Modern scientific data management and analysis usually rely on multiple scientists with diverse expertise. In recent years, such a collaborative effort is often structured and automated by a data flow-oriented process called scientific workflow. However, such workflows may have to be designed and revised among multiple scientists over a long time period. Existing workbenches are single user-oriented and do not support scientific workflow application development in a "collaborative fashion". In this paper, we report our research on the enabling techniques in the aspects of collaboration provenance management and reproduciability. Based on a scientific collaboration ontology, we propose a service-oriented collaboration model supported by a set of composable collaboration primitives and patterns. The collaboration protocols are then applied to support effective concurrency control in the process of collaborative workflow composition. We also report the design and development of Confucius, a service-oriented collaborative scientific workflow composition tool that extends an open-source, single-user development environment.

Large-scale scientific data management and analysis usually relies on many distributed scientists with diverse expertise. In recent years, such a collaborative effort is often composed and automated into a dataflow-oriented process, a so-called scientific workflow. However, existing scientific workflow tools are single user-oriented and do not support collaborative scientific workflow composition, execution, and management among multiple distributed scientists. In this paper, we report our study of collaboration protocols towards building a tool supporting collaborative scientific workflow composition. Based on a scientific collaboration ontology, we propose a collaboration model supported by a set of collaboration primitives and patterns. The collaboration protocols are then applied to support effective concurrency control in the process of collaborative workflow composition.