Collaborative Scientific Workflow Composition as a Service: An Infrastructure Supporting Collaborative Data Analytics Workflow Design and Management
2016 IEEE 2nd International Conference on Collaboration and Internet Computing (CIC) (2016)
Pittsburgh, Pennsylvania, United States
Nov. 1, 2016 to Nov. 3, 2016
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CIC.2016.039
The need for collaborative data analytics increases significantly when confronted with the challenges of big data. Although workflow tools offer a formal way to define, automate, and repeat multi-step computational procedures, designing complex data processing workflow requires collaboration from multiple people with complementary expertise. Existing tools are not suitable to support collaborative design of comprehensive workflows. To address such a challenge, this paper reports the design and development of a software infrastructure with the capability of supporting collaborative data-oriented workflow composition and management, adding a key component to existing cyberinfrastructure that will support big data collaboration through the Internet. A collaborative provenance query model (CPM) is presented together with graph-based patterns and algebra. A hypergraph theory-based provenance mining technique is reported. The research extends an existing open-source workflow tool, by adding system-level facilities to support human interaction and cooperation that are essential for an effective and efficient scientific collaboration.
Collaboration, Bridges, Data analysis, Data models, Big data, Business, Surface reconstruction
J. Zhang et al., "Collaborative Scientific Workflow Composition as a Service: An Infrastructure Supporting Collaborative Data Analytics Workflow Design and Management," 2016 IEEE 2nd International Conference on Collaboration and Internet Computing (CIC), Pittsburgh, Pennsylvania, United States, 2016, pp. 219-228.