Dynamic Workflow-Engine

We present and assess the novel thesis that a language commonly accepted for requirement elicitation is worth using for configuration of business process automation systems. We suggest that Cockburn's well accepted requirements elicitation language - the written use case language, with a few extensions, ought to be used as a workflow modelling language. We evaluate our thesis by studying in detail an industrial implementation of a workflow engine whose workflow modelling language is our extended written use case language; by surveying the variety of business processes that can be expressed by our extended written use case language; and by empirically assessing the readability of our extended written use case language. Our contribution is sixfold: (i) an architecture with which a workflow engine whose workflow modelling language is an extended written use case language can be built, configured, used and monitored; (ii) a detailed study of an industrial implementation of use case oriented workflow engine; (iii) assessment of the expressive power of the extended written use case language which is based on a known pattern catalogue; (iv) another assessments of the expressive power of the extended written use case language which is based on an equivalence to a formal model that is known to be expressive; (v) an empirical evaluation in industrial context of the readability of our extended written use case language in comparison to the readability of the incumbent graphical languages; and (vi) reflections upon the state of the art, methodologies, our results, and opportunities for further research. Our conclusions are that a workflow engine whose workflow modelling language is an extended written use case language can be built, configured, used and monitored; that in an environment that calls upon an extended written use case language as a workflow modelling language, the transition between the modelling and verification state, enactment state, and monitoring state is dynamic; that a use case oriented workflow engine was implemented in industrial settings and that the approach was well accepted by management, workflow configuration officers and workflow participants alike; that the extended written use case language is quite expressive, as much as the incumbent graphical languages; and that in industrial context an extended written use case language is an efficient communication device amongst stakeholders

Investigating Differences between Graphical and Textual Declarative Process Models

Declarative approaches to business process modeling are regarded as well suited for highly volatile environments, as they enable a high degree of flexibility. However, problems in understanding declarative process models often impede their adoption. Particularly, a study revealed that aspects that are present in both imperative and declarative process modeling languages at a graphical level-while having different semantics-cause considerable troubles. In this work we investigate whether a notation that does not contain graphical lookalikes, i.e., a textual notation, can help to avoid this problem. Even though a textual representation does not suffer from lookalikes, in our empirical study it performed worse in terms of error rate, duration and mental effort, as the textual representation forces the reader to mentally merge the textual information. Likewise, subjects themselves expressed that the graphical representation is easier to understand

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

Modelling suggests ABO histo-incompatibility may substantially reduce SARS-CoV-2 transmission

Several independent datasets suggest blood type A is over-represented and type O under-represented among COVID-19 patients. However, blood group antigens appear not to be conventional susceptibility factors in that they do not affect disease severity, and the relative risk to non-O individuals is attenuated when population prevalence is high. Here, I model a scenario in which ABO transfusion incompatibility reduces the chance of a patient transmitting the virus to an incompatible recipient – thus in Western populations type A and AB individuals are “super-recipients” while type O individuals are “super-spreaders”. This results in an offset in the timing of the epidemic among individuals of different blood types, and an increased relative risk to type A/AB patients that is most pronounced during early stages of the epidemic. However, once the majority of any given population is infected, the relative risk to each blood type approaches unity. Published data on COVID-19 prevalence from regions in the early stages of the SARS-CoV-2 epidemic suggests that if this model holds true, ABO incompatibility reduces virus transmissibility by at least 60 %. Exploring the implications of this model for vaccination strategies shows that paradoxically, targeted vaccination of either high-susceptibility type A/AB or “super-spreader” type O individuals is less effective than random vaccination at blocking community spread of the virus. Instead, the key is to maintain blood type diversity among the remaining susceptible individuals. Given the good agreement between this model and observational data on disease prevalence, the underlying biochemistry urgently requires experimental investigation