Fr. Anthony and Fr. Harry Linsinbigler (canonist for the UOC-USA) talk about recent blessings at the parish Fr. Harry serves (Protection of the Theotokos in Dover, FL), variations on the sacrament of confession, and the ontology of the priesthood. Listen and find out how relics and myrrh-streaming icons can help a parish's culture, what the differences are between the different prayers of absolution, and whether the priest is just a fill-in for when the bishop can't be at the parish. Enjoy the show!

The user experience of any software or website consists of elements from the conceptual to the concrete level. These elements of user experience assist in the design and development of user interfaces. On the other hand, ontologies provide a framework for computable representation of user interface elements and underlying data. This paper discusses strategies of introducing ontologies at different user interface layers adapted from user experience elements. These layers range from abstract levels (e.g. User needs/Application Objectives) to concrete levels (e.g. Application User Interface) in terms of data representation. The proposed ontological framework enables device independent, semi-automated GUI construction which we will demonstrate at a personal information management example.

Semantic-based technologies have been steadily increasing their relevance in recent years in both the research world and business world. Considering this, the present article discusses the process of design and implementation of a competency management system in information and communication technologies domain utilizing the latest Semantic Web tools and technologies including D2RQ server, TopBraid Composer, OWL 2, SPARQL, SPARQL Rules and common human resources related public vocabularies. In particular, the paper discusses the process of building individual and enterprise competence models in a form of ontology database, as well as different ways of meaningful search and retrieval of expertise data on the Semantic Web. The ontological knowledge base aims at storing the extracted and integrated competences from structured, as well as unstructured sources. By using the illustrative case study of deployment of such a system in the Human Resources sector at the Mihajlo Pupin Institute, this paper shows an example of new approaches to data integration and information management. The proposed approach extends the functionalities of existing enterprise information systems and offers possibilities for development of future Internet services. This allows organizations to express their core competences and talents in a standardized, machine processable and understandable format, and hence, facilitates their integration in the European Research Area and beyond.

Retrieving information or discovering knowledge from a well organized data center in general is requested to be familiar with its schema, structure, and architecture, which against the inherent concept and characteristics of cloud environment. An effective approach to retrieve desired information or to extract useful knowledge is an important issue in the emerging information/knowledge cloud. In this paper, we propose an ontology-based agent generation framework for information retrieval in a flexible, transparent, and easy way on cloud environment. While user submitting a flat-text based request for retrieving information on a cloud environment, the request will be automatically deduced by a Reasoning Agent (RA) based on predefined ontology and reasoning rule, and then be translated to a Mobile Information Retrieving Agent Description File (MIRADF) that is formatted in a proposed Mobile Agent Description Language (MADF). A generating agent, named MIRA-GA, is also implemented to generate a MIRA according to the MIRADF. We also design and implement a prototype to integrate these agents and show an interesting example to demonstrate the feasibility of the architecture.

Project monitoring plays a crucial role in project management, which is a part of every stage of a project's life-cycle. Nevertheless, along with the increasing ratio of outsourcing in many companies' strategic plans, project monitoring has been challenged by geographically dispersed project teams and culturally diverse team members. Furthermore, because of the lack of a uniform standard, data exchange between various project monitoring software becomes an impossible mission. These factors together lead to the issue of ambiguity in project monitoring processes. Ontology is a form of knowledge representation with the purpose of disambiguation. Consequently, in this paper, we propose the framework of an ontology-based real-time project monitoring system (ORPSM), in order to, by means of ontologies, solve the ambiguity issue in project monitoring processes caused by multiple factors. The framework incorporates a series of ontologies for knowledge capture, storage, sharing and term disambiguation in project monitoring processes, and a series of metrics for assisting management of project organizations to better monitor projects. We propose to configure the ORPMS framework in a cloud environment, aiming at providing the project monitoring service to geographically distributed and dynamic project members with great flexibility, scalability and security. A case study is conducted on a prototype of the ORPMS in order to evaluate the framework.

Aim/Purpose: Vis-à-vis management of crisis and disaster situations, this paper focuses on important use cases of social media functions, such as information collection & dissemination, disaster event identification & monitoring, collaborative problem-solving mechanism, and decision-making process. With the prolific utilization of disaster-based ontological framework, a strong disambiguation system is realized, which further enhances the searching capabilities of the user request and provides a solution of unambiguous in nature. Background: Even though social media is information-rich, it has created a challenge for deriving a decision in critical crisis-related cases. In order to make the whole process effective and avail quality decision making, sufficiently clear semantics of such information is necessary, which can be supplemented through employing semantic web technologies. Methodology: This paper evolves a disaster ontology-based system availing a framework model for monitoring uses of social media during risk and crisis-related events. The proposed system monitors a discussion thread discovering whether it has reached its peak or decline after its root in the social forum like Twitter. The content in social media can be accessed through two typical ways: Search Application Program Interfaces (APIs) and Streaming APIs. These two kinds of API processes can be used interchangeably. News content may be filtered by time, geographical region, keyword occurrence and availability ratio. With the support of disaster ontology, domain knowledge extraction and comparison against all possible concepts are availed. Besides, the proposed method makes use of SPARQL to disambiguate the query and yield the results which produce high precision. Contribution: The model provides for the collection of crisis-related temporal data and decision making through semantic mapping of entities over concepts in a disaster ontology we developed, thereby disambiguating potential named entities. Results of empirical testing and analysis indicate that the proposed model outperforms similar other models. Findings: Crucial findings of this research lie in three aspects: (1) Twitter streams and conventional news media tend to offer almost similar types of news coverage for a specified event, but the rate of distribution among topics/categories differs. (2) On specific events such as disaster, crisis or any emergency situations, the volume of information that has been accumulated between the two news media stands divergent and filtering the most potential information poses a challenging task. (3) Relational mapping/co-occurrence of terms has been well designed for conventional news media, but due to shortness and sparseness of tweets, there remains a bottleneck for researchers. Recommendations for Practitioners: Though metadata avails collaborative details of news content and it has been conventionally used in many areas like information retrieval, natural language processing, and pattern recognition, there is still a lack of fulfillment in semantic aspects of data. Hence, the pervasive use of ontology is highly suggested that build semantic-oriented metadata for concept-based modeling, information flow searching and knowledge exchange. Recommendation for Researchers: The strong recommendation for researchers is that instead of heavily relying on conventional Information Retrieval (IR) systems, one can focus more on ontology for improving the accuracy rate and thereby reducing ambiguous terms persisting in the result sets. In order to harness the potential information to derive the hidden facts, this research recommends clustering the information from diverse sources rather than pruning a single news source. It is advisable to use a domain ontology to segregate the entities which pose ambiguity over other candidate sets thus strengthening the outcome. Impact on Society: The objective of this research is to provide informative summarization of happenings such as crisis, disaster, emergency and havoc-based situations in the real world. A system is proposed which provides the summarized views of such happenings and corroborates the news by interrelating with one another. Its major task is to monitor the events which are very booming and deemed important from a crowd’s perspective. Future Research: In the future, one shall strive to help to summarize and to visualize the potential information which is ranked high by the model.

Nan WU,Xiaocong LAI,Mei CHEN,Ying PAN, Vol.E107-D, No.11, pp.1433-1443
With the development of the Semantic Web, an increasing number of researchers are utilizing ontology technology to construct domain ontology. Since there is no unified construction standard, ontology heterogeneity occurs. The ontology matching method can fuse heterogeneous ontologies, which realizes the interoperability between knowledge and associates to more relevant semantic information. In the case of differences between ontologies, how to reduce false matching and unsuccessful matching is a critical problem to be solved. Moreover, as the number of ontologies increases, the semantic relationship between ontologies becomes increasingly complex. Nevertheless, the current methods that solely find the similarity of names between concepts are no longer sufficient. Consequently, this paper proposes an ontology matching method based on semantic association. Accurate matching pairs are discovered by existing semantic knowledge, and then the potential semantic associations between concepts are mined according to the characteristics of the contextual structure. The matching method can better carry out matching work based on reliable knowledge. In addition, this paper introduces a probabilistic logic repair method, which can detect and repair the conflict of matching results, to enhance the availability and reliability of matching results. The experimental results show that the proposed method effectively improves the quality of matching between ontologies and saves time on repairing incorrect matching pairs. Besides, compared with the existing ontology matching systems, the proposed method has better stability.
Publication Date: 2024/11/01

Mr. Andre C. LuJan is noted for his expertise as the owner and founder of PaleoTex LLC

ETSI releases 3 new ontology specifications for Smart Cities, Industry 4.0 and Smart Agriculture

Sophia Antipolis, 24 June 2019

Following the first three SAREF (Smart Applications REFerence ontology) specifications for energy, environment and buildings, the ETSI SmartM2M Technical Committee has just released three new specifications for smart cities, industry and manufacturing, and smart agriculture and food chain domains.

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ETSI launches IoT ontology for automotive, eHealth, wearables and water distribution

Sophia Antipolis, 1 September 2020

The ETSI SmartM2M technical committee is pleased to confirm it has extended its IoT SAREF ontology with four new sectors addressing the automotive, eHealth/Ageing-well, wearable and water domains. The Smart Applications REFerence (SAREF) ontology is intended to enable interoperability between solutions from different providers and within various activity sectors in the Internet of Things (IoT), thus contributing to the development of the global digital market. SmartM2M has already developed six extensions, now supplemented with these four new specifications.

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xxii, 322 pages : illustrations (some color), maps, plans ; 28 cm

Dr. Villa dedicates her research to the elderly and veteran populations and also serves as a professor for California State University

Apparatus for use in generating a mapping using ontologies, the apparatus including at least one electronic processing device that determines ontologies having respective ontology terms, determines a group of ontology terms from at least one of the ontologies, determines alignment between ontology terms in the ontologies for at least some of the group of ontology terms, the alignment being determined at least partially in accordance with an ontology term meaning of the ontology terms and generates a mapping in accordance with the alignment.

Oxford : Oxford University Press, 2019.

Oxford, UK ; New York, NY : Oxford University Press, [2017]

Online Resource

Bryant, Levi R., author

Husain, Martha, 1937-

Wachterhauser, Brice R., 1953- author

Hayden Library - B105.C477 C6487 2019

Hayden Library - B2948.D82613 2018

Hayden Library - BD311.M36 2018

Online Resource

Online Resource

Online Resource

Hayden Library - QC174.26.W3 C65 2018

Hayden Library - QC174.26.W3 G36 2017

Dewey Library - QC174.12.B64 2018