Ontology Modularization

The goal of this research is to create a reference data model for educational and research institutes of Iranian Ministry of Sciences, Research, and Technology. After investigating existing technologies and considering the problem context, ontology was chosen as the data model format. In order to create the target ontology, an ontology construction methodology was designed and implemented. This methodology is created using design science research method and contains an architecture, a detailed workflow process, a guideline for performing 1each step, and related softwares in an integrated web-based system. The designed system is implemented in PHP and is available as open source. The system is used as the main tool to construct the target ontology. The proposed methodology leverages the three main knowledge sources including textual documents, existing ontologies in the higher education domain, and reverse engineering of a relational database of an integrated university system. The resulted product of this methodology was evaluated based on the data requirements of the Ministry of Sciences, Research, and Technology, and its shortcomings were resolved. The novelty of this work is both on the generated product, that is, a localized reference data model, and an ontology construction methodology.

Ontology engineering on the web requires a well-defined ontology module system that allows sharing knowledge. This involves declaring modules that expose their content through an interface which hides the way concepts are modeled. We provide a straightforward syntax for such modules which is mainly based on ontology alignments. We show how to adapt a generic semantics of alignments so that it accounts for the hiding of non-exported elements, but honor the semantics of the encapsulated ontologies. The generality of this framework allows modules to be reused within different contexts built upon various logical formalisms.

Ontology engineering on the web requires a well-defined ontology module system that allows sharing knowledge. This involves declaring modules that expose their content through an interface which hides the way concepts are modeled. We provide a straightforward syntax for such modules which is mainly based on ontology alignments. We show how to adapt a generic semantics of alignments so that it accounts for the hiding of non-exported elements, but honor the semantics of the encapsulated ontologies. The generality of this framework allows modules to be reused within different contexts built upon various logical formalisms.

This paper describes a new formalism based on multi-level networked knowledge (MLNK), a combination of different ontologies describing heterogeneous and complementary domains aligned with semantic correspondences. Ontology alignments make explicit the correspondences between terms from different ontologies and must be taken into account in reasoning, where two explicit form of correspondences are given: mappings represent predefined relations such as subsumption, equivalence, or disjointness, that have a fixed semantics in all interpretations; as well as links that can relate complementary ontologies by introducing terms defined by experts, and their semantics varies according to interpretations. The proposed MLNK formalism can be transformed into a Distributed System capable of supporting DDL semantics. It permits to apply a contextual reasoning where ontologies and alignments by pairs of ontologies are developed in different and incompatible contexts. The semantic of the proposed formalism is extensively described along with an illustrative example.

This paper presents an ontology web server project in Web 2.0 that allows the collaborative devel opment of ontologies. The levels of presenting ontologies and mathematical models underlying these presen tations are discussed. The CASL language (Common Algebraic Specification Language) is reviewed.

Abstract. Ontology Modularization is one of the techniques that bear good promises of effective help towards scalability in ontology design, use, and management. The development of proper ontological modules should provide a mechanism for packaging coherent sets of concepts, relationships, axioms, and instances, and a means for reusing these sets in new environments, possibly heterogeneous with respect to the environment the modules were first built. The main contribution of this paper is to describe an approach for ...

Ontology partitioning is a good solution to overcome challenges of large ontologies such as reusability, scalability, complexity and maintenance. The languages of ontology such as OWL do not allow partial reuse and one must use the whole ontology. The problem is that processing large ontologies consumes more time and space than processing only parts of ontologies. To produce high quality modules, one must consider both semantic and structure of an ontology. In this paper, we partition a given ontology according to its semantic and structure to accomplish reusability. Semantic is considered according to weights given to different relationships, and random walk distance is used to maintain a balance between semantic and structure. In our work, more relationships are taken into account than other approaches that only consider hierarchical relations. We propose an agglomerative and a heuristic algorithm to partition ontologies. Our methods produce meaningful modules and reduce required time and space to process an ontology.

In this paper we present the results of our work on s-module (semantic modules) framework. The framework, introduced recently, consists of a high-level semantic description of a modular knowledge base accompanied by an algebra for manipulating module contents. The main contribution of the article is the presentation of the process of expressing Distributed Description Logics knowledge base within the s-module framework. As the two methods exhibit two different approaches to modularization, analysis of this procedure is helpful in capturing the specifics of DDL, comparing it to other methods, and discussing the completeness of the s-module framework.

Tool support-Protégé plugin ProSÉ Operative for last version of Protégé 4 (builds 60 to 62) Takes advantage of the OWL API features Introduction Motivation Formalisms Our methodology Tool Experiments Juvenile Rheumatoid Arthritis Ontology (JRAO) NCI JRAO Galen Arthropathy Arthritis Autoimmune Disease Rheumatologic Disorder Atrophic Arthritis Polyarthritis Rheumatoid Arthritis Juvenile Chronic Polyarthritis Juvenile Rheumatoid Arthritis Arthritis diseases C1. .. C7 Joints Drugs a ff e c ts isT rea ted By Provides access to well-established knowledge Doesn't require expertise in drugs, proteins, anatomy etc. Guarantees to provide [safe] Importing terms doesn't change their meaning. [eco] Import all relevant parts of external ontologies but as little as possible. [aux] The order of imports doesn't matter. Provides access to well-established knowledge Doesn't require expertise in drugs, proteins, anatomy etc. Guarantees to provide [safe] Importing terms doesn't change their meaning. [eco] Import all relevant parts of external ontologies but as little as possible. [aux] The order of imports doesn't matter.

The Semantic Web and ontologies have received increased attention in recent years. The delivery of welldesigned ontologies enhances the effect of Semantic Web services, but building ontologies from scratch requires considerable time and effort. Modularizing ontologies and integrating ontology modules to a given context help users effectively develop ontologies and revitalize ontology dissemination. Therefore, various tools for modularizing ontologies have been developed. However, selecting an appropriate tool to fit a given context is difficult because the assumptions for the approaches greatly vary. Therefore, a suitable framework is required to compare and help screen the most suitable modularization tool. In this research, we propose a new evaluation framework for selecting an appropriate ontology modularization tool. We present three aspects of tool evaluation as the main dimensions for the assessment of modularization tools: tool performance, data performance, and usability. This study provides an implicit evaluation and an empirical analysis of three modularization tools. It also provides an evaluation method for ontology modularization, enabling ontology engineers to compare different modularization tools and easily choose an appropriate one for the production of qualifying ontology modules. The experimental results indicate that the proposed evaluation criteria for ontology modularization tools are valid and effective. This research provides a useful method for assessing and selecting ontology modularization tools. Modularization performance, data performance, and usability are the three modularization aspects designed and applied to the context of ontology. We provide a new focus on the comprehensive framework to evaluate the performance and usability of ontology modularization tools. The proposed framework should be of value to both ontology engineers, who are interested in ontology modularization, and to practitioners, who need information on how to evaluate and select a specific type of ontology tool in accordance with the requirements of the individual environment.

There is a diversity of ontology languages in use, among them OWL, RDF, OBO, Common Logic, and F-logic. Related languages such as UML class diagrams, entity-relationship diagrams and object role modelling provide bridges from ontology modelling to applications, e.g. in software engineering and databases. Another diversity appears at the level of ontology modularity and relations among ontologies. There is ontology matching and alignment, module extraction, interpolation, ontologies linked by bridges, interpretation and refinement, and combination of ontologies. The Distributed Ontology, Modelling and Specification Language (DOL) aims at providing a unified meta language for handling this diversity. In particular, DOL provides constructs for (1) "as-is" use of ontologies formulated in a specific ontology language, (2) ontologies formalised in heterogeneous logics, (3) modular ontologies, and (4) links between ontologies. This paper sketches the design of the DOL language. DOL will be submitted as a proposal within the OntoIOp (Ontology Integration and Interoperability) standardisation activity of the Object Management Group (OMG).

In this paper we present the results of our work on s-module (semantic modules) framework. The framework, introduced recently, consists of a high-level semantic description of a modular knowledge base accompanied by an algebra for manipulating module contents. The main contribution of the article is the presentation of the process of expressing Distributed Description Logics knowledge base within the s-module framework. As the two methods exhibit two different approaches to modularization, analysis of this procedure is helpful in capturing the specifics of DDL, comparing it to other methods, and discussing the completeness of the s-module framework.

Abstract. As the Semantic Web emerges the problem of semantic heterogeneity is becoming more acute. Ontology matching techniques aim at tackling this problem by establishing correspondences between elements of the ontologies. These techniques rely on distance metrics, often called (dis) similarity measures, to assess the similarity of elements within the ontologies. Most of these approaches are either terminological, structural and/or extensional. However, recently some proposals for semantics-based measures have been ...

Abstract. Ontology Modularization is one of the techniques that bear good promises of effective help towards scalability in ontology design, use, and management. The development of proper ontological modules should provide a mechanism for packaging coherent sets of concepts, relationships, axioms, and instances, and a means for reusing these sets in new environments, possibly heterogeneous with respect to the environment the modules were first built. The main contribution of this paper is to describe an approach for ...

Ontology partitioning is a good solution to overcome challenges of large ontologies such as reusability, scalability, complexity and maintenance. The languages of ontology such as OWL do not allow partial reuse and one must use the whole ontology. The problem is that processing large ontologies consumes more time and space than processing only parts of ontologies. To produce high quality modules, one must consider both semantic and structure of an ontology. In this paper, we partition a given ontology according to its semantic and structure to accomplish reusability. Semantic is considered according to weights given to different relationships, and random walk distance is used to maintain a balance between semantic and structure. In our work, more relationships are taken into account than other approaches that only consider hierarchical relations. We propose an agglomerative and a heuristic algorithm to partition ontologies. Our methods produce meaningful modules and reduce required time and space to process an ontology.

Modularity is a key requirement for collaborative ontology engineering and for distributed ontology reuse on the Web. Modern ontology languages, such as OWL, are logic-based, and thus a useful notion of modularity needs to take the semantics of ontologies and their implications into account. We propose a logic-based notion of modularity that allows the modeler to specify the external signature of their ontology, whose symbols are assumed to be defined in some other ontology. We define two restrictions on the usage of the external signature, a syntactic and a slightly less restrictive, semantic one, each of which is decidable and guarantees a certain kind of "black-box" behavior, which enables the controlled merging of ontologies. Analysis of real-world ontologies suggests that these restrictions are not too onerous.

Innovation is currently recognized as an essential competitive enabler for any organization that wants to survive and grow. In addition, organizations feel a growing need to open up their internal innovation processes and to integrate innovation management tools. But, due to the distributed and heterogeneous characteristics of innovation knowledge, it becomes more difficult to manage the innovation process effectively and efficiently. However, the emerging and rapid development of semantic web technologies brings new opportunities. In this paper, a novel modular ontology that provides a semantic representation of innovation and a common language to foster interoperability, declarativity, and intelligent services between tools and to support the innovation life cycle is introduced. Our Innovation Management Ontology consists of three sub-ontologies that refer to three factors, which are: innovation core -Idea-, innovation actor and innovation context, we have identified as cornerstones of any successful innovation. 

Abstract. As the Semantic Web emerges the problem of semantic heterogeneity is becoming more acute. Ontology matching techniques aim at tackling this problem by establishing correspondences between elements of the ontologies. These techniques rely on distance metrics, often called (dis) similarity measures, to assess the similarity of elements within the ontologies. Most of these approaches are either terminological, structural and/or extensional. However, recently some proposals for semantics-based measures have been ...

Ontology Modularization is one of the techniques that bear good promises of effective help towards scalability in ontology design, use, and management. The development of proper ontological modules should provide a mechanism for packaging coherent sets of concepts, relationships, axioms, and instances, and a means for reusing these sets in new environments, possibly heterogeneous with respect to the environment the modules were first built. The main contribution of this paper is to describe an approach for extracting views from domain ontology using existential dependency (ED) by reverse engineering process. The extraction process based on ED could provide a coherent fragment of ontology parts together with transitive closure of dependant parts. The goal of reverse engineering process is to output a possible conceptual model, which is more readable to extracting the views, on the basis of the code in which the ontology is implemented. Thus, a set of translation rules is used to conv...

Abstract. Modularization is a key requirement to manage the size and complexity of large ontologies by replacing each one by a set of smaller ontologies. Two reasons for this requirement are that current ontology languages such as OWL do not allow partial reuse of ontologies and ontologies are ever growing to cover more knowledge in a specific domain. Many existing modularization methods focus on either semantics or structural aspects of ontologies while both of them are important. In this paper, we consider both semantic and structure by combining these aspects using random walk algorithms to achieve a balance between them. We also define weights for different relations to take semantic into account. The proposed method is designed using two algorithms: a greedy algorithm and a heuristic one to reduce run-time and time-complexity. Our goal is to produce reusable modules of high quality and support large ontologies. The results of the experiments show that our algorithms perform wel...

In this paper, we present a novel structure-based partitioning algorithm opportunely designed to break a large ontology into different modules related to specific topics for the domain of interest. The main idea behind our work is to exploit topological properties of the ontology graph and several techniques derived from Network Analysis to produce an effective partitioning without considering any information about semantics of ontology relationships. Several preliminary experiments conducted to validate the effectiveness of our approach are also reported.

With the growth rate of information repositories, most of the current research effort are focusing on improving the accuracy in searching and managing information (especially text data), because of lacking of adaptive knowledge representation to the information content of these systems. Besides, domain knowledge is evolving and consequently, ontologies should be automatically built and extended. Thus, introducing modularity paradigm in ontology engineering is now important to tackle scalability problems. In this paper, we address the problem of representing modular ontologies at an abstract level that can improve the traditional information system with higher efficiency, in the context of previous work aiming at integrating ontology learning in traditional Information Retrieval systems on the web. The contribution consists in organizing ontology elements into semantic three-layered ontology warehouse (topic classification, domain knowledge representation, and module representation). The proposed model has been applied for textual content semantic search and relevance improvement has been observed.

With the growth rate of information repositories, most of the current research effort are focusing on improving the accuracy in searching and managing information (especially text data), because of lacking of adaptive knowledge representation to the information content of these systems. Besides, domain knowledge is evolving and consequently, ontologies should be automatically built and extended. Thus, introducing modularity paradigm in ontology engineering is now important to tackle scalability problems. In this paper, we ...

To deal with autonomous agents’ knowledge and subjective beliefs in the open, heterogeneous and inherently distributed settings concerned by Agreement Technologies, we need special formalisms that combine knowledge, taking also into account disagreements and heterogeneity from multiple interconnected contexts. For agents to reason jointly, they need to combine knowledge by means of correspondences and links between context elements. Each context contains a chunk of knowledge dening a logical theory, that we call ontology or ontology unit.

Many real-world ontologies contain thousands of terms and are developed by multiple participants. The use of monolithic ontologies can cause problems that affect various stages of the ontology life cycle. Thus, there is an urgent need for tools and methodologies that facilitate modular ontology design. The benefits of a modular approach include division of labor, scalability, partial reuse, and broadened participation. This article presents a methodology for modular ontology development. The main idea is to facilitate an interoperable hierarchical network of ontology modules. Modules are designed as a combination of more abstract modules in higher levels of the hierarchy. This methodology differs from previous methodologies in the way that it defines concrete development steps, to facilitate use by both naive and expert ontology developers. This methodology is also supported by ontology design patterns and a prototypical ontology development tool.

This paper describes a new formalism based on multi-level networked knowledge (MLNK), a combination of different ontologies describing heterogeneous and complementary domains aligned with semantic correspondences. Ontology alignments make explicit the correspondences between terms from different ontologies and must be taken into account in reasoning, where two explicit form of correspondences are given: mappings represent predefined relations such as subsumption, equivalence, or disjointness, that have a fixed semantics in all interpretations; as well as links that can relate complementary ontologies by introducing terms defined by experts, and their semantics varies according to interpretations. The proposed MLNK formalism can be transformed into a Distributed System capable of supporting DDL semantics. It permits to apply a contextual reasoning where ontologies and alignments by pairs of ontologies are developed in different and incompatible contexts. The semantic of the proposed formalism is extensively described along with an illustrative example.

In a turbulent and more competition-oriented environment, organizations need to develop their ability to adapt quickly. To be able to adapt, an organization must, of course, be innovative and attractive, and successful innovation should be carefully planned and efficiently managed. Even if some researchers treat the early stages of innovation as "fuzzy" because of their uncertainty, we suppose, as many others that a well structured processes, a clear representation and a good designed management framework are crucial for the ultimate success of any innovation. Understanding the process of innovation is to understand the factors that facilitate and inhibit the success of innovations. A best understanding of how these factors are related will lead to define a proper representation and an efficient management framework supporting the innovation full lifecycle. In addition, organizations have become more aware of external knowledge and technology to maintain their competitiveness in the global market and they feel a growing need to open up their innovation processes. Therefore, to achieve successful innovation in an open context, it is necessary to overcome the challenge of integrating distributed and heterogeneous knowledge management systems. The emerging and rapid development of semantic technologies brings new opportunities and provides a promising direction for such challenge. Semantic technologies focus on the formalization of knowledge to create schemes that allow knowledge to be effectively stored, modified, shared, exchanged and reasoned. In this paper, a semantically-powered framework for innovation management is presented. This framework includes a new Lifecycle Model supporting all activities of innovation with a special focus on its front end stages; a Semantic Representation of innovation, based on three factors we have identified as cornerstones of any successful innovation and that supports a set of automatic and intelligent services such as annotation, relationship retrieval and semantic search; used to power the Core Services of our framework that aim to promote innovation, notably within an open context.

Innovation is currently recognized as an essential competitive enabler for any organization that wants to survive and grow. In addition, organizations feel a growing need to open up their internal innovation processes and to integrate innovation management tools. But, due to the distributed and heterogeneous characteristics of innovation knowledge, it becomes more difficult to manage the innovation process effectively and efficiently. However, the emerging and rapid development of semantic web technologies brings new opportunities. In this paper, a novel modular ontology that provides a semantic representation of innovation and a common language to foster interoperability, declarativity, and intelligent services between tools and to support the innovation life cycle is introduced. Our Innovation Management Ontology consists of three sub-ontologies that refer to three factors, which are: innovation core-Idea-, innovation actor and innovation context, we have identified as cornerstones of any successful innovation. 

Ontologies are the core component in semantic Web applications. The employment of an ontology building method affects the quality of ontology and the applicability of ontology language. A weighted evaluation approach for ontology building guidelines is presented in this paper. The evaluation criteria are based on an existing classification scheme of a semiotic framework for evaluating the quality of conceptual models. Directions for further refinement of ontology building methods are discussed.

In the last two decades several methodologies to assist the ontology development process have been reported in the literature. However, despite important advances, there are no computational tools supporting them yet. Thus, when an ontology development process ends, the things that remain are just design products (e.g., competency questions, class diagrams, implementations, etc.), without an explicit representation of how they were obtained. This paper presents a framework meant to explicitly capture and trace ontology development processes (the activities carried out, the actors executing them, etc.), along with their associated products.

This paper introduces 'just enough' principles and 'systems engineering' approach to the practice of ontology development to provide a minimal yet complete, lightweight, agile and integrated development process, supportive of stakeholder management and implementation independence.

Ontology partitioning is a good solution to overcome challenges of large ontologies such as reusability, scalability, complexity and maintenance. The languages of ontology such as OWL do not allow partial reuse and one must use the whole ontology. The problem is that processing large ontologies consumes more time and space than processing only parts of ontologies. To produce high quality modules, one must consider both semantic and structure of an ontology. In this paper, we partition a given ontology according to its semantic and structure to accomplish reusability. Semantic is considered according to weights given to different relationships, and random walk distance is used to maintain a balance between semantic and structure. In our work, more relationships are taken into account than other approaches that only consider hierarchical relations. We propose an agglomerative and a heuristic algorithm to partition ontologies. Our methods produce meaningful modules and reduce required time and space to process an ontology.

Aspect-Oriented Programming (AOP) provides new constructs and concepts to handle secondary requirements in applications. Secondary requirements, i.e. crosscutting concerns, of the Internet of things (IoT) applications is inherited from the nature of the complexity of interactions, and implementation crosscutting concerns over core IoT architecture. Realizing the full potential of the IoT application requires a new abstraction design technique. This paper proposes an abstract class element toward a design approach to providing better means better separation of concerns. The proposed approach is accompanied by gathering relevant contextual properties pertaining to the environment of IoT interactions. A new architectural aspect-aware definition is proposed for tracking the logic of interaction characteristics on the IoT components being designed.

—In recent years, there has been a growth in the use of reference conceptual models, in general, and domain ontologies, in particular, to capture information about complex and critical domains. These models play a fundamental role in different types of critical semantic interoperability tasks. Therefore, it is essential that domain experts are able to understand and reason using the models' content. In other words, it is important that conceptual models are cognitively tractable. However, it is unavoidable that when the information of the represented domain grows, so does the size and complexity of the artifacts and models that represent them. For this reason, more sophisticated techniques for complexity management in ontology-driven conceptual models, need to be developed. Some approaches are based on the notion of model modularization. In this paper, we follow the work on model modularization to present an approach for view extraction for the ontology-driven conceptual modeling language OntoUML. We provide a formal definition for ontological views over OntoUML conceptual models that completely leverages on the ontologically well-grounded real-world semantics of that language. Moreover, we present a plug-in tool, particularly developed for an OntoUML model-based editor that implements this formal view structure in terms of queries defined over the OntoUML metamodel embedded in that tool.

The main contribution of this paper is the notion of ontology space, which allows us to move from an ontology-centric vision to a constellation-centric vision of the Web, where multiple ontologies and their interactions can be explicitly modeled and studied. This, in turn, allows us to study how OWL ontologies can interoperate, and, in particular, to provide two main results. The first is a formalization of the intended semantics of the OWL importing operator as opaque semantics. This result makes explicit the fact that the semantics of the importing ontology and of the imported ontology are independent. The second is the introduction of the notion of transparent semantics, which allows us to constrain the semantics of an ontology to be the same, on selected language elements, to that of a second reference ontology.

— Ontologies play a key role in semantic interoperability projects, capturing the conceptualization underlying the various systems to be integrated. In the case of large information systems landscapes, a single monolithic ontology often becomes hard to design and maintain. In this setting, it is common to divide the ontological model in consistently interlinked modular ontologies, forming an ontology network. This paper explores the role of Enterprise Architecture (EA) models in defining the ontologies in an ontology network. We report on an exploratory study in the scope of an e-Government interoperability project in the area of public security. In the reported study, an EA model provides guidance in the modularization of the ontology network.

Abstract. We describe the design and use of the Ontology Pre-Processor Language (OPPL) as a means of embedding the use of Knowledge Patterns in OWL ontologies. We illustrate the specification of patterns in OPPL and discuss the advantages of its adoption by Ontology Engineers with respect to ontology generation, transformation, and maintainability. The consequence of the declarative specification of patterns will be their unambiguous description inside an ontology in OWL. Thus, OPPL enables an ontology engineer to work ...

We consider expressive Description Logics (ALCN ) allowing for number restrictions on complex roles built with combinations of role constructors. In particular, we are mainly interested in Logics (called ALC N) allowing for the same kind of complex roles both in number and in value restrictions, which represent very expressive description languages and can be shown very useful for applications.

Ontologies are parts of an Artificial Intelligent advance research area where it is a very familiar topic in computer science. There are many domains of interests that can utilize ontolologies to use them as the knowledge repository. Economy is one of the widely interesting topics that anyone can relate to. This research simplifies ontologies concepts using economy domain to guide people in the field of economics to understand how ontology works as well as to guide the computer software developers to understand the basic concept of economy. The economy ontology is illustrated in ontology chart and hierarchical chart.

Abstract Modularisation is crucial to create re-usable and manageable ontologies. The modularisation is usually performed a posteriori, ie after the ontology is developed, and has been applied mainly to well-structured domains. With the increasing popularity of social ...

We present the syntax and semantics of a modular ontology language SHOIQP to support context-specific reuse of knowledge from multiple ontologies. A SHOIQP ontology consists of multiple ontology modules (each of which can be viewed as a SHOIQ ontology) and concept, role and nominal names can be shared by “importing” relations among modules. SHOIQP supports contextualized interpretation, ie, interpretation from the point of view of a specific package. We establish the necessary and sufficient constraints on ...

The focus of ontology modularization to date has largely been on the creation of techniques to carry out ontology modularization. This creates a problem in evaluating the results of the different techniques. Ontology modularization techniques cannot solely be evaluated by examining their logical properties. Certain applications of ontology modularization, such as ontology reuse, require a new objective way to evaluate the results. This paper motivates the use of an entropy inspired measure to evaluate ontology modules by arguing that current objective measures of evaluation do not reconcile with the subjective measures employed by Ontology Engineers. Experiments are conducted to show that an entropy based evaluation of ontology modules is beneficial to an Ontology Engineer evaluating the results of ontology module extraction techniques.

Abstract. We describe the design and use of the Ontology Pre-Processor Language (OPPL) as a means of embedding the use of Knowledge Patterns in OWL ontologies. We illustrate the specification of patterns in OPPL and discuss the advantages of its adoption by Ontology Engineers with respect to ontology generation, transformation, and maintainability. The consequence of the declarative specification of patterns will be their unambiguous description inside an ontology in OWL. Thus, OPPL enables an ontology engineer to work ...

Applications users claim ever more quality in the software prod- uct; that does not mean only an improved performance but also a better usability or a more e-cient interaction paradigm; in other words, a better "user experience". The designer focus is not on the system but on the user and his applications. This point of view creates new requirements that

This paper presents experiences about the modeling and implementation of utility ontologies used within the Agentcities initiative. Utility ontologies include domain-independent concepts which most services developed within the project use. Ontology building was carried out collaboratively among very different partners from industry and academia. The application domain of the ontologies is an open, dynamic test-bed for agent deployment and they

This paper presents experiences about modeling and implementation of ontologies to be used within the Agentcities initiative. A practical case of collaborative ontology-building among very different partners from industry is described. The application domain of the ontologies is ...