Showing papers on "Upper ontology published in 2019"

Data modeling for museum collections

Abstract: . The relationship between cultural heritage, digital technologies and visual models involves an increasingly wide area of research, oriented towards the renewal of archives and museums for the preservation and promotion of culture. Recent research activities are the result of the progressive strengthening of digital technologies and the needs of a new generation of “digital” users, which requires museums to update their means of communication using Semantic Web languages and technologies shaped by a social conceptualization of a graph-based representation of information. The growth of several digitized heritage collections increases the necessity of proper methodologies to develop a structured system able to access to these collections and the large amount of data, metadata and paradata related to the digitized objects in a structured and organized way, defining a set of collection information models (CIM), that considers not only the digitizing process but also the data collection process, layered by an Upper Ontology level structure, based on CIDOC-CRM.

A Pattern Language for Value Modeling in ArchiMate

Abstract: In recent years, there has been a growing interest in modeling value in the context of Enterprise Architecture, which has been driven by a need to align the vision and strategic goals of an enterprise with its business architecture. Nevertheless, the current literature shows that the concept of value is conceptually complex and still causes a lot of confusion. For example, we can find in the literature the concept of value being taken as equivalent to notions as disparate as goals, events, objects and capabilities. As a result, there is still a lack of proper support for modeling all aspects of value as well as its relations to these aforementioned notions. To address this issue, we propose in this paper a pattern language for value modeling in ArchiMate, which is based on the Common Ontology of Value and Risk, a well-founded reference ontology developed following the principles of the Unified Foundation Ontology. This enables us to delineate a clear ontological foundation, which addresses the ambiguous use of the value concept. The design of the Value Pattern Language will be guided by the Design Science Research Methodology. More specifically, a first iteration of the build-and-evaluate loop is presented, which includes the development of the pattern language and its demonstration by means of a case study of a low-cost airline.

CEVO: Comprehensive EVent Ontology Enhancing Cognitive Annotation on Relations

Abstract: While the general analysis of named entities has received substantial research attention on unstructured as well as structured data, the analysis of relations among named entities has received limited focus. In fact, a review of the literature revealed a deficiency in research on the abstract conceptualization required to organize relations. We believe that such an abstract conceptualization can benefit various communities and applications such as natural language processing, information extraction, machine learning, and ontology engineering. In this paper, we present Comprehensive EVent Ontology (CEVO), built on Levin's conceptual hierarchy of English verbs that categorizes verbs with shared meaning, and syntactic behavior. We present the fundamental concepts and requirements for this ontology. Furthermore, we present three use cases employing the CEVO ontology on annotation tasks: (i) annotating relations in plain text, (ii) annotating ontological properties, and (iii) linking textual relations to ontological properties. These use-cases demonstrate the benefits of using CEVO for annotation: (i) annotating English verbs from an abstract conceptualization, (ii) playing the role of an upper ontology for organizing ontological properties, and (iii) facilitating the annotation of text relations using any underlying vocabulary. This resource is available at https:llshekarpour.github.io/cevo.io/ using https://w3id.org/cevonamespace.

A review on feature based approach in semantic similarity for multiple ontology

Abstract: Measuring semantic similarity between terms is an important step in information retrieval and information integration which requires semantic content matching. Semantic similarity has attracted great concern for a long time in artificial intelligence, psychology and cognitive science. This paper contains a review of the state of art approaches including structure based approach, information content based approach, features based approach and hybrid approach. We also discussed similarity according to their advantages, disadvantages and issues related to multiple ontology especially on methods in features based approach.

PERSWADE-CORE: A Core Ontology for Communicating Socio-Environmental and Sustainability Science

Abstract: The Centre on Persuasive Systems for Wise Adaptive Living (PERSWADE) aims at developing and applying persuasive technologies and system science for social innovation that can help humanity to move toward sustainable, wise, adaptive living. The PERSWADE collaborative knowledge base needs to be designed with the intent to bring together, enrich and logically relate heterogeneous content, such as datasets, scientific literature and any kind of multimedia and social content, to support a participatory approach and help to translate science into action. PERSWADE-CORE, the foundation ontology described in this paper, plays a critical role in this by providing the backbone semantic infrastructure to enable collaboration through efficient data and knowledge integration, sharing and reuse. It also serves the purpose of clarifying and explaining the goals, functions and operations of the Centre. Because of its purpose, PERSWADE-CORE has been designed to be easy-to-use and easy-to-adapt by allowing generic, as well as more specific, relationships among concepts. The PERSWADE approach prioritizes interoperability and relies on the Semantic Web infrastructure. Furthermore, its design is intrinsically aimed at collaborative environments in which ontologies are expected to evolve as a response to users' activity.

Syntactico-Semantic Reasoning using PCFG, MEBN & PP Attachment Ambiguity

Abstract: Probabilistic context free grammars (PCFG) have been the core of the probabilistic reasoning based parsers for several years especially in the context of the NLP. Multi entity Bayesian networks (MEBN) a First Order Logic probabilistic reasoning methodology is widely adopted and used method for uncertainty reasoning. Further upper ontology like Probabilistic Ontology Web Language (PR-OWL) built using MEBN takes care of probabilistic ontologies which model and capture the uncertainties inherent in the domain's semantic information. The paper attempts to establish a link between probabilistic reasoning in PCFG and MEBN by proposing a formal description of PCFG driven by MEBN leading to the usage of PR-OWL modeled ontologies in PCFG parsers. Furthermore, the paper outlines an approach to resolve the prepositional phrase (PP) attachment ambiguity using the proposed mapping between PCFG and MEBN.

Application of Allen’s Temporal Logic to Ontological Modeling for Enterprise Interoperability

Abstract: The problems of creating lifecycle ontologies for enterprise interoperability are addressed in this paper. Enterprise interoperability and enterprise integration are essential components of enterprise engineering (EE). A few definitions and viewpoints on EE are examined in the first hand. An original discipline for EE is considered. A generalized ontological approach to enterprise engineering is developed on the basis of combination of the lifecycle modeling, knowledge management and ontological engineering. It calls for the modeling and coordination of at least three lifecycles: enterprise lifecycle, knowledge lifecycle and product lifecycle. A general representation of lifecycle knowledge graph by a mind map is given. Particular emphasis is put on granular lifecycle upper ontology and meta-ontology. The lifecycle representations being discussed include both visualized and abstract ones. Allen’s logic is used to construct principle temporal relations between stages and phases of lifecycle.