Using Insights from Cognitive Neuroscience to Investigate the Effects of Event-Driven Process Chains on Process Model Comprehension

Business process models have been adopted by enterprises for more than a decade. Especially for domain experts, the comprehension of process models constitutes a challenging task that needs to be mastered when creating or reading these models. This paper presents the results we obtained from an eye tracking experiment on process model comprehension. In detail, individuals with either no or advanced expertise in process modeling were confronted with models expressed in terms of Event-driven Process Chains (EPCs), reflecting different levels of difficulty. The first results of this experiment confirm recent findings from one of our previous experiments on the reading and comprehension of process models. On one hand, independent from their level of exper-tise, all individuals face similar patterns, when being confronted with process models exceeding a certain level of difficulty. On the other, it appears that process models expressed in terms of EPCs are perceived differently compared to process models specified in the Business Process Model and Notation (BPMN). In the end, their generalization needs to be confirmed by additional empirical experiments. The presented expe-riment continues a series of experiments that aim to unravel the factors fostering the comprehension of business process models by using methods and theories stemming from the field of cognitive neuroscience and psychology

Cognitive Insights into Business Process Model Comprehension: Preliminary Results for Experienced and Inexperienced Individuals

Process modeling constitutes a fundamental task in the context of process-aware information systems. Besides process model creation, the reading and understanding of process models is of utmost importance. To better understand the latter, we have developed a conceptual framework focusing on the comprehension of business process models. By adopting concepts from cognitive neuroscience and psychology, the paper presents initial results from a series of eye tracking experiments on process model comprehension. The results indicate that experiences with process modeling have an influence on overall model comprehension. In turn, with increasing process model complexity, individuals with either no or advanced expertise in process modeling do not significantly differ with respect to process model comprehension. The results further indicate that both groups face similar challenges in reading and comprehending process models. The conceptual framework takes these results into account and provides the basis for the further experiments

LawV : towards an ontology-based visual modeling language in the legal domain

There has been an increase use of Domain-Specific Visual Modeling Language (DSVML) as a means of improving models’ comprehensibility and, consequently, stakeholders’ productivity. Combining the benefits of DSVMLs and of an ontological approach for designing and evaluating DSVMLs, we present, in this paper, the first-steps towards an ontology-based DSVML in the legal domain called LawV. The main purpose of LawV is to provide for a visual symbolic representation for legal statements. LawV has been built by applying an ontology-based language engineering method called PoNTO-S and UFO-L, a legal core ontology. To evaluate LawV, we instantiate a judicial case selected from the database of Appeal Court of the Esp ́ırito Santo State in Brazil

Eye Tracking Experiments on Process Model Comprehension: Lessons Learned

For documenting business processes, there exists a plethora of process modeling languages. In this context, graphical process models are used to enhance the process comprehensibility of the stakeholders involved. The large number of available modeling languages, however, aggravates process model comprehension and increases the knowledge gap between domain and modeling experts. Upon this, one major challenge is to identify factors fostering the comprehension of process models. This paper discusses the experiences we gathered with the use of eye tracking in experiments on process model comprehension and the lessons learned in this context. The objective of the experiments was to study the comprehension of process models expressed in terms of four different modeling languages (i.e., BPMN, eGantt, EPC, and Petri Net). This paper further provides recommendations along nine identified categories that can foster related experiments on process model comprehension

A Survey-based Analysis of Principles to Evaluate Visual Notations of Process Modeling Languages

Process modeling languages such as BPMN or EPC provide a set of graphical constructs defining their visual notations. The visual notation is one comparison criteria in favor of a process modeling language. Usually, the first choice for the evaluation of visual notations are the principles of the Physics of Notation (PoN) theory. Their vague operationalization, however, gives room for contradictory recommendations how to improve visual notations. Therefore, the intention of this paper is to identify recent empirical studies to visual notations of process modeling languages, which might contribute to a better understanding of PoN principles. A comprehensive literature survey has been conducted showing a confirmation of the PoN principles and identifying refinements for their operationalization. We applied our findings to an evaluation of the visual notation of BPMN from 2012 and showed advancements. Our findings define the current guidelines for evaluating and improving visual notations of process modeling languages

An Ontology-Based Process for Domain-Specific Visual Language Design

Em Modelagem Conceitual, tem ocorrido um interesse crescente em Linguagens de Modelagem Visuais Específicas de Domínio ( Domain-Specific Visual Modeling Languages (DSVMLs)) e no suporte que elas provêem para compr eensão do domínio de um problema e comunicação entre modelado res e interessados. Assim, é importante providenciar diretrizes para o design de DSVMLs. Por muitos anos, o foco de pesquisa tem sido na sintaxe abstrata, enqu anto a sintaxe concreta tem recebido menor atenção. Isso é um infortúnio, pois a sintaxe visual impacta significativamente a capacidade de comunicação e de resolução de problemas de modelos conceituais Um dos trabalhos mais disseminados para análise e d esign de aspectos visuais de linguagens de modelagem é a Física das Notações (Po N). PoN define um conjunto de princípios usado para analisar e projetar notaçõ es visuais cognitivamente eficientes. Contudo, PoN tem lacunas, tais como: (i ) Falta um método para aplicar seus princípios; (ii) O design de símbolos não cria sistematicamente símbolos que refletem entidades do mundo real. Nesta pesquisa, nós apresentamos a Física das Notações Sistematizada (PoN-S) para resolver a lacuna (i). PoN-S estabelece um con junto ordenado de atividades de design e sugere quando aplicar os princípios de PoN . Ela também propõe grupos de princípios de PoN. Outra maneira de melhorar a qualidade de DSVMLs é a aplicação de teorias ontológicas, mas ontologias podem ser aplicadas com sucesso no design de sintaxes concretas como tem sido aplicadas para a s intaxe abstrata? Guizzardi (2013) propoem diretrizes ontológicas baseadas na O ntologia de Fundamentação Unificada (UFO) para auxiliar no design de notações visuais. Contudo, tais diretrizes também tem lacunas: (iii) São diretrizes isoladas e não parte de um processo de design; (iv) O conjunto de distinções ontológicas, é restrito; (v) As diretrizes ontológicas são restritas a serem aplicadas no esta belecimento dos símbolos de uma DSVMLs. Para resolver as lacunas (ii) até (v) nós combinamo s as diretrizes ontológicas baseadas em UFO com PoN-S, originando a Física das Notações Ontologizada e Sistematizada (PoNTO-S) . PoNTO-S é um processo de design sistematizado par a sintaxes concretas de DSVMLs que conecta a sintaxe concreta com o significado do mundo-real (isto é, o significado ontológico). Este projeto é um processo de Design Science com di ferentes iterações, cada uma produzindo artefatos próprios. O problema de design é o design de sintaxes concretas de DSVMLs. Os artefatos são melhorias de duas soluções existentes: PoN e diretrizes ontológicas baseadas em UFO. PoN-S e PoNTO-S são classificados como teorias de design, visto serem p rocesso de design. Nós também investimos em estudos empíricos. Foram executados e studos exploratórios para dar suporte as indicações coletadas durante a revisão d e literatura e guiar algumas decisões. Após desenvolver versões de PoN-S e PoNTO -S nós aplicamos novos estudos empíricos que geraram evidências para concl uirmos que PoN-S e PoNTO-S são utéis, e que tais abordagens podem evoluir, dan do origem a abordagens ainda mais úteis