A Context-based Framework for Improving Decision Making in Scientific Workflow
Scientific workflow (SWF) is considered as a way to automate the decision making with a compilation of known sequences of actions for routine procedure. Current scientific workflow systems lack abilities, in the one hand, in capturing the context of the case of the scientific workflow, and, in the other hand, in delivering the real-time assistance to help the user make effective decisions. We propose a context-based framework to improve decision making in SWF. This framework allows making context explicit and realizing the contextualization of the workflows stored in the SWF repository. We use Contextual Graphs (CxGs) as formalism for representing uniformly all the ingredients of a decision-making process in a SWF, so that scientists can customize information and formalize their research and strategies. An example drawn from an application in virtual screening is given to illustrate the potentiality of our contextbased framework. Finally, we conclude that a contextbased formalism such as CxGs is the key element to enhance decision-making support in SWF systems.
artificial intelligence context scientific workflow decision making human computer interaction contextual graphs
Xiaoliang Fan Ruisheng Zhang Lian Li Patrick Br(e)zillon
School of Mathematics and Statistics School of Information Science and Engineering Lanzhou Universit School of Information Science and Engineering Lanzhou University, Lanzhou, China School of Mathematics and Statistics School of Information Science and Engineering Lanzhou Universit Laboratoire dInformatique de Paris 6 Universit(e) Pierre et Marie Curie Paris, France
国际会议
上海
英文
15-19
2011-03-11（万方平台首次上网日期，不代表论文的发表时间）