Understanding understandability of conceptual models - what are we actually talking about? - Supplement

Investigating and improving the quality of conceptual models has gained tremendous importance in recent years. In general, model understandability is regarded one of the most important model quality goals and criteria. A considerable amount of empirical studies, especially experiments, have been conducted in order to investigate factors in-fluencing the understandability of conceptual models. However, a thorough review and reconstruction of 42 experiments on conceptual model understandability shows that there is a variety of different understandings and conceptualizations of the term model understandability. As a consequence, this term remains ambiguous, research results on model understandability are hardly comparable and partly imprecise, which shows the necessity of clarification what the conceptual modeling community is actually talking about when the term model understandability is used. This contribution represents a supplement to the article „ Understanding understandability of conceptual models – What are we actually talking about?” published in the Proceedings of the 31st International Conference on Conceptual Modeling (ER 2012) which aimed at overcoming the above mentioned shortcoming by investigating and further clarifying the concept of model understandability. This supplement contains a complete overview of Table 1 (p. 69 in the original contribution) which could only be partly presented in the conference proceedings due to space limitations. Furthermore, an erratum concerning the overview in Table 2 (p. 71 in the original contribution) is presented

Measuring User Beliefs and Attitudes towards Conceptual Schemas: Tentative Factor and Structural Equation Model

Human factors research in conceptual modeling is scarce. Recently, quality assurance frameworks, methods and tools for conceptual schemas have received increased research attention, but the perception of quality by schema users has largely been ignored in this stream of research. This paper proposes a tentative model of user beliefs and attitudes towards the quality of conceptual schemas. The proposed model is original in the sense that it includes both perceived semantic quality and perceived pragmatic quality measures. The paper also presents a new measurement instrument for the perceived semantic quality of conceptual schemas. This instrument was used in a classroom experiment that tested the proposed user beliefs and attitudes model. It was shown that the perceived semantic quality of a schema is directly related to its perceived usefulness and perceived ease of use and indirectly to the user satisfaction with the schema

Percieved Evaluability - Development of a Theoretical Model and a Measurement Scale

Sound conceptual models are commonly considered as an important factor for successful information systems (IS) development. Due to inaccurate conceptual specifications, IS projects can be delayed or even fail. Thus, thorough evaluation of models is a major concern in IS research. Consequently, theoretical models are required which elucidate the conditions for the successful evaluability of conceptual models. However, IS literature only provides little insights about the prerequisites of effective evaluation. Systematic investigations on the evaluability of conceptual models are missing. Therefore, is paper aims at two research results. Firstly, based on a comprehensive literature review we propose a theoretical model of perceived evaluability. This theoretical model rests on the influence of domain knowledge and the perceived comprehensibility of conceptual models as its two main impact factors. Secondly, to prepare an empirical evaluation of the theoretical model, the development of measurement scales is described. The first steps of this process are exemplified based on an inquiry of modeling experts and implications for testing our hypotheses are provide

MegSDF Mega-system development framework

A framework for developing large, complex software systems, called Mega-Systems, is specified. The framework incorporates engineering, managerial, and technological aspects of development, concentrating on an engineering process. MegSDF proposes developing Mega-Systems as open distributed systems, pre-planned to be integrated with other systems, and designed for change. At the management level, MegSDF divides the development of a Mega-System into multiple coordinated projects, distinguishing between a meta-management for the whole development effort, responsible for long-term, global objectives, and local managements for the smaller projects, responsible for local, temporary objectives. At the engineering level, MegSDF defines a process model which specifies the tasks required for developing Mega-Systems, including their deliverables and interrelationships. The engineering process emphasizes the coordination required to develop the constituent systems. The process is active for the life time of the Mega-System and compatible with different approaches for performing its tasks. The engineering process consists of System, Mega-System, Mega-System Synthesis, and Meta-Management tasks. System tasks develop constituent systems. Mega-Systems tasks provide a means for engineering coordination, including Domain Analysis, Mega-System Architecture Design. and Infrastructure Acquisition tasks. Mega-System Synthesis tasks assemble Mega-Systems from the constituent systems. The Meta-Management task plans and controls the entire process. The domain analysis task provides a general, comprehensive, non-constructive domain model, which is used as a common basis for understanding the domain. MegSDF builds the domain model by integrating multiple significant perceptions of the domain. It recommends using a domain modeling schema to facilitate modeling and integrating the multiple perceptions. The Mega-System architecture design task specifies a conceptual architecture and an application architecture. The conceptual architecture specifies common design and implementation concepts and is defined using multiple views. The application architecture maps the domain model into an implementation and defines the overall structure of the Mega-System, its boundaries, components, and interfaces. The infrastructure acquisition task addresses the technological aspects of development. It is responsible for choosing, developing or purchasing, validating, and supporting an infrastructure. The infrastructure integrates the enabling technologies into a unified platform which is used as a common solution for handling technologies. The infrastructure facilitates portability of systems and incorporation of new technologies. It is implemented as a set of services, divided into separate service groups which correspond to the views identified in the conceptual architecture

Tackling Dierent Business Process Perspectives

Business Process Management (BPM) has emerged as a discipline to design, control, analyze, and optimize business operations. Conceptual models lie at the core of BPM. In particular, business process models have been taken up by organizations as a means to describe the main activities that are performed to achieve a specific business goal. Process models generally cover different perspectives that underlie separate yet interrelated representations for analyzing and presenting process information. Being primarily driven by process improvement objectives, traditional business process modeling languages focus on capturing the control flow perspective of business processes, that is, the temporal and logical coordination of activities. Such approaches are usually characterized as \u201cactivity-centric\u201d. Nowadays, activity-centric process modeling languages, such as the Business Process Model and Notation (BPMN) standard, are still the most used in practice and benefit from industrial tool support. Nevertheless, evidence shows that such process modeling languages still lack of support for modeling non-control-flow perspectives, such as the temporal, informational, and decision perspectives, among others. This thesis centres on the BPMN standard and addresses the modeling the temporal, informational, and decision perspectives of process models, with particular attention to processes enacted in healthcare domains. Despite being partially interrelated, the main contributions of this thesis may be partitioned according to the modeling perspective they concern. The temporal perspective deals with the specification, management, and formal verification of temporal constraints. In this thesis, we address the specification and run-time management of temporal constraints in BPMN, by taking advantage of process modularity and of event handling mechanisms included in the standard. Then, we propose three different mappings from BPMN to formal models, to validate the behavior of the proposed process models and to check whether they are dynamically controllable. The informational perspective represents the information entities consumed, produced or manipulated by a process. This thesis focuses on the conceptual connection between processes and data, borrowing concepts from the database domain to enable the representation of which part of a database schema is accessed by a certain process activity. This novel conceptual view is then employed to detect potential data inconsistencies arising when the same data are accessed erroneously by different process activities. The decision perspective encompasses the modeling of the decision-making related to a process, considering where decisions are made in the process and how decision outcomes affect process execution. In this thesis, we investigate the use of the Decision Model and Notation (DMN) standard in conjunction with BPMN starting from a pattern-based approach to ease the derivation of DMN decision models from the data represented in BPMN processes. Besides, we propose a methodology that focuses on the integrated use of BPMN and DMN for modeling decision-intensive care pathways in a real-world application domain

Considerations for a design and operations knowledge support system for Space Station Freedom

Engineering and operations of modern engineered systems depend critically upon detailed design and operations knowledge that is accurate and authoritative. A design and operations knowledge support system (DOKSS) is a modern computer-based information system providing knowledge about the creation, evolution, and growth of an engineered system. The purpose of a DOKSS is to provide convenient and effective access to this multifaceted information. The complexity of Space Station Freedom's (SSF's) systems, elements, interfaces, and organizations makes convenient access to design knowledge especially important, when compared to simpler systems. The life cycle length, being 30 or more years, adds a new dimension to space operations, maintenance, and evolution. Provided here is a review and discussion of design knowledge support systems to be delivered and operated as a critical part of the engineered system. A concept of a DOKSS for Space Station Freedom (SSF) is presented. This is followed by a detailed discussion of a DOKSS for the Lyndon B. Johnson Space Center and Work Package-2 portions of SSF

THE EFFECT OF DOMAIN FAMILIARITY ON MODELLING ROLES: AN EMPIRICAL STUDY

Conceptual modelling (CM) involves analysts working with domain experts to create a representation of the domain called a conceptual model. We address two issues of CM research. The first deals with the meaning that conceptual models convey. We propose guidelines for how analysts can reflect the concept of a “role” in a conceptual model using the extended entity relationship (EER) method. Roles are important in organizations, but analysts have little guidance about how to model them. The second issue focuses on the effect of prior domain familiarity of the users on the understanding of conceptual models. We conducted a laboratory study to determine how domain familiarity affects users’ understanding of conceptual models that represent roles. Our results indicate that conceptual models can be developed to show roles more clearly but that the benefit of doing so depends on model readers’ familiarity with the modeled domain. In particular, our guidelines will be most useful when users have moderate knowledge of the domain shown in the model. When users are very familiar with the domain, the guidelines do not seem to have much benefit. However, when users have very little knowledge of the domain, the guidelines do help to a certain extent

What we know and what we do not know about DMN

The recent Decision Model and Notation (DMN) establishes business decisions as first-class citizens of executable business processes. This research note has two objectives: first, to describe DMN's technical and theoretical foundations; second, to identify research directions for investigating DMN's potential benefits on a technological, individual and organizational level. To this end, we integrate perspectives from management science, cognitive theory and information systems research