Process of ontology construction for the development of an intelligent system for the organization and retrieval of knowledge in biodiversity – SISBIO

This work describes the ontology construction process for the development of an Intelligent System for the Organization and Retrieval of Knowledge in Biodiversity – SISBIO. The system aims at the production of strategic information for the biofuel chain Two main methodologies are used for the construction of the ontologies: knowledge engineering and ontology engineering. The first one consists of extracting and organizing the biofuel specialists´ knowledge, and ontology engineering is used to represent the knowledge through indicative expressions and its relations, developing a semantic network of relationships.Applications in Artificial Intelligence - Ontologies and Intelligent WebRed de Universidades con Carreras en Informática (RedUNCI

Process of ontology construction for the development of an intelligent system for the organization and retrieval of knowledge in biodiversity – SISBIO

This work describes the ontology construction process for the development of an Intelligent System for the Organization and Retrieval of Knowledge in Biodiversity – SISBIO. The system aims at the production of strategic information for the biofuel chain Two main methodologies are used for the construction of the ontologies: knowledge engineering and ontology engineering. The first one consists of extracting and organizing the biofuel specialists´ knowledge, and ontology engineering is used to represent the knowledge through indicative expressions and its relations, developing a semantic network of relationships.Applications in Artificial Intelligence - Ontologies and Intelligent WebRed de Universidades con Carreras en Informática (RedUNCI

COGMIR: A Computer Model for Knowledge Integration.

Knowledge integration is an important topic for knowledge engineering. In this dissertation, we explore some aspects of knowledge integration, namely, accumulation of scientific knowledge and performing analogical reasoning on the acquired knowledge. Knowledge to be integrated is conveyed by paragraph-like pieces, these pieces will be referred to as documents. By incorporating some results from cognitive science, the Deutsch-Kraft model of information retrieval is extended to a model for knowledge engineering, which integrates acquired knowledge and performs intelligent retrieval. The resulting computer model is termed COGMIR, which stands for a COGnitive Model for Intelligent Retrieval. A scheme, named query invoked memory reorganization, is used in COGMIR for knowledge integration. Unlike some other schemes which realize knowledge integration through subjective understanding by representing new knowledge in terms of existing knowledge, the proposed scheme suggests at storage time only recording the possible connection of knowledge acquired from different documents. The actual binding of the knowledge acquired from different documents is deferred to query time, depending on the actual needs of the query. Therefore, although there is only one way to store knowledge, there are potentially numerous ways to utilize the knowledge. From the classical information retrieval viewpoint, we have extended the original model in the following sense, not only each document be represented as a whole, but also the meaning of each document can be represented. In addition, since facts are constructed from the documents, document retrieval and fact retrieval are treated in a unified way. Moreover, when the requested knowledge is not available, query invoked memory reorganization can generate suggestion based on available knowledge through analogical reasoning. This is done by revising the algorithms developed for document retrieval and fact retrieval, and by incorporating Gentner\u27s structure mapping theory. Analogical reasoning is treated as a natural extension of intelligent retrieval, so that two previously separate research areas are thus combined. A case study is provided to demonstrate the fundamental ideas. All the components are implemented as list structures, which bears an interesting similarity to relational data-bases

Semantic web domain knowledge representation using software engineering modeling technique

The semantic web offers a great deal of deviation from the way in which the current search engines which are based on the traditional information search theory work. Semantic search is carried out by ontology based intelligent information retrieval. So a good semantic search needs a good ontology. The ontology developers need more familiar notations and tools for a uniform representation of ontologies. UML being a standard modeling language in software engineering, it is better supported in terms of expertise and the tools as compared to the upcoming semantic web languages. This work proposes a representation technique which is based on software engineering standards namely UML for modeling domain knowledge of the Semantic Web. The ontology for Company Domain has been presented using this software engineering modeling technique. The UML tool like Rational Rose tool can be used to provide support for modeling complex ontologies of the given domain

Semantic Web Domain Knowledge Representation Using Software Engineering Modeling Technique

ICSD2007, BangaloreThe semantic web offers a great deal of deviation from the way in which the current search engines which are based on the traditional information search theory work. Semantic search is carried out by ontology based intelligent information retrieval. So a good semantic search needs a good ontology. The ontology developers need more familiar notations and tools for a uniform representation of ontologies. UML being a standard modeling language in software engineering, it is better supported in terms of expertise and the tools as compared to the upcoming semantic web languages. This work proposes a representation technique which is based on software engineering standards namely UML for modeling domain knowledge of the Semantic Web. The ontology for Company Domain has been presented using this software engineering modeling technique. The UML tool like Rational Rose tool can be used to provide support for modeling complex ontologies of the given domain.DRTC,ISI,Bangalore,INDI

Essentials In Ontology Engineering: Methodologies, Languages, And Tools

In the beginning of the 90s, ontology development was similar to an art: ontology developers did not have clear guidelines on how to build ontologies but only some design criteria to be followed. Work on principles, methods and methodologies, together with supporting technologies and languages, made ontology development become an engineering discipline, the so-called Ontology Engineering. Ontology Engineering refers to the set of activities that concern the ontology development process and the ontology life cycle, the methods and methodologies for building ontologies, and the tool suites and languages that support them. Thanks to the work done in the Ontology Engineering field, the development of ontologies within and between teams has increased and improved, as well as the possibility of reusing ontologies in other developments and in final applications. Currently, ontologies are widely used in (a) Knowledge Engineering, Artificial Intelligence and Computer Science, (b) applications related to knowledge management, natural language processing, e-commerce, intelligent information integration, information retrieval, database design and integration, bio-informatics, education, and (c) the Semantic Web, the Semantic Grid, and the Linked Data initiative. In this paper, we provide an overview of Ontology Engineering, mentioning the most outstanding and used methodologies, languages, and tools for building ontologies. In addition, we include some words on how all these elements can be used in the Linked Data initiative

Developing engineering ontology for domain coordinate metrology

Već razvijene i primenjene inženjerske informacije, često su skladištene i zaboravljene. Trenutni pristupi pretraživanju informacija su nedovoljno efikasni u razumevanju inženjerskih sadržaja, jer oni nisu razvijeni tako da dele, ponovo upotrebljavaju i predstavljaju informacije jednog inženjerskog domena. U ovom radu se daje trenutno stanje razvoja inženjerske ontologije i predlaže metod njenog razvoja na konceptualnom nivou, u cilju ponovne upotrebe i deljenja znanja u domenu koordinatne metrologije. Osim toga, metod definiše razvoj ontologije za potrebe izgradnje baze znanja, kao jedne od osnovnih komponenti inteligentnog sistema za inspekciju prizmatičnih delova na numerički upravljanoj mernoj mašini. Predloženi metod je implementiran u softveru Protégé na primeru jednog mernog dela.Already developed and applied engineering information, it is often stored and forgotten. Current approaches for information retrieval are not effective enough in understanding of engineering contents, because they are not developed to share, reuse and represent information of an engineering domain. This paper presents the current state of development engineering ontology (EO) and suggests the method of its development at conceptual level, in order to reuse and share knowledge in domain of coordinate metrology (CM). Furthermore, the method defines development of ontology for the construction of knowledge base, as one of the basic components of an intelligent system for the inspection of prismatic parts on coordinate measuring machine (CMM). The proposed method is implemented in the software Protégé on the example of one measuring part

Developing engineering ontology for domain coordinate metrology

Već razvijene i primenjene inženjerske informacije, često su skladištene i zaboravljene. Trenutni pristupi pretraživanju informacija su nedovoljno efikasni u razumevanju inženjerskih sadržaja, jer oni nisu razvijeni tako da dele, ponovo upotrebljavaju i predstavljaju informacije jednog inženjerskog domena. U ovom radu se daje trenutno stanje razvoja inženjerske ontologije i predlaže metod njenog razvoja na konceptualnom nivou, u cilju ponovne upotrebe i deljenja znanja u domenu koordinatne metrologije. Osim toga, metod definiše razvoj ontologije za potrebe izgradnje baze znanja, kao jedne od osnovnih komponenti inteligentnog sistema za inspekciju prizmatičnih delova na numerički upravljanoj mernoj mašini. Predloženi metod je implementiran u softveru Protégé na primeru jednog mernog dela.Already developed and applied engineering information, it is often stored and forgotten. Current approaches for information retrieval are not effective enough in understanding of engineering contents, because they are not developed to share, reuse and represent information of an engineering domain. This paper presents the current state of development engineering ontology (EO) and suggests the method of its development at conceptual level, in order to reuse and share knowledge in domain of coordinate metrology (CM). Furthermore, the method defines development of ontology for the construction of knowledge base, as one of the basic components of an intelligent system for the inspection of prismatic parts on coordinate measuring machine (CMM). The proposed method is implemented in the software Protégé on the example of one measuring part