Ontology-driven conceptual modeling: A'systematic literature mapping and review

All rights reserved. Ontology-driven conceptual modeling (ODCM) is still a relatively new research domain in the field of information systems and there is still much discussion on how the research in ODCM should be performed and what the focus of this research should be. Therefore, this article aims to critically survey the existing literature in order to assess the kind of research that has been performed over the years, analyze the nature of the research contributions and establish its current state of the art by positioning, evaluating and interpreting relevant research to date that is related to ODCM. To understand and identify any gaps and research opportunities, our literature study is composed of both a systematic mapping study and a systematic review study. The mapping study aims at structuring and classifying the area that is being investigated in order to give a general overview of the research that has been performed in the field. A review study on the other hand is a more thorough and rigorous inquiry and provides recommendations based on the strength of the found evidence. Our results indicate that there are several research gaps that should be addressed and we further composed several research opportunities that are possible areas for future research

Activity-driven content adaptation for effective video summarisation

In this paper, we present a novel method for content adaptation and video summarization fully implemented in compressed-domain. Firstly, summarization of generic videos is modeled as the process of extracted human objects under various activities/events. Accordingly, frames are classified into five categories via fuzzy decision including shot changes (cut and gradual transitions), motion activities (camera motion and object motion) and others by using two inter-frame measurements. Secondly, human objects are detected using Haar-like features. With the detected human objects and attained frame categories, activity levels for each frame are determined to adapt with video contents. Continuous frames belonging to same category are grouped to form one activity entry as content of interest (COI) which will convert the original video into a series of activities. An overall adjustable quota is used to control the size of generated summarization for efficient streaming purpose. Upon this quota, the frames selected for summarization are determined by evenly sampling the accumulated activity levels for content adaptation. Quantitative evaluations have proved the effectiveness and efficiency of our proposed approach, which provides a more flexible and general solution for this topic as domain-specific tasks such as accurate recognition of objects can be avoided

Non classical concept representation and reasoning in formal ontologies

Formal ontologies are nowadays widely considered a standard tool for knowledge representation and reasoning in the Semantic Web. In this context, they are expected to play an important role in helping automated processes to access information. Namely: they are expected to provide a formal structure able to explicate the relationships between different concepts/terms, thus allowing intelligent agents to interpret, correctly, the semantics of the web resources improving the performances of the search technologies. Here we take into account a problem regarding Knowledge Representation in general, and ontology based representations in particular; namely: the fact that knowledge modeling seems to be constrained between conflicting requirements, such as compositionality, on the one hand and the need to represent prototypical information on the other. In particular, most common sense concepts seem not to be captured by the stringent semantics expressed by such formalisms as, for example, Description Logics (which are the formalisms on which the ontology languages have been built). The aim of this work is to analyse this problem, suggesting a possible solution suitable for formal ontologies and semantic web representations. The questions guiding this research, in fact, have been: is it possible to provide a formal representational framework which, for the same concept, combines both the classical modelling view (accounting for compositional information) and defeasible, prototypical knowledge ? Is it possible to propose a modelling architecture able to provide different type of reasoning (e.g. classical deductive reasoning for the compositional component and a non monotonic reasoning for the prototypical one)? We suggest a possible answer to these questions proposing a modelling framework able to represent, within the semantic web languages, a multilevel representation of conceptual information, integrating both classical and non classical (typicality based) information. Within this framework we hypothesise, at least in principle, the coexistence of multiple reasoning processes involving the different levels of representation

Semantic Memory

How is it that we know what a dog and a tree are, or, for that matter, what knowledge is? Our semantic memory consists of knowledge about the world, including concepts, facts and beliefs. This knowledge is essential for recognizing entities and objects, and for making inferences and predictions about the world. In essence, our semantic knowledge determines how we understand and interact with the world around us. In this chapter, we examine semantic memory from cognitive, sensorimotor, cognitive neuroscientific, and computational perspectives. We consider the cognitive and neural processes (and biases) that allow people to learn and represent concepts, and discuss how and where in the brain sensory and motor information may be integrated to allow for the perception of a coherent “concept”. We suggest that our understanding of semantic memory can be enriched by considering how semantic knowledge develops across the lifespan within individuals

SBVR to OWL 2 Mappings - An Automatable and Structural-Rooted Aproach

La amplia aplicabilidad del mapeo de reglas de negocio en sentencias ontológicas ha sido recientemente reconocida. Algunas de las aplicaciones más importantes son: (1) la utilización de razonadores ontológicos para probar la consistencia de la información del dominio del negocio, (2) la generación de una ontología destinada a ser utilizada en la etapa de análisis del proceso de desarrollo de software, y (3) la posibilidad de encapsular la especificación declarativa del conocimiento del negocio en un sistema de información mediante la implementación de una ontología. El lenguaje denominado Semantics of Business Vocabulary and Business Rules (SBVR) brinda soporte a tal enfoque al proveer al experto del negocio una forma lingüistica de describir semánticamente los conceptos y especificar las reglas de negocio, en forma independiente al diseño del sistema de información. Aunque trabajos previos han presentado algunas propuestas, resta definir un enfoque exhaustivo y automatizable de tales mapeos. Este trabajo presenta un conjunto amplio y detallado de transformaciones que permiten la generación automatizable de una ontología implementada en OWL 2, partiendo de la especificación SBVR del dominio del negocio. Tales transformaciones están basadas en la especificación estructural de ambos estándars, y son descriptas mediante un caso de estudio. Se ha realizado un ejemplo real de validación, abordando la factibilidad de los mapeos mediante la evalución de la calidad de la ontología resultante.Wide applicability of mapping business rules expressions to ontology statements have already been recognized. Some of the most important applications are: (1) using of ontology reasoners to prove the consistency of business domain information, (2) generation of an ontology intended to be used in the analysis stage of a software development process, and (3) the possibility of encapsulate the declarative specication of business knowledge into information software systems by means of an implemented ontology. The Semantics of Business Vocabulary and Business Rules (SBVR) supports that approach by providing business people with a linguistic way to semantically describe business concepts and specify business rules in an independent way of any information system design. Previous work have presented some proposals but an exhaustive and automatable approach for them still is lacking. This work presents a broad and detailed set of transformations that allows the automatable generation of an OWL 2 ontology from the SBVR specications of a business domain. Such transformations are rooted on the structural specication of both standards and are depicted through a case study. A real case validation example was performed, approaching the feasibility of the mappings by the quality assessment of the developed ontology.Fil: Reynares, Emiliano. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Tecnologica Nacional. Facultad Regional Santa Fe. Centro de Investigacion y Desarrollo de Ingenieria en Sistemas de Informacion; ArgentinaFil: Caliusco, Maria Laura. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Tecnologica Nacional. Facultad Regional Santa Fe. Centro de Investigacion y Desarrollo de Ingenieria en Sistemas de Informacion; ArgentinaFil: Galli, Maria Rosa. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Santa Fe. Instituto de Desarrollo y Diseño (i); Argentin

Towards a Conceptualization of Sociomaterial Entanglement

In knowledge representation, socio-technical systems can be modeled as multiagent systems in which the local knowledge of each individual agent can be seen as a context. In this paper we propose formal ontologies as a means to describe the assumptions driving the construction of contexts as local theories and to enable interoperability among them. In particular, we present two alternative conceptualizations of the notion of sociomateriality (and entanglement), which is central in the recent debates on socio-technical systems in the social sciences, namely critical and agential realism. We thus start by providing a model of entanglement according to the critical realist view, representing it as a property of objects that are essentially dependent on different modules of an already given ontology. We refine then our treatment by proposing a taxonomy of sociomaterial entanglements that distinguishes between ontological and epistemological entanglement. In the final section, we discuss the second perspective, which is more challenging form the point of view of knowledge representation, and we show that the very distinction of information into modules can be at least in principle built out of the assumption of an entangled reality

Creation and extension of ontologies for describing communications in the context of organizations

Thesis submitted to Faculdade de Ciências e Tecnologia of the Universidade Nova de Lisboa, in partial fulfillment of the requirements for the degree of Master in Computer ScienceThe use of ontologies is nowadays a sufficiently mature and solid field of work to be considered an efficient alternative in knowledge representation. With the crescent growth of the Semantic Web, it is expectable that this alternative tends to emerge even more in the near future. In the context of a collaboration established between FCT-UNL and the R&D department of a national software company, a new solution entitled ECC – Enterprise Communications Center was developed. This application provides a solution to manage the communications that enter, leave or are made within an organization, and includes intelligent classification of communications and conceptual search techniques in a communications repository. As specificity may be the key to obtain acceptable results with these processes, the use of ontologies becomes crucial to represent the existing knowledge about the specific domain of an organization. This work allowed us to guarantee a core set of ontologies that have the power of expressing the general context of the communications made in an organization, and of a methodology based upon a series of concrete steps that provides an effective capability of extending the ontologies to any business domain. By applying these steps, the minimization of the conceptualization and setup effort in new organizations and business domains is guaranteed. The adequacy of the core set of ontologies chosen and of the methodology specified is demonstrated in this thesis by its effective application to a real case-study, which allowed us to work with the different types of sources considered in the methodology and the activities that support its construction and evolution

Variations in Conceptual Modeling: Classification and Ontological Analysis

Conceptual models are aimed at providing formal representations of a domain. They are mainly used for the purpose of understanding and communicating about requirements for information systems.Conceptual modeling has acquired a large body of research dealing with the semantics of modeling constructs, with the goal to make models better vehicles for understanding and communication. However, it is commonly known that different people construct different models of a given domain although all may be similarly adequate. The premise of this paper is that variations in models reflect vagueness in the criteria for deciding how to map reality into modeling constructs. Exploring model variations as such can contribute to research that deals with the semantics of modeling constructs.This paper reports an exploratory study in which empirically obtained model variations were qualitatively analyzed and classified into variation types. In light of the identified variation types, we analyzed two ontology-based modeling frameworks in order to evaluate their potential contribution to a reduction in variations. Our analysis suggests that such frameworks may contribute to more conclusive modeling decision making, thus reducing variations. However, since there is no complete consistency between the two frameworks, in order to reduce variations, a single framework should be systematically applied