Ontology Web Language

Concept extraction can help in building ontologies, which are the main component of the semantic Web. Ontologies are not only used in the semantic Web, but also in other fields such as Information Retrieval to improve the retrieval. In this work, an Automatic Concept Extractor, which processes Arabic text, is presented. The algorithm of the Automatic Concept Extractor tags the words in the text, finds the pattern of each noun, and outputs only those nouns whose patterns match one of the concepts patterns in the concepts extraction rules. The result of each rule was evaluated individually to find the rules with the highest precision. Two datasets were crawled from the Web and converted to XML. Each rule was tested twice with each dataset as the input. The average precision of the rules showed that the rules with the patterns "Tafe'el" “ليعفت” and Fe'aleh “ةلاعف” achieved a high precision.

This chapter states and explains that a Learning Design is the result of a knowledge engineering process where knowledge and competencies, learning design, media and delivery models are constructed in an integrated framework. Consequently, we present our MOT+ general graphical language and editor that help construct structured interrelated visual models. The MOT+LD editor is the newly added specialization of this editor for learning designs, producing IMS-LD compliant Units of Learning. The MOT+OWL editor is another specialization of the general visual language for knowledge and competency models based on the OWL specification. We situate both models within our taxonomy of knowledge models respectively as a multi-actor collaborative process and a domain theory. The association between these "content" models and learning design components is seen as the essential task in an instructional design methodology, to guide the construction of high quality learning environments.

The ever increasing amount of data gathered by more growers in more years offers possibilities to add value. Therefore—for interested parties and stakeholders—a common and controlled vocabulary of the potato domain that describes concepts, attributes, and the relations between them in a formal way using a standardised knowledge representation language is being developed: a potato ontology. The advantage is that all possible stakeholders will be able to understand the data expressed by this ontology and that software applications can process them automatically. It will also allow the application of advanced numerical techniques that may help to uncover previously unknown correlations. This version of the potato ontology aims at the domain of processing potatoes in a setting of mechanised potato production where growers have access to automated decision support systems and exchange data electronically. This paper describes the procedures to establish such an ontology where competency questions formulated by stakeholders and potential users take a central position. The potato ontology formally describes “Concepts” or “Classes”. The three main classes are those used in crop ecology: Crop, Environment and Management. Classes, e.g., biocides are a subclass of agro-chemicals, and in turn have a subclass Fungicides. The ontology also describes the “Properties” of classes, e.g., agrochemicals are produced synthetically in a factory; biocides are used to protect crops and fungicides to control fungi. The ontology also describes the “Attributes” (properties) of the concepts, e.g., all agrochemicals have attributes such as dose and time of application and mode of application. “Restrictions” may be that a particular chemical can only be applied with a certain type of equipment, or its application is restricted to a certain period or dose. The ontology also features “Instances” which are the individual data such as a particular herbicide treatment with values for field, time, dose, active ingredient, trademark, mode of application, which equipment operated by whom. The standardisation language used is the “Ontology Web Language”.

The Ontology Web Language (OWL) is a language used for the Semantic Web. OWL is based on Description Logics (DLs), a family of logical formalisms for representing and reasoning about conceptual and terminological knowledge. Among these, the logic \(\mathcal{ALC\,}\) is a ground DL used in many practical cases. Moreover, the Semantic Web appears as a new field for the application of formal methods, that could be used to increase its reliability. A starting point could be the formal verification of satisfiability provers for DLs. In this paper, we present the PVS specification of a prover for \(\mathcal{ALC\,}\) , as well as the proofs of its termination, soundness and completeness. We also present the formalization of the well–foundedness of the multiset relation induced by a well–founded relation. This result has been used to prove the termination and the completeness of the \(\mathcal{ALC\,}\) prover.

We have developed a semantic data framework that supports interdisciplinary virtual observatory projects across the fields of solar physics, space physics and solar-terrestrial physics. This work required a formal, machine understandable representation for concepts, relations and attributes of physical quantities in the domains of interest as well as their underlying data representations. To fulfill this need, we developed a set of solar-terrestrial ontologies as formal encodings of the knowledge in the Ontology Web Language��� ...

Service interface description languages such as WSDL, and related standards, are evolving rapidly to provide a foundation for interoperation between Web services. At the same time, Semantic Web service technologies, such as the Ontology Web Language for Services (OWL-S), are developing the means by which services can be given richer semantic specifications. Richer semantics can enable fuller, more flexible automation of service provision and use, and support the construction of more powerful tools and methodologies. Both sets of technologies can benefit from complementary uses and cross-fertilization of ideas. This paper shows how to use OWL-S in conjunction with Web service standards, and explains and illustrates the value added by the semantics expressed in OWL-S.

Service interface description languages such as WSDL, and related standards, are evolving rapidly to provide a foundation for interoperation between Web services. At the same time, Semantic Web service technologies, such as the Ontology Web Language for Services (OWL-S), are developing the means by which services can be given richer semantic specifications. Richer semantics can enable fuller, more flexible automation of service provision and use, and support the construction of more powerful tools and methodologies. Both sets of technologies can benefit from complementary uses and cross-fertilization of ideas. This paper shows how to use OWL-S in conjunction with Web service standards, and explains and illustrates the value added by the semantics expressed in OWL-S.

Abstract—Personalization is one of the key features of the future Internet. However, the success of personalized services mostly relies on user profiles. Therefore, a generic, shareable, and reusable user profile is crucial for service providers for the uptake of personalized services. This ...

We have developed a semantic data framework that supports interdisciplinary virtual observatory projects across the fields of solar physics, space physics and solar-terrestrial physics. This work required a formal, machine understandable representation for concepts, relations and attributes of physical quantities in the domains of interest as well as their underlying data representations. To fulfill this need, we developed a set of solar-terrestrial ontologies as formal encodings of the knowledge in the Ontology Web Language��� ...

We have developed a semantic data framework that supports interdisciplinary virtual observatory projects across the fields of solar physics, space physics and solar-terrestrial physics. This work required a formal, machine understandable representation for concepts, relations and attributes of physical quantities in the domains of interest as well as their underlying data representations. To fulfill this need, we developed a set of solar-terrestrial ontologies as formal encodings of the knowledge in the Ontology Web Language��� ...