim Hendler.
Option 1: A Description Logic Primer. Markus Krotzsch, Frantiek Simancik, Ian Horrocks.
Both options: http://protege.stanf
