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Research 1

Integrating Object-Oriented and Ontological Representations: A Case Study in Java and OWL

author: Bijan Parsia, School of Computer Science, The University of Manchester

Description

The Web Ontology Language (OWL) provides a modelling paradigm that is especially well suited for developing models of large, structurally complex domains such as those found in Health Care and the Life Sciences. OWL’s declarative nature combined with powerful reasoning tools has effectively supported the development of very large and complex anatomy, disease, and clinical ontologies. OWL, however, is not a programming language, so using these models in applications necessitates both a technical means of integrating OWL models with programs and considerable methodological sophistication in knowing how to integrate them. In this paper, we present an analytical framework for evaluating various OWL-Java combination approaches. We have developed a software framework for what we call hybrid modelling, that is, building models in which part of the model exists and is developed directly in Java and part of the model exists and is developed directly in OWL. We analyse the advantages and disadvantages of hybrid modelling both in comparison to other approaches and by means of a case study of a large medical records system.

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Slides
0:00 Integrating Object-Oriented and Ontological Representations
0:36 Overview
1:45 The Problem
3:59 Software Models (1)
4:01 Software Models (2)
6:05 Simple Software Model (1)
6:19 Simple Software Model (2)
6:31 Simple Software Model (3)
6:42 Model-Based Software
8:24 Direct Models
9:07 Indirect Models (1)
9:23 Indirect Models (2)
9:54 Indirect Models: Programmer’s View
10:06 Indirect Models (2)
10:51 Direct Models
11:14 Indirect Models: Programmer’s View
11:26 Indirect Models: Conceptual View
11:42 Software Models
13:08 Static Indirect Models
13:38 Dynamic Indirect Models (1)
13:56 Dynamic Indirect Models (2)
14:14 Dynamic Indirect Models (3)
15:16 Indirect Models
15:48 Dynamic Ontology-Backed Models (1)
16:28 Dynamic Ontology-Backed Models (2)
17:13 Dynamic Ontology-Backed Models (3)
17:24 Dynamic Ontology-Backed Models (4)
17:27 Dynamic Ontology-Backed Models (5)
17:37 Dynamic Ontology-Backed Models (6)
18:08 Direct vs. Ontology-Backed Models
18:20 Dynamic Model Updating
19:05 Domain-Neutral API
19:23 Domain-Specific API
19:29 Instantiation Processing
19:41 Knowledge Engineering by Domain Experts
19:55 Knowledge Encapsulation
20:08 Hybrid Models (1)
20:09 Hybrid Models (2)
20:41 Direct Models
20:52 Indirect Models
21:02 PCM-Style Hybrid Models (1)
22:02 PCM-Style Hybrid Models (2)
22:17 PCM-Style Hybrid Models (3)
22:28 PCM-Style Hybrid Models (4)
23:09 Temporal Slicing (2)
23:48 Temporal Slicing (4)
24:11 Hybrid vs. Other Model Types
25:16 Conclusion
25:32 Hybrid Model Building Framework (5)
26:04 Conclusion

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