ODE: Ontology-based software Development Environment

Journal of Membrane Science, 2002

Software tools processing partially common set of data should share an understanding of what these data mean. Since ontologies have been used to express formally a shared understanding of information, we argue that they are a way towards Semantic SEEs. In this paper we discuss an ontology-based approach to tool integration and present ODE, an ontology-based SEE.

2005

are systems designed to support software development and maintenance, and also for supporting project control and management. They provide means to integrate developers with the software process and the supporting technology. Since during software development many information resources are produced and used, it is very important to add semantics to them in order to improve the assistance given by the environment. In this context, ontologies are a key enabling technology for Semantic SEEs (SSEEs). A SSEE can be viewed as a SEE in which part of the information handled has associated a formal meaning (semantics), augmenting its tools' ability to work in conjunction with each other and with human developers. This paper discusses how ontologies are used in ODE, an Ontology-based software Development Environment, to make it a SSEE.

2003

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2006

There is now almost unanimous agreement that the object-oriented paradigm, applied to software engineering, is superior to the classical (function-based, procedural) paradigm. On the other hand, the object-oriented software engineering methodologies have been evolved significantly over the last two decades. The advent of Web in general and Semantic Web in particular led, for example, to merging them with the ontologies and appearance of related models and tools. Using ontologies however in the classical object-oriented software development life cycle is still not very well supported by respective research, procedures, techniques and tools. The main idea of this paper is to pay attention to the opportunities for using ontologies in the phase of high-level analysis of object-oriented systems in general and, more specifically, to show how ontologies can be used for converting a problem domain text description into an object model. The object model of a system consists of objects, identified from the text description and structural linkages corresponding to existing or established relationships. The ontologies provide metadata schemas, offering a controlled vocabulary of concepts. At the center of both object models and ontologies are objects within a given problem domain. The difference is that while the object model should contain explicitly shown structural dependencies between objects in a system, including their properties, relationships, events and processes, the ontologies are based on related terms only. On the other hand, the object model refers to the collections of concepts used to describe the generic characteristics of objects in object-oriented languages. Because ontology is accepted as a formal, explicit specification of a shared conceptualization, we can naturally link ontologies with object models, which represent a system-oriented map of related objects, described as Abstract Data Types (ADTs).

2003

One of today's hottest IT topics is integration, as bringing together information from different sources and structures is not completely solved. The approach outlined here wants to illustrate how ontologies [Gr93] could help to support the integration process. The main benefits for an ontology-based approach are the ability to picture all occurring data structures, for ontologies can be seen as nowadays most advanced knowledge representation model the combination of deduction and relational database systems, which extends the mapping and business logic capabilities a higher degree of abstraction, as the model is separated from the data storage its extendibility and reusability

2000

2003

ABSTRACT Resolving conceptual conflicts between formalized ontologies is likely to become a major engineering problem as ontologies move into widespread use on the semantic web. We believe that in the immediate and medium-term future, conflict resolution will require the use of human collaboration, and cannot be achieved by automated methods except in simple cases.

2003

Ontologies can be used in Domain Oriented Software Engineering Environments (DOSEEs) to organize and describe knowledge and to support management, acquisition and sharing of knowledge regarding some domain. However, ontology construction is not a simple task. Thus, it is necessary to provide tools that support ontology development. This paper discusses the use of ontologies to support domain-oriented software development in ODE, an Ontology-based software Development Environment, and presents ODEd, an ontology editor developed to satisfy the requirements for an ontology editor in a DOSEE. These requirements include the definition of concepts and relations using graphic representations, automatic generation of some classes of axioms, derivation of object frameworks from ontologies, and ontology instantiation and browsing.

2005

In this paper we propose software engineering subontology. We called it application-specific ontology, for specific software development. It enables remote team members browsing, searching, sharing, and authoring ontological data under the distributed software engineering projects environment. We transform explicit meaningful human knowledge into application-specific ontology, where knowledge structures and semantics are linked, and we go through a formal hand-shaking agreement establishing process before the semantic contents are updated in ontology repositories. The application-specific ontology is used for communication over project agreement to facilitate better, highly consistent communications and formalized domain knowledge sharing. We assume that object-oriented development is deployed in the distributed projects. The knowledge of object-oriented development formed in the application-specific ontology clarifies the objectoriented development concepts in a machine understandable form. Software agent, for example, can be utilised to extract information.

2007

As software systems become bigger and more complex, software developers need to cope with a growing amount of information and knowledge. The knowledge generated during the software development process can be a valuable asset for a software company. But in order to take advantage of this knowledge, the company must store and manage it for reuse. Ontologies are a powerful mechanism for representing knowledge and encoding its meaning. These structures can be used to model and represent the knowledge, stored in a knowledge management system, and classify it according to the knowledge domain that the system supports. This paper describes the Semantic Reuse System (SRS), which takes advantage of ontologies, represented using the knowledge representation languages of the Semantic Web, for software development knowledge reuse. We describe how this knowledge is stored and the reasoning mechanisms that support the reuse.