Scientists require provenance information either to validate their model or to investigate the origin of an unexpected value. However, they do not maintain any provenance information and even designing the processing workflow is rare in practice. Therefore, in this paper, we propose a solution that can build the workflow provenance graph by interpreting the scripts used for actual processing. Further, scientists can request fine-grained provenance information facilitating the inferred workflow provenance.We also provide a guideline to customize the workflow provenance graph based on user preferences. Our evaluation shows that the proposed approach is relevant and suitable for scientists to manage provenance
Workflow provenance typically assumes that each module is a “black-box”, so that each output depends...
The increasing data volume and highly complex models used in different domains make it difficult to ...
Data provenance allows scientists in different domains validating their models and algorithms to fin...
Scientists can facilitate data intensive applications to study and understand the behavior of a comp...
Integrated provenance support promises to be a chief advantage of scientific workflow systems over s...
Many scientists are using workflows to systematically design and run computational experiments. Once...
Scientific experiments are becoming increasingly large and complex, with a commensurate increase in ...
Abstract. We propose noWorkflow, a tool that transparently captures provenance of scripts and enable...
Scientific workflows have recently emerged as a new paradigm for representing and managing complex d...
The automated tracking and storage of provenance information promises to be a major advantage of sci...
The open provenance architecture approach to the challenge was distinct in several regards. In parti...
Data is an ever-expanding part of life in today’s world. Understanding the origin and the history of...
International audienceOften data processing is not implemented by a workflow system or an integratio...
Often data processing is not implemented by a workflow system or an integration application but is p...
Abstract. Often data processing is not implemented by a workflow sys-tem or an integration applicati...
Workflow provenance typically assumes that each module is a “black-box”, so that each output depends...
The increasing data volume and highly complex models used in different domains make it difficult to ...
Data provenance allows scientists in different domains validating their models and algorithms to fin...
Scientists can facilitate data intensive applications to study and understand the behavior of a comp...
Integrated provenance support promises to be a chief advantage of scientific workflow systems over s...
Many scientists are using workflows to systematically design and run computational experiments. Once...
Scientific experiments are becoming increasingly large and complex, with a commensurate increase in ...
Abstract. We propose noWorkflow, a tool that transparently captures provenance of scripts and enable...
Scientific workflows have recently emerged as a new paradigm for representing and managing complex d...
The automated tracking and storage of provenance information promises to be a major advantage of sci...
The open provenance architecture approach to the challenge was distinct in several regards. In parti...
Data is an ever-expanding part of life in today’s world. Understanding the origin and the history of...
International audienceOften data processing is not implemented by a workflow system or an integratio...
Often data processing is not implemented by a workflow system or an integration application but is p...
Abstract. Often data processing is not implemented by a workflow sys-tem or an integration applicati...
Workflow provenance typically assumes that each module is a “black-box”, so that each output depends...
The increasing data volume and highly complex models used in different domains make it difficult to ...
Data provenance allows scientists in different domains validating their models and algorithms to fin...