Palash Bera

Using Ontology Languages for Conceptual Modeling

Conceptual models are used to support understanding of and communication about application domains in information systems development. Such models are created using modeling grammars usually employing graphic representation. To be effective, a grammar should support precise representation of domain concepts and their relationships. Ontology languages such as OWL emerged to define terminologies to support information sharing on the Web. These languages have features that enable representation of semantic relationships among domain concepts and of domain rules, not readily possible with extant conceptual modeling techniques. However, the emphasis in ontology languages has been on formalization and being computer-readable, not on how they can be used to convey domain semantics. Hence, it is unclear how they can be used as conceptual modeling grammars. We suggest using philosophically based ontological principles to guide the use of OWL as a conceptual modeling grammar. The paper presents specific guidelines for creating conceptual models in OWL and demonstrates, via example, the application of the guidelines to creating representations of domain phenomena. To test the effectiveness of the guidelines we conducted an empirical study comparing how well diagrams created with the guidelines support domain understanding in comparison to diagrams created without the guidelines. The results indicate that diagrams created with the guidelines led to better domain understanding of participants.

How colors in business dashboards affect users' decision making

Business dashboards that overuse or misuse colors cause cognitive overload for users who then take longer to make decisions.

Guidelines for using UML association classes and their effect on domain understanding in requirements engineering

The analysis and description of the application domain are important parts of the requirements engineering process. Domain descriptions are frequently represented as models in the de-facto standard unified modeling language (UML). Recent research has specified the semantics of various UML language elements for domain modeling, based on ontological considerations. In this paper, we empirically examine ontological modeling guidelines for the UML association construct, which plays a central role in UML class diagrams. Using an experimental study, we find that some, but not all, of the proposed guidelines lead to better application domain models. We use a process-tracing study to investigate in more detail the effects of ontological guidelines. The combined results indicate that ontological guidelines can improve the usefulness of UML class diagrams for describing the application domain, and thus have the potential to improve downstream system development activities and ultimately affect the successful information systems implementation.

Guest editorial for EMMSAD’2017 special section

The EMMSAD (Exploring Modeling Methods for Systems Analysis and Development) series has produced 22 events, associated with CAiSE (Conference on Advanced Information Systems Engineering), from 1996 to 2017. From 2009, EMMSAD has become a 2-day working conference. The topics addressed by the EMMSAD series focus on modeling methods for software systems, enterprises, and business processes, as well as their evaluation through a variety of empirical and non-empirical approaches. The aims, topics, and history of EMMSAD can be found on the Web site at http://www.emmsad.org/.

Improving the representation of roles in conceptual modeling: theory, method, and evidence

Conceptual models represent the Organizational domain for which an information system is developed. These models are important tools in defining the requirements for the system. When describing an Organization or part of it, a key concept is the notion of roles played by actors in the domain. Actors in an Organization act in various roles, hence, showing that roles in a conceptual model can promote understanding of how the Organization works. However, despite the importance of roles in understanding Organizations and their prevalence in various aspects of information systems development, no consensus exists on what roles are, or how to represent them in conceptual models. In this paper, we formally define role as a conceptual modeling construct based on literature analysis, ontological concepts, and principles of classification. Using this definition, we derive guidelines for representing roles in conceptual models and suggest rules for modeling roles with the widely used extended entity-relationship grammar. Finally, we test the effectiveness of the modeling rules by conducting an experimental study to compare the domain understanding of readers using two types of conceptual modeling scripts. One script was obtained by violating the rules and the other by not violating the rules. We obtained data on domain understanding (using problem-solving questions) and on the process of understanding (using eye tracking). The results indicate that the role-based rules are not only useful for understanding the models but also provide direct clues as to why this is so.

The effects of construct redundancy on readers' understanding of conceptual models

Thispaperinvestigatestheeffectofconstructredundancyonreaders’understandingofconceptual models.Conceptualmodelsplayacrucialroleinunderstandingthedomainrelatedtoinformation systemdevelopment.Theclarityofsuchmodelscanbecompromisediftheyareconstructedusinga conceptualmodellinggrammarexhibitingconstructredundancywhereonereal-worldphenomenon mapstotwoormoregrammarconstructs.Withtwoempiricalstudiesonsolvingdomain-related problemsusingUnifiedModelingLanguage(UML)classdiagramsasconceptualdomainmodels, itwasfoundthatwhenconstructredundancyispresentatdifferentstrengths,thentheeffectofthe redundancyontheunderstandingofamodeldependsonthemodelingknowledgeofthereader.Novice readerswithminimalmodelingknowledgefindmodelsdifficulttointerpretwhenastronglevelof redundancycausedbydistinctconstructredundancyexists.However,whenthemodelshaveaweak levelofredundancythenthesereadersfindthemeasiertounderstandcomparedtomodelswithout redundancy.Incontrast,trainedreadersareindifferenttoaweaklevelofredundancyinamodel. KEywoRDS Conceptual Models, Information System Development, Redundancy, Unified Modeling Language (UML)

Do Distracting Dashboards Matter? Evidence from an Eye Tracking Study

This paper analyzes the effect of distraction on using dashboards. Distraction in dashboards was introduced by increasing the non-pixel data and not highlighting the task relevant area. Eye tracking technology was used to precisely measure how much time and effort users make to understand the dashboards. Eye tracking technology was used as it provides the details of the mental processes by which users make decision regarding the tasks. A laboratory study was conducted using eye tracking technology to understand how subjects use two types of dashboards- distracted and non-distracted to perform certain tasks. Results show that although both distracted and non-distracted groups performed equally well in answering the tasks, the distracted group had significantly high overall fixation time and count. This shows that the distracted group spent more time and effort in answering the task. Also, it was found that the non-distracted group spent more time and effort on the specific area of the dashboard where the answer of the task was available.