Collaborative scientific workflows supporting collaborative science

Abstract

Collaboration has become a dominant feature of modern science. Many scientific problems are beyond the realm of individual discipline or scientist to solve and hence require collaborative efforts. Meanwhile, today's science becomes increasingly more dataintensive, resulting in a rapid transition from computational science to e-Science (or digital science). Recently, scientific workflows have emerged for scientists to integrate distributed computations, datasets, and analysis tools to enable and accelerate scientific discovery. The convergence of the above two trends naturally leads to the concept of collaborative scientific workflows. This paper presents a disciplinary definition of this term, discusses the opportunities, requirements, and challenges of collaborative scientific workflows for the enablement of scientific collaboration, and concludes with our ongoing work in this direction.

Facilitating Asynchronous Collaboration in Scientific Workflow Composition Using Provenance

“…Among them, Scientific Workflow Management Systems (SWfMSs) [13,17,44,47] are designed to efficiently handle the specification, modification, execution, failure management, and monitoring of activities in a scientific workflow [28]. Many existing SWfMSs only allows a single researcher to work on a workflow, whereas complex scientific problems require scientists from various backgrounds to work collaboratively to address a scientific question [29]. Since many of the SWfMSs do not support collaboration, researchers must send the project files manually to each other if they need input from another researcher.…”

“…Consequently, we need a tool to manage all these workspaces and different versions of the same workflow. Having an integrated system in which researchers can asynchronously join the experiment from different locations and have a personal workspace makes it possible to do much more complex experiments [29].…”

“…In today's science, collaboration has become a norm. Many scientific problems are beyond the scope of individuals or a person to address that necessitating collaboration [19,29]. Many scientific investigations require collaboration between scientists from varying backgrounds.…”

“…Many scientific investigations require collaboration between scientists from varying backgrounds. While many current scientific research projects are collaborative in nature, the team members are often spread throughout the world [29]. In a collaborative workflow creation, different team members often conceptualize their ideas in the form of multiple scientific workflows and then share them in a shared infrastructure.…”

“…They automate the lifecycle process of a scientific workflow including composition, deployment, execution, and analysis [30]. Data experiments are becoming more sophisticated, dimensional, and large, and efficient data analysis is beyond the scope of a single researcher and necessitates collaboration with several academics from other fields [29,37]. There are many SWfMSs allowing researchers to conduct scientific experiments such as Workspace [44], Taverna [16], ProvDB [32], VisTrails [13], Pegasus [17], Kepler [5,30], Triana, Wings, Confucius [47,48] and Sedna.…”