# Process Makna - **A Semantic Wiki For Scientific** Workflows

Adrian Paschke, Zhili Zhao Freie Universität Berlin
[Paschke|Zhili] AT inf.fu-berlin.de Abstract: Virtual e-Science infrastructures supporting Web-based scientific workflows are an example for knowledge-intensive collaborative and weakly-structured processes where the interaction with the human scientists during process execution plays a central role. In this paper we propose the lightweight dynamic user-friendly interaction with humans during execution of scientific workflows via the low-barrier approach of Semantic Wikis as an intuitive interface for non-technical scientists. Our Process Makna Semantic Wiki system is a novel combination of an business process management system adapted for scientific workflows with a Corporate Semantic Web Wiki user interface supporting knowledge intensive human interaction tasks during scientific workflow execution.

## 1. **Introduction**

Scientific Workflows underlie the large-scale complex e-science applications and infrastructures, e.g., lab experiments, simulations, complex knowledge-intensive research questions. Compared with business workflows, a scientific workflow has special features such as computation, data or transaction intensity, knowledge-intensive human expert interaction, and a large number of activities including management of virtual organisations such as research collaborations and research teams. The described emerging computing infrastructures with powerful computing and resource sharing capabilities present the potential for accommodating those special features.

There are many industrial-strength Business Process Management (BPM) workflow tools available. However when it comes to knowledge-intensive scientific workflows, practical experiences have shown that the modelled scientific process representations are often not enacted correctly, consistently and homogenously. The reality of daily work of a researcher involves different science domains, different roles, and heterogeneous information and data objects. Moreover, the scientific processes are subject to frequent changes and exceptions which require flexible compensations and many human interactions. Traditional BPM approaches such as "Peoplelinks", "Partnerlinks", 