Ranking of business process simulation tools with DEX/QQ hierarchical decision model

The omnipresent need for optimisation requires constant improvements of companies’ business processes (BPs). Minimising the risk of inappropriate BP being implemented is usually performed by simulating the newly developed BP under various initial conditions and “what-if” scenarios. An effectual business process simulations software (BPSS) is a prerequisite for accurate analysis of an BP. Characterisation of an BPSS tool is a challenging task due to the complex selection criteria that includes quality of visual aspects, simulation capabilities, statistical facilities, quality reporting etc. Under such circumstances, making an optimal decision is challenging. Therefore, various decision support models are employed aiding the BPSS tool selection. The currently established decision support models are either proprietary or comprise only a limited subset of criteria, which affects their accuracy. Addressing this issue, this paper proposes a new hierarchical decision support model for ranking of BPSS based on their technical characteristics by employing DEX and qualitative to quantitative (QQ) methodology. Consequently, the decision expert feeds the required information in a systematic and user friendly manner. There are three significant contributions of the proposed approach. Firstly, the proposed hierarchical model is easily extendible for adding new criteria in the hierarchical structure. Secondly, a fully operational decision support system (DSS) tool that implements the proposed hierarchical model is presented. Finally, the effectiveness of the proposed hierarchical model is assessed by comparing the resulting rankings of BPSS with respect to currently available results

Behavioral analysis of scientific workflows with semantic information

The recent development in scientific computing related areas has shown an increasing interest in scientific workflows because of their abilities to solve complex challenges. Problems and challenges that were too heavy or time-consuming can be solved now in a more efficient manner. Scientific workflows have been progressively improved by means of the introduction of new paradigms and technologies, being the semantic area one of the most promising ones. This paper focuses on the addition of semantic Web techniques to the scientific workflow area, which facilitates the integration of network-based solutions. On the other hand, a model checking technique to study the workflow behavior prior to its execution is also described. Using the Unary RDF annotated Petri net formalism (U-RDF-PN), scientific workflows can be improved by adding semantic annotations related to the task descriptions and workflow evolution. This technique can be applied using a complete environment for the model checking of this kind of workflows that is also depicted in this work. Finally, the proposed methodology is exemplified by its application to a couple of known scientific workflows: the First Provenance Challenge and the InterScan protein analysis workflow