Development of a pattern library and a decision support system for building applications in the domain of scientific workflows for e-Science

Abstract

Karastoyanova et al. created eScienceSWaT (eScience SoftWare Engineering Technique), that targets at providing a user-friendly and systematic approach for creating applications for scientific experiments in the domain of e-Science. Even though eScienceSWaT is used, still many choices about the scientific experiment model, IT experiment model and infrastructure have to be made. Therefore, a collection of best practices for building scientific experiments is required. Additionally, these best practice need to be connected and organized. Finally, a Decision Support System (DSS) that is based on the best practices and enables decisions about the various choices for e-Science solutions, needs to be developed. Hence, various e-Science applications are examined in this thesis. Best practices are recognised by abstracting from the identified problem-solution pairs in the e-Science applications. Knowledge and best practices from natural science, computer science and software engineering are stored in patterns. Furthermore, relationship types among patterns are worked out. Afterwards, relationships among the patterns are defined and the patterns are organized in a pattern library. In addition, the concept for a DSS that provisions the patterns and its prototypical implementation are presented.