PubFlow: Publication Workflows for Scientific Data - From acquisition and processing toward archival and publication
PubFlow invents new approaches and a pilot application to work with scientific data in scientific workflows to increase the productivity in scientific work. PubFlow provides a data publication framework for scientific data, build on top of proven business workflow technologies such as BPEL and BPMN. It brings automation and role-based working models to the domain of scientific data management. In PubFlow, data managers create data-management workflows with a graphical, domain-specific modeling language and scientists execute these workflows to automatically upload their data to the repositories. Besides providing workflow support, PubFlow also serves as a data-integration framework among heterogeneous systems. PubFlow automatically collects provenance information during data processing and stores it in an integrated, W3C Prov-O compliant, archive. In the first project phase, PubFlow is applied to the domain of marine sciences, which we intend to extend to the life sciences in a second phase.
The project is managed by Prof. Dr. Wilhelm Hasselbring and funded by the DFG, Scientific Library Services and Information Systems (LIS) (Geschäftszeichen HA 2038/3-1).