Representing Interactional and External Environmental Semantics using Unified Modelling Language (UML)

Object-oriented methodology is widely used in the information system development field. Nonetheless, recent research studies have discovered that the modelling grammars that use object-oriented methodology lack necessary constructs to represent certain real-world semantics. Therefore, the use of such grammars with their shortcomings can produce defective conceptual models, thereby producing defective information systems. Evermann and Wand (2005, 2009) studied this issue and proposed a set of rules for object-oriented grammatical constructs to represent static and behaviour semantics of a real-world phenomenon. This paper extends their work by proposing object-oriented grammatical rules for the interactional and external environmental semantics of a real-world phenomenon. This representation is exemplified using an object-oriented modelling grammar namely Unified Modelling Language (UML). Subsequently, the set of new rules has been validated using a case study. This extended UML facilitates seamless integration between the conceptual model and its system model

theory and empirical test

Successful information systems (IS) development requires the under- standing of the real world domain in which the IS is situated in and of which it is a representation. Developing such an understanding is the role of systems analy- sis, the first major step in IS development. Conceptual models developed during systems analysis are used to support understanding of and communication about the real world domain. Recent years have seen the emergence of the object-oriented approach in general and UML special cally for IS design and implementation. However, no generally accepted modelling language has been proposed for use during IS analysis. This study will examine the suitability of UML as a conceptual modelling lan- guage. This study comprises two parts. The first part studies UML from an ontological perspective, attaches real- world semantics and derives ontologically grounded rules for applying UML to conceptual modelling. It is argued that by following these rules, modellers will improve the performance of the resultant models. In a second step, the derived rules and proposed advantages must be empirically supported. An experimental study is designed for this purpose

Alternative representations for visual constrainst specification in the layered view model

Extensible Markup Language (XML), with its rich set of semantics and constraints, is becoming the dominant standard for storing, describing and interchanging data among various Enterprises Information Systems (EIS) and databases. With the increased reliance on such semi-structured data and schemas, there exists a requirement to model, design, and constrain semi-structured data and the associated semantics at a higher level of abstraction than at the instance or data level. But most semi-structured schema languages lack the ability to provide higher levels of abstraction, such as visual constraints, that are easily understood by humans. Conversely, though Object-Oriented (OO) conceptual models offers the power in describing and modelling real-world data semantics, constraints and their inter-relationships in a form that is precise and comprehensible to users, they provide insufficient modelling constructs for utilizing XML schema like data descriptions and constraints. Therefore, it is interesting to investigate conceptual and schema formalisms as a means of providing higher level semantics in the context of XML-related data engineering. In this paper, we present a visual constraint specification model for an XML layered view model. First we briefly outline the view model and then provide a detailed discussion on modelling issues related to view constraint specification using two OO modelling languages, namely OMG's UML/OCL and XML Semantics (XSemantic) nets. To demonstrate our concepts, we also provide an illustrative case study example based on a real-world application

Towards a Set Theoretical Approach to Big Data Analytics

Abstract—Formal methods, models and tools for social big data analytics are largely limited to graph theoretical approaches such as social network analysis (SNA) informed by relational sociology. There are no other unified modeling approaches to social big data that integrate the conceptual, formal and software realms. In this paper, we first present and discuss a theory and conceptual model of social data. Second, we outline a formal model based on set theory and discuss the semantics of the formal model with a real-world social data example from Facebook. Third, we briefly present and discuss the Social Data Analytics Tool (SODATO) that realizes the conceptual model in software and provisions social data analysis based on the conceptual and formal models. Fourth and last, based on the formal model and sentiment analysis of text, we present a method for profiling of artifacts and actors and apply this technique to the data analysis of big social data collected from Facebook page of the fast fashion company, H&M

On the role of domain ontologies in the design of domain-specific visual modeling langages

Domain-Specific Visual Modeling Languages should provide notations and abstractions that suitably support problem solving in well-defined application domains. From their user’s perspective, the language’s modeling primitives must be intuitive and expressive enough in capturing all intended aspects of domain conceptualizations. Over the years formal and explicit representations of domain conceptualizations have been developed as domain ontologies. In this paper, we show how the design of these languages can benefit from conceptual tools developed by the ontology engineering community

Generic unified modelling process for developing semantically rich, dynamic and temporal models

Models play a vital role in supporting a range of activities in numerous domains. We rely on models to support the design, visualisation, analysis and representation of parts of the world around us, and as such significant research effort has been invested into numerous areas of modelling; including support for model semantics, dynamic states and behaviour, temporal data storage and visualisation. Whilst these efforts have increased our capabilities and allowed us to create increasingly powerful software-based models, the process of developing models, supporting tools and /or data structures remains difficult, expensive and error-prone. In this paper we define from literature the key factors in assessing a model’s quality and usefulness: semantic richness, support for dynamic states and object behaviour, temporal data storage and visualisation. We also identify a number of shortcomings in both existing modelling standards and model development processes and propose a unified generic process to guide users through the development of semantically rich, dynamic and temporal models

Modeling views in the layered view model for XML using UML

In data engineering, view formalisms are used to provide flexibility to users and user applications by allowing them to extract and elaborate data from the stored data sources. Conversely, since the introduction of Extensible Markup Language (XML), it is fast emerging as the dominant standard for storing, describing, and interchanging data among various web and heterogeneous data sources. In combination with XML Schema, XML provides rich facilities for defining and constraining user-defined data semantics and properties, a feature that is unique to XML. In this context, it is interesting to investigate traditional database features, such as view models and view design techniques for XML. However, traditional view formalisms are strongly coupled to the data language and its syntax, thus it proves to be a difficult task to support views in the case of semi-structured data models. Therefore, in this paper we propose a Layered View Model (LVM) for XML with conceptual and schemata extensions. Here our work is three-fold; first we propose an approach to separate the implementation and conceptual aspects of the views that provides a clear separation of concerns, thus, allowing analysis and design of views to be separated from their implementation. Secondly, we define representations to express and construct these views at the conceptual level. Thirdly, we define a view transformation methodology for XML views in the LVM, which carries out automated transformation to a view schema and a view query expression in an appropriate query language. Also, to validate and apply the LVM concepts, methods and transformations developed, we propose a view-driven application development framework with the flexibility to develop web and database applications for XML, at varying levels of abstraction

Towards automated knowledge-based mapping between individual conceptualisations to empower personalisation of Geospatial Semantic Web

Geospatial domain is characterised by vagueness, especially in the semantic disambiguation of the concepts in the domain, which makes defining universally accepted geo- ontology an onerous task. This is compounded by the lack of appropriate methods and techniques where the individual semantic conceptualisations can be captured and compared to each other. With multiple user conceptualisations, efforts towards a reliable Geospatial Semantic Web, therefore, require personalisation where user diversity can be incorporated. The work presented in this paper is part of our ongoing research on applying commonsense reasoning to elicit and maintain models that represent users' conceptualisations. Such user models will enable taking into account the users' perspective of the real world and will empower personalisation algorithms for the Semantic Web. Intelligent information processing over the Semantic Web can be achieved if different conceptualisations can be integrated in a semantic environment and mismatches between different conceptualisations can be outlined. In this paper, a formal approach for detecting mismatches between a user's and an expert's conceptual model is outlined. The formalisation is used as the basis to develop algorithms to compare models defined in OWL. The algorithms are illustrated in a geographical domain using concepts from the SPACE ontology developed as part of the SWEET suite of ontologies for the Semantic Web by NASA, and are evaluated by comparing test cases of possible user misconceptions

Using Ontologies for the Design of Data Warehouses

Obtaining an implementation of a data warehouse is a complex task that forces designers to acquire wide knowledge of the domain, thus requiring a high level of expertise and becoming it a prone-to-fail task. Based on our experience, we have detected a set of situations we have faced up with in real-world projects in which we believe that the use of ontologies will improve several aspects of the design of data warehouses. The aim of this article is to describe several shortcomings of current data warehouse design approaches and discuss the benefit of using ontologies to overcome them. This work is a starting point for discussing the convenience of using ontologies in data warehouse design.Comment: 15 pages, 2 figure