Ontologies for Software Engineering and Software Technology 2006 ed. [Kõva köide]

1. Ontological Engineering: Principles, Methods, Tools and Languages		1	(48)
1.1 Introduction		1	(2)
1.2 What Is an Ontology? Viewpoints from a Philosopher and from an Ontology Engineer		3	(2)
1.3 What Are the Main Components of an Ontology?		5	(1)
1.4 Ontological Engineering		6	(2)
1.5 Principles for the Design of Ontologies		8	(1)
1.6 Ontology Development Process and Life Cycle		9	(7)
1.7 Methods, Methodologies, Tools and Languages		16	(22)
1.7.1 Methods, Methodologies and Tools Used for the Whole Ontology Development Life Cycle		16	(6)
1.7.2 Ontology Learning		22	(3)
1.7.3 Ontology Alignment and Merging		25	(6)
1.7.4 Ontology Evolution and Versioning		31	(1)
1.7.5 Ontology Evaluation		32	(2)
1.7.6 Ontology Implementation		34	(4)
1.8 Conclusions		38	(1)
1.9 Acknowledgements		39	(1)
References		39	(10)
2. Using Ontologies in Software Engineering and Technology		49	(54)
2.1 Introduction		49	(1)
2.2 Kinds of Ontologies		50	(7)
2.2.1 Heavyweight Versus Lightweight Ontologies		56	(1)
2.3 A Review of the Uses in SET		57	(16)
2.3.1 Ontology Versus Conceptual Model		63	(1)
2.3.2 Ontology Versus Metamodel		64	(1)
2.3.3 Ontologies in Software Engineering Environments		65	(2)
2.3.4 Representing Ontologies Using Software Engineering Techniques		67	(2)
2.3.5 Experiences and Lessons Learned in Software Engineering Research		69	(4)
2.4 A Proposal of Taxonomy		73	(6)
2.4.1 Ontologies of Domain		74	(2)
2.4.2 Ontologies as Software Artifacts		76	(3)
2.5 Review and Classification of Proposals in the Literature		79	(16)
2.5.1 Proposals of Ontologies of Domain		79	(7)
2.5.2 Proposals of Ontologies as Software Artifacts		86	(9)
References		95	(8)
3. Engineering the Ontology for the SWEBOK: Issues and Techniques		103	(20)
3.1 Introduction		103	(2)
3.2 History and Principles of the SWEBOK Project		105	(4)
3.2.1 Hierarchical Organization		107	(1)
3.2.2 Reference Material and Matrix		108	(1)
3.2.3 Depth of Treatment		108	(1)
3.3 The Ontology of the SWEBOK from a Conceptual and Consensus-Reaching Perspective		109	(3)
3.4 The Ontology of the SWEBOK as a Formal Artifact		112	(2)
3.5 Fundamental Elements of the Ontology of the SWEBOK		114	(5)
3.5.1 Activities, Artifacts and Agents		114	(2)
3.5.2 Models, Specifications and Methods		116	(1)
3.5.3 Theoretical Standpoints and Guidelines		117	(2)
3.6 Conclusions		119	(1)
References		120	(3)
4. An Ontology for Software Development Methodologies and Endeavours		123	(30)
4.1 Introduction		123	(2)
4.2 Ontology Architecture		125	(8)
4.2.1 The Communities Involved		125	(2)
4.2.2 Usage and Ontology Domains		127	(4)
4.2.3 Product and Process		131	(2)
4.3 Endeavour-Related Concepts		133	(9)
4.3.1 High-Level View		134	(1)
4.3.2 The Process Side		135	(2)
4.3.3 The Product Side		137	(3)
4.3.4 The Producer Side		140	(1)
4.3.5 Endeavour-Related Concepts: Conclusion		141	(1)
4.4 Method-Related Concepts		142	(6)
4.4.1 Templates and Resources		142	(1)
4.4.2 Duality in the Method Domain		143	(5)
4.4.3 Applying the Methodology		148	(1)
4.5 Conclusion		148	(1)
References		149	(4)
5. Software Maintenance Ontology		153	(22)
5.1 Introduction		153	(1)
5.2 Software Maintenance		154	(2)
5.3 An Ontology for Software Maintenance		156	(10)
5.3.1 Overview of the Ontology		157	(1)
5.3.2 The System Sub-ontology		158	(2)
5.3.3 The Computer Science Skills Sub-ontology		160	(2)
5.3.4 The Maintenance Process Sub-ontology		162	(3)
5.3.5 The Organizational Structure Sub-ontology		165	(1)
5.3.6 The Application Domain Sub-ontology		166	(1)
5.4. Validating the Ontology		166	(3)
5.4.1 Quality Validation		167	(1)
5.4.2 Relevance Validation		168	(1)
5.5 Putting the Maintenance Ontology to Work		169	(2)
5.6 Conclusion		171	(1)
References		172	(3)
6. An Ontology for Software Measurement		175	(22)
6.1 Introduction		175	(2)
6.2 Previous Analysis		177	(1)
6.3 A Running Example		178	(1)
6.4 The Proposal of Software Measurement Ontology		179	(15)
6.4.1 The SMO		179	(15)
6.5 Conclusions		194	(1)
References		195	(2)
7. An Ontological Approach to SQL:2003		197	(20)
7.1 Introduction		197	(1)
7.2 SQL Evolution		198	(3)
7.3 The Ontology for SQL:2003		201	(8)
7.3.1 The Data Types Sub-ontology		202	(2)
7.3.2 The Schema Objects Sub-ontology		204	(5)
7.4 Example		209	(3)
7.5 Conclusions		212	(2)
References		214	(3)
8. The Object Management Group Ontology Definition Metamodel		217	(32)
8.1 Introduction		218	(1)
8.2 Why a MOF Ontology Metamodel?		219	(3)
8.2.1 Why a Metamodel?		219	(1)
8.2.2 Why MOF?		220	(1)
8.2.3 Why Not UML?		221	(1)
8.3 The Ontology Development Metamodel		222	(13)
8.3.1 RDF/OWL Metamodel		224	(4)
8.3.2 Topic Maps		228	(3)
8.3.3 Common Logic		231	(2)
8.3.4 General Structure of Metamodels		233	(2)
8.4 Profiles and Mappings		235	(7)
8.4.1 The Need for Translation		235	(1)
8.4.2 UML Profiles		236	(2)
8.4.3 Mappings		238	(2)
8.4.4 Mapping CL		240	(1)
8.4.5 Interaction of Profiles and Mappings		241	(1)
8.5 Extendibility		242	(2)
8.5.1 Metaclass Taxonomy		242	(1)
8.5.2 Semantic Domain Models		243	(1)
8.5.3 n-ary associations		244	(1)
8.6 Discussion		244	(1)
8.7 Acknowledgments		245	(1)
References		246	(3)
9. Ontologies, Meta-models, and the Model-Driven Paradigm		249	(26)
9.1 Introduction		249	(4)
9.2 Models and Ontologies		253	(4)
9.2.1 What's in a Model?		253	(2)
9.2.2 What's in an Ontology?		255	(2)
9.3 Similarity Relations and Meta-modelling		257	(5)
9.3.1 Meta-models		258	(2)
9.3.2 Metameta-models		260	(1)
9.3.3 The Meta-pyramid, the Modelling Architecture of MDE		261	(1)
9.4 MDE and Ontologies		262	(8)
9.4.1 Domain and Upper-Level Ontologies		263	(1)
9.4.2 Relationship of Ontologies and System Models on Different Meta-levels		264	(1)
9.4.3 Employing Domain Ontologies in the MDA		265	(2)
9.4.4 Conceptual Benefits of an Ontology-Aware Meta-pyramid		267	(1)
9.4.5 Tools Based on an Ontology-Aware Meta-pyramid		268	(1)
9.4.6 The mega-Model of Ontology-Aware MDE		269	(1)
9.5 Related Work		270	(1)
9.6 Conclusions		271	(1)
9.7 Acknowledgments		271	(1)
References		271	(4)
10. Use of Ontologies in Software Development Environments		275	(36)
10.1 Introduction		275	(2)
10.2 From SDE to DOSDE		277	(2)
10.3 Domain-Oriented Software Development Environment		279	(13)
10.3.1 Domain Ontology in DOSDE		279	(1)
10.3.2 Task Ontology in DOSDE		280	(7)
10.3.3 Mapping Domain and Task		287	(1)
10.3.4 Using Knowledge Throughout the Software Development		288	(4)
10.4 From DOSDE to EOSDE		292	(2)
10.5 Enterprise-Oriented Software Development Environments		294	(6)
10.5.1 Enterprise Ontology		296	(4)
10.6 Tools in DOSDE and EOSDE		300	(5)
10.6.1 Domain Theory Browser		301	(1)
10.6.2 Sapiens: A Yellow Page's Software Tool		302	(2)
10.6.3 RHPIan: A Software Tool for Human Resource Planning		304	(1)
10.7 Conclusion		305	(1)
References		306	(5)
11. Semantic Upgrade and Publication of Legacy Data		311
11.1 Introduction and Motivation		311	(3)
11.2 Global Approach to Database-to-Ontology Mapping		314	(1)
11.3 Mapping Situations between Databases and Ontologies		315	(4)
11.4. The R20 Language		319	(11)
11.4.1 A Mapping Description Specified in R20		320	(1)
11.4.2 Description of Database Schemas		321	(1)
11.4.3 Definition of Concept Mappings		322	(2)
11.4.4 Describing Conditions and Conditional Expressions		324	(1)
11.4.5 Describing Transformations		325	(1)
11.4.6 Attribute and Relation Mappings		326	(4)
11.5 The ODEMapster Processor		330	(1)
11.6 Experimentation: The Fund Finder Application		330	(5)
11.6.1 Ontologies in the Funding Domain		332	(2)
11.6.2 The Presentation Part: Semantic Publishing and Navigation		334	(1)
11.7 Conclusions and Future Work		335	(2)
11.8 Acknowledgements		337	(1)
References		337

Francisco Ruiz is associate professor in the Computer Science Department at the University of Castilla-La Mancha (UCLM) and Vice-Director of the Alarcos Research Group. He has been Dean of the UCLM Computer Science School for seven years and Data Processing Director at the same University for four years. His current research interests include: business process management systems, software process technology and modeling, software maintenance, and software projects planning and managing.



Coral Calero is Associate Professor in the Computer Science Department at the University of Castilla-La Mancha (UCLM). Her research interests are: software quality metrics, quality models, web and portal quality, databases and data warehouse quality and software architectures.



Mario Piattini is a Certified Information System Auditor and a Certified information System Manager by ISACA (Information System Audit and Control Association) as well as a Full Professor in the Department of Computer Science at the University of Castilla-La Mancha, in Ciudad Real, Spain. He leads the ALARCOS research group of the Department of Computer Science at the University of Castilla-La Mancha, in Ciudad Real, Spain. His research interests are: advanced databases, database quality, software metrics, security and audit, software maintenance.