Provenance and Annotation of Data and Processes
Transparently gathering provenance with provenance aware condor
TAPP'09 First workshop on on Theory and practice of provenance
Web enabling desktop workflow applications
Proceedings of the 4th Workshop on Workflows in Support of Large-Scale Science
Efficient querying of distributed provenance stores
Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing
The Foundations for Provenance on the Web
Foundations and Trends in Web Science
Middleware for managing provenance metadata
Middleware '10 Posters and Demos Track
PROPUB: towards a declarative approach for publishing customized, policy-aware provenance
SSDBM'11 Proceedings of the 23rd international conference on Scientific and statistical database management
A new approach for publishing workflows: abstractions, standards, and linked data
Proceedings of the 6th workshop on Workflows in support of large-scale science
Online workflow management and performance analysis with stampede
Proceedings of the 7th International Conference on Network and Services Management
SPADE: support for provenance auditing in distributed environments
Proceedings of the 13th International Middleware Conference
| Hi-index | 0.00 |
As scientific workflows and the data they operate on, grow in size and complexity, the task of defining how those workflows should execute (which resources to use, where the resources must be in readiness for processing etc.) becomes proportionally more difficult. While "workflow compilers", such as Pegasus, reduce this burden, a further problem arises: since specifying details of execution is now automatic, a workflow's results are harder to interpret, as they are partly due to specifics of execution. By automating steps between the experiment design and its results, we lose the connection between them, hindering interpretation of results. To reconnect the scientific data with the original experiment, we argue that scientists should have access to the full provenance of their data, including not only parameters, inputs and intermediary data, but also the abstract experiment, refined into a concrete execution by the "workflow compiler". In this paper, we describe preliminary work on adapting Pegasus to capture the process of workflow refinement in the PASOA provenance system.