Modeling events as entities in object-oriented conceptual modeling languages

Most current conceptual modeling languages and methods do not model events as entities. We argue that, at least in object-oriented (O-O) languages, modeling events as entities provides substantial benefits. We show that a method for behavioral modeling that deals with event and entity types in a uniform way may yield better behavioral schemas. The proposed method makes extensive use of language constructs such as constraints, derived types, derivation rules, type specializations and operations, which are present in all complete O-O conceptual modeling languages. The method can be adapted to most O-O languages. In this paper we explain its adaptation to the UML.     

A method for the definition of integrity constraints in object-oriented conceptual modeling languages

We propose a new method that eases the definition of integrity constraints in object-oriented conceptual modeling languages. The essence of the method is to represent constraints by special operations that we call constraint operations. The formal specification of these operations is the definition of the corresponding constraints. The method allows the specialization of constraints and the definition of exceptions. The main application of the method is for static constraints. However, a variant of it can also be applied for creation-time and deletion-time constraints, two particular classes of temporal constraints. The method can be adapted to any object-oriented language, and we show its adaptation to the UML. We also show that our method has several advantages over existing methods.     

Using a trope-based foundational ontology for bridging different areas of concern in ontology-driven conceptual modeling

In recent years, ontology-driven reference models have gained much attention in the literature due to their potential key role in activities such as complex information modeling and semantic interoperability. The engineering process of these conceptual models should account for different phases addressing different areas of concern. In an initial phase of conceptual domain modeling, the target modeling artifacts should be constructed with the goal of maximizing quality attributes such as expressivity and truthfulness to the represented domain in reality. In a subsequent development phase, the resulting domain models can be used to guide the design decisions in the construction of different implementation artifacts addressing different computational concerns. In this paper, we present a philosophically sound, cognitively-oriented and formally characterized foundational theory of objects and tropes (property-instances). Moreover, we use this theory to bring about engineering contributions to both the aforementioned phases of ontology-driven conceptual modeling. Firstly, we show how this theory has been used to (re)design a system of modeling primitives underlying the conceptual domain modeling language OntoUML. Furthermore, we provide precise directives on how to map conceptual domain models in this language to their implementation in less-expressive computationally-oriented codification languages. In particular, we address here a mapping strategy to OWL (Web Ontology Language) that partially preserves the modal-temporal semantics of OntoUML. Finally, we discuss computational support for the proposed approach in terms of conceptual model construction, automatic transformation and temporal querying.     

A conceptual modeling framework for discrete event simulation using hierarchical control structures

Conceptual Modeling (CM) is a fundamental step in a simulation project. Nevertheless, it is only recently that structured approaches towards the definition and formulation of conceptual models have gained importance in the Discrete Event Simulation (DES) community. As a consequence, frameworks and guidelines for applying CM to DES have emerged and discussion of CM for DES is increasing. However, both the organization of model-components and the identification of behavior and system control from standard CM approaches have shortcomings that limit CM’s applicability to DES. Therefore, we discuss the different aspects of previous CM frameworks and identify their limitations. Further, we present the Hierarchical Control Conceptual Modeling framework that pays more attention to the identification of a models’ system behavior, control policies and dispatching routines and their structured representation within a conceptual model. The framework guides the user step-by-step through the modeling process and is illustrated by a worked example.     

Complexity and clarity in conceptual modeling: Comparison of mandatory and optional properties

Two versions of the entity-relationship model (ERM) are compared in this empirical study. One model grammar uses optional properties and the other employs mandatory properties and subtypes. The optional grammar produces apparently less complex models than the mandatory with subtypes. An ontological analysis indicates that mandatory properties may be superior to optional properties in providing clearer representations. The Cognitive Theory of Multimedia Learning is used to hypothesize superior local information provided by mandatory properties can lead to improved viewer understanding of a model. An experiment comparing the two ERM grammars is described and results confirm the use of mandatory relationships leads to improved understanding even though the model is apparently more complex. These results suggest clarity within the model may be more important than the apparent complexity of the model when a model is used for developing domain understanding.     

What do the pictures mean? Guidelines for experimental evaluation of representation fidelity in diagrammatical conceptual modeling techniques

It is important to articulate the objectives and underlying assumptions behind a growing body of experimental research in conceptual modeling. We provide four guidelines for developing materials for experiments that evaluate conceptual modeling techniques, under the assumption that a primary purpose of conceptual modeling is to facilitate communication between analysts and users in validating domain knowledge during systems development. These guidelines assist in developing experimental materials that support meaningful tests of domain semantics. We present empirical evidence indicating the value of two of the guidelines. We also evaluate selected recent experiments on conceptual modeling with respect to the guidelines.     

A framework for empirical evaluation of conceptual modeling techniques

The paper presents a framework for the empirical evaluation of conceptual modeling techniques used in requirements engineering. The framework is based on the notion that modeling techniques should be compared via their underlying grammars. The framework identifies two types of dimensions in empirical comparisons—affecting and affected dimensions. The affecting dimensions provide guidance for task definition, independent variables and controls, while the affected dimensions define the possible mediating variables and dependent variables. In particular, the framework addresses the dependence between the modeling task—model creation and model interpretation—and the performance measures of the modeling grammar. The utility of the framework is demonstrated by using it to categorize existing work on evaluating modeling techniques. The paper also discusses theoretical foundations that can guide hypothesis generation and measurement of variables. Finally, the paper addresses possible levels for categorical variables and ways to measure interval variables, especially the grammar performance measures.     

Ontologies for conceptual modeling: their creation, use, and management

Although ontologies have been proposed as an important and natural means of representing real world knowledge for the development of database designs, most ontology creation is not carried out systematically. To be truly useful, a repository of ontologies, organized by application domain is needed, along with procedures for creating and integrating ontologies into database design methodologies. This research proposes a methodology for creating and managing domain ontologies. An architecture for an ontology management system is presented and implemented in a prototype. Empirical validation of the prototype demonstrates the effectiveness of the research.     

An active modeling system for econometric analysis

This paper examines the feasibility of developing an “artificially intelligent econometrician” as an active decision support system (ADSS) in the sense articulated by [Manheim, 1988]. We review the system components of an ADSS and then relate them to a modeling system for econometric analysis that we have implemented. We present the query language of the PERM (Progressive EconometRic Modeling) system and offer an extension to the language based on process-oriented constructs for model integration. The query language and its extension correspond to the ADSS's user-directed and computer-directed process managers, respectively. Schemas representing statistical strategies are stored as processes in the extended language and serve as the econometric knowledge base. We suggest an approach to building an inference processor for this system based on experiments to record user query protocols and relate them to the schemas in the knowledge base. The connection between user processes and schemas is implemented by demon constructs in the extended language. Finally, we examine the extent to which our proposed system constitutes an ADSS.     

ODAP: an ontological approach for expressing the semantics of analysis patterns in conceptual modeling

Systematic software reuse is emerging as a promising route to improved software development productivity and quality. While many benefits of patterns reuse have been identified, there is a need to develop a mechanism for supporting and automating the reuse of relevant analysis patterns for conceptual modeling. To enable effective reuse of analysis patterns, extant approaches require judgment about correctly instantiating and combining the analysis patterns. Building on prior research in ontology and conceptual modeling, we propose a “top-down” approach, referred to as Ontology for Describing Analysis Patterns (ODAP), to explicitly express the semantics of analysis patterns. We show how ODAP helps provide a mechanism to identify appropriate instances of analysis patterns including the discovery of valid combinations with other patterns in a patterns base. Thus, ODAP can enable communication of the meaning of the analysis pattern constructs to modelers and be the basis for a design support environment that supports the development of conceptual schemas using analysis patterns.

Unified meta-modeling framework using bond graph grammars for conceptual modeling

Existing techniques for developing large scale complex engineering systems are predominantly software based and use Unified Modeling Language (UML). This leads to difficulties in model transformation, analysis, validation, verification and automatic code generation. Currently no general frameworks are available to bridge the concept-code gap rampant in design and development of complex, software-intensive mechatronic systems called cyber-physical systems. To fill this gap and provide an alternative approach to Object Management Group’s UML/SysML/OCL combination, we propose: Bond Graph based Unified Meta-Modeling Framework (BG-UMF). BG-UMF is a practical and viable alternative and uses a novel hybrid approach based on model unification and integration. The focus is on conceptual design and development of executable models for large systems. The viability of the framework is demonstrated through an application scenario: conceptual design and development of a navigation and control system for a rotor-craft UAV.     

Information technology adoption for sustainable development: green e-books as an example*

ABSTRACT

In recent years, due to increasing awareness of the need for environmental protection, there have been significant efforts to improve consumers’ acceptance of green information technology(IT) products for sustainable development. This study first investigated how knowledge about a green IT product (e-books) influences consumers’ planning processes by using the technology acceptance model and the theory of planned behavior. Data from 320 respondents were analyzed using structural equation modeling to examine the hypothesized relationships in the research model. Results show that perceived usefulness, attitudes, subjective norms, and perceived behavioral control have a significant and positive impact on the intention to purchase e-books. Results also show the moderating effect of consumers’ knowledge about the environmental friendliness of e-books on their intention to buy e-books. Finally, important implications of the findings are discussed, and directions for future research are also provided in this paper.