Ontology Charts Research Articles

Hit or Miss? Evaluating the Potential of a Research Niche: A Case Study in the Field of Virtual Quality Management

When knowledge is developed fast, as it is the case so often nowadays, one of the main difficulties in initiating new research in any field is to identify the domain’s specific state-of-the-art and trends. In this context, to evaluate the potential of a research niche by assisting the literature review process and to add a new and modern large-scale and automated dimension to it, the paper proposes a methodology that uses “Latent Semantic Analysis” (LSA) for identifying trends, focused within the knowledge space created at the intersection of three sustainability-related methodologies/concepts: “virtual Quality Management” (vQM), “Industry 4.0”, and “Product Life-Cycle” (PLC). The LSA was applied to a significant number of scientific papers published around these concepts to generate ontology charts that describe the knowledge structure of each by the frequency, position, and causal relation of associated notions. These notions are combined for defining the common high-density knowledge zone from where new technological solutions are expected to emerge throughout the PLC. The authors propose the concept of the knowledge space, which is characterized through specific descriptors with their own evaluation scales, obtained by processing the emerging information as identified by a combination of classic and innovative techniques. The results are validated through an investigation that surveys a relevant number of general managers, specialists, and consultants in the field of quality in the automotive sector from Romania. This practical demonstration follows each step of the theoretical approach and yields results that prove the capability of the method to contribute to the understanding and elucidation of the scientific area to which it is applied. Once validated, the method could be transferred to fields with similar characteristics.

Introducing BPMN 2.0 based, invariant and dynamic constrains to MEASUR’s ontology charts

MEASUR’s ontology charts are models that provide a static view of the organizational structures. The model has been used in a number of cases and have provided evidence of stability and clarity. Additionally, they have been used for the development of information systems either manually or through the use of tools such as model driven development frameworks and have proved to generate various artefacts such as design models and even prototype systems. While precise and informative they lack the ability to capture the dynamic aspects of the organizations. In this research, we propose the use of business process modeling notation as a visual language that can capture the invariant and dynamic constrains of the MEASUR’s ontology charts.

Pilot testing model to uncover industrial symbiosis in Brazilian industrial clusters.

The main objective of this study was to create a pilot model to uncover industrial symbiosis practices in Brazilian industrial clusters. For this purpose, a systematic revision was conducted in journals selected from two categories of the ISI Web of Knowledge: Engineering, Environmental and Engineering, Industrial. After an in-depth revision of literature, results allowed the creation of an analysis structure. A methodology based on fuzzy logic was applied and used to attribute the weights of industrial symbiosis variables. It was thus possible to extract the intensity indicators of the interrelations required to analyse the development level of each correlation between the variables. Determination of variables and their weights initially resulted in a framework for the theory of industrial symbiosis assessments. Research results allowed the creation of a pilot model that could precisely identify the loopholes or development levels in each sphere. Ontology charts for data analysis were also generated. This study contributes to science by presenting the foundations for building an instrument that enables application and compilation of the pilot model, in order to identify opportunity to symbiotic development, which derives from "uncovering" existing symbioses.

Understanding the Semantics of a Mixed Reality Environment

Objectives: The objective of this paper is to explore how mixed reality can be enhanced with actual understanding of the recognized objects. Methods: This paper will conceptually utilize a method called MEASUR semantic analysis and explain how it can improve the semantic understanding of the environment. The paper explains how a MEASUR Ontology Chart, that captures the semantics of a mixed reality environment can be generated and how it can increase the user interaction with the mixed environment. Findings: Mixed reality is a new field of research that aims to enhance our reality with computer generated 3D graphics, also known as holograms. Additionally, it allows the user to interact with virtual and real objects. Even though we are still at the beginning of exploring its potentials, mixed reality is expected to be a game changer in most aspects of our everyday life. A major problem with the current state of art mixed reality applications is that they have very limited understanding about the real-world environment. They are utilizing computer vision approaches for identifying objects from the real world but yet again there is no real association between the various objects and limited or no understanding of their semantics. This limits the supported interaction between the users and mixed reality environment. Application/Improvements: This paper will conceptually utilize a method called MEASUR semantic analysis and explain how it can improve the semantic understanding of the environment. The paper explains how a MEASUR Ontology Chart, that captures the semantics of a mixed reality environment can be generated and how it can increase the user interaction with the mixed environment.

E-Mail Fraud Detection - An Organisational Semiotic View

Fraud detections methods have become more sophisticated as more cunning ways are being used to commit fraud. Data mining methods have extensively been used in the detection of fraud but the use of ontology based methods is not very prominent and popular. A method based on organisational semiotics which employs semantic analysis and norm analysis is new in this area. Determining the agents, the authorities responsible for decision making, and the affordances, the potential behaviour of these authorities including the rules that govern that behaviour which make up the organisation is important in using these methods in the fraud detection domain. Through this a graphical representation of the relationships between these agents and affordances in the form of an ontology chart can be drawn from which a generic fraud framework can be based.

Ontology modeling for generation of clinical pathways

Purpose: Increasing costs of health care, fuelled by demand for high quality, cost-effective healthcare has drove hospitals to streamline their patient care delivery systems. One such systematic approach is the adaptation of Clinical Pathways (CP) as a tool to increase the quality of healthcare delivery. However, most organizations still rely on are paper-based pathway guidelines or specifications, which have limitations in process management and as a result can influence patient safety outcomes. In this paper, we present a method for generating clinical pathways based on organizational semiotics by capturing knowledge from syntactic, semantic and pragmatic to social level. Design/methodology/approach: The proposed modeling approach to generation of CPs adopts organizational semiotics and enables the generation of semantically rich representation of CP knowledge. Semantic Analysis Method (SAM) is applied to explicitly represent the semantics of the concepts, their relationships and patterns of behavior in terms of an ontology chart. Norm Analysis Method (NAM) is adopted to identify and formally specify patterns of behavior and rules that govern the actions identified on the ontology chart. Information collected during semantic and norm analysis is integrated to guide the generation of CPs using best practice represented in BPMN thus enabling the automation of CP.

Creating ontology chart of economic objects: The application of menger’s ideas

Processing data is one of the main concerns of almost every field of study which deals with information. But today with the growing data and information a new delicate problem arises: “processing” knowledge. One way to start solving it is by categorizing knowledge; then trying to manage these knowledge categories according to the interest of the field of study; and finally implementing them into a problem-solving platform such as a software program, a web page or merely in a new algorithm. Ontologies come in handy in one of the key links of this chain: knowledge management. In this paper we show the how to use ontologies for data and knowledge management and how they can be applied in formalizing economic concepts. We did this classification according to Menger’s ideas.

Collective Construction of Meaning and System for an Inclusive Social Network

Information and Communication Technology has the potential of benefiting citizens, allowing access to knowledge, communication and collaboration, and thus promoting the process of constitution of a fairer society. The design of systems that make sense to the users’ community and that respect their diversity demands socio-technical views and an in-depth analysis of the involved parties. The authors have adopted Organizational Semiotics and Participatory Design as theoretical and methodological frames of reference to face this challenge in the design of an Inclusive Social Network System for the Brazilian context. This paper presents the use of some artifacts adapted from Problem Articulation Method to clarify concepts and prospect solutions. Results of this clarification fed the Semantic Analysis Method from which this paper presents and discusses an Ontology Chart for the domain and the first signs of the inclusive social network system.

A MEASUR and RUP Combined Business Modeling Method

Business modeling is a primary task in the information systems development lifecycle. Although both MEASUR (Methods for Eliciting, Analyzing and Specifying User's Requirement) and RUP (Rational Unified Process) provide their own Business Method (BMM), each has obvious merits and demerits. To keep the merits and avoid the demerits at the same time, in this paper, a MEASUR and RUP combined BMM is devised based on the comparison of the two BMMs respectively from the semantics, pragmatics and social world of the semiotic framework. The method proposed consists of three activities in sequence. Unified Language (UML) Use Case Diagrams (UCD) are employed in the first activity UCD Modeling to model business functions concerning with the social world since they are the only formal result modeling business functions in both BMMs. The extended UML Activity Diagrams (AD) are employed in the second activity Extended UML AD Modeling to model both norms and communications concerning with both the social world and the pragmatics since UML AD can model communications directly and obviously but norms cannot and therefore make the analysis of purposes in communications much easier. In addition, it is easy to extend UML AD with the deontic operators to express the same meaning as norms following the simple rules. The Ontology Charts (OC) are employed in the third activity Modeling to define meanings of terminology used in business models and concerning with the semantics since ontological dependencies are modeled directly and clearly in OC but not defined in UML Class Diagrams.

Adaptive Requirement-Driven Architecture for Integrated Healthcare Systems

In order to improve the quality of healthcare services, large-scale medical information systems should be integrated with adaptability in response to the changing medical environment. In this paper, we propose a requirement-driven architecture for healthcare information systems that will be able to respond to new requirements. The system operates through the mapping mechanism between these layers and thus can organize functions dynamically adapting to user’s requirement. Furthermore, we introduce the organizational semiotics methods to capture and analyze user’s requirement through ontology chart and norms. Based on these results, the structure of user’s requirement pattern (URP) is established as the driving factor of our system. Finally, we propose an integration framework for data sharing amongst different hospital organizations and also present the HL7 based virtual database to realize the data integration. Our research makes a contribution to the design and implementation of the architecture of healthcare systems which can adapt to the changing medical environment.

Transformation of Semantic Analysis to Com+ Business Requirements Using MDA Approach

Model Driven Architecture (MDA) is one of many competing techniques that have the potential to contribute towards the development of better software systems. However the business support at Computation-Independent Model (CIM) level does not necessarily allow the development teams to utilize its power and it might become difficult to bridge the gap between analysis, design and implementation phases. Consequently, the clients usually do not get what they want. Semantic Analysis expressed as ontology charts offers a very sound business analytical method that can be used to overcome these problems. The aim of this paper is, with the help of Meta Object Facility (MOF) meta-model, to advocate the use of Semantic Analysis and to present a method of transforming it to the Component Object Model (COM+) architecture, which is the Microsoft standard for developing application programs.

Creating Ontology Chart Using Economy Domain Ontologies

Ontologies are parts of an Artificial Intelligent advance research area where it is a very familiar topic in computer science. There are many domains of interests that can utilize ontolologies to use them as the knowledge repository. Economy is one of the widely interesting topics that anyone can relate to. This research simplifies ontologies concepts using economy domain to guide people in the field of economics to understand how ontology works as well as to guide the computer software developers to understand the basic concept of economy. The economy ontology is illustrated in ontology chart and hierarchical chart.