Related papers: Research Traceability using Provenance Services fo…
We outline the approach being developed in the neuGRID project to use provenance management techniques for the purposes of capturing and preserving the provenance data that emerges in the specification and execution of workflows in…
Providing an appropriate level of accessibility to and tracking of data or process elements in large volumes of medical data, is an essential requirement in the Big Data era. Researchers require systems that provide traceability of…
In complex data analyses it is increasingly important to capture information about the usage of data sets in addition to their preservation over time to ensure reproducibility of results, to verify the work of others and to ensure…
This paper discusses the CRISTAL object lifecycle management system and its use in provenance data management and the traceability of system events. This software was initially used to capture the construction and calibration of the CMS…
With the increasingly digital nature of biomedical data and as the complexity of analyses in medical research increases, the need for accurate information capture, traceability and accessibility has become crucial to medical researchers in…
This paper presents the use of the CRISTAL software in the N4U project. CRISTAL was used to create a set of provenance aware analysis tools for the Neuroscience domain. This paper advocates that the approach taken in N4U to build the…
The transformations, analyses and interpretations of data in scientific workflows are vital for the repeatability and reliability of scientific workflows. This provenance of scientific workflows has been effectively carried out in Grid…
Conducting experiments and documenting results is daily business of scientists. Good and traceable documentation enables other scientists to confirm procedures and results for increased credibility. Documentation and scientific conduct are…
This paper presents the CRISTAL-iSE project as a framework for the management of provenance information in industry. The project itself is a research collaboration between academia and industry. A key factor in the project is the use of a…
Provenance has been thought of a mechanism to verify a workflow and to provide workflow reproducibility. This provenance of scientific workflows has been effectively carried out in Grid based scientific workflow systems. However, recent…
By abstracting Grid middleware specific considerations from clinical research applications, re-usable services should be developed that will provide generic functionality aimed specifically at medical applications. In the scope of the…
Evolving user requirements presents a considerable software engineering challenge, all the more so in an environment where data will be stored for a very long time, and must remain usable as the system specification evolves around it.…
The emergence of Cloud computing provides a new computing paradigm for scientific workflow execution. It provides dynamic, on-demand and scalable resources that enable the processing of complex workflow-based experiments. With the ever…
As data-driven methods are becoming pervasive in a wide variety of disciplines, there is an urgent need to develop scalable and sustainable tools to simplify the process of data science, to make it easier to keep track of the analyses being…
We present the data model, design choices, and performance of ProvSQL, a general and easy-to-deploy provenance tracking and probabilistic database system implemented as a PostgreSQL extension. ProvSQL's data and query models closely reflect…
The volumes and complexity of data that companies need to handle are increasing at an accelerating rate. In order to compete effectively and ensure their commercial sustainability, it is becoming crucial for them to achieve robust…
We present here a provenance management system adapted to astronomical projects needs. We collected use cases from various astronomy projects and defined a data model in the ecosystem developed by the IVOA (International Virtual Observatory…
To benefit from the abundance of data and the insights it brings data processing pipelines are being used in many areas of research and development in both industry and academia. One approach to automating data processing pipelines is the…
Recording the provenance of scientific computation results is key to the support of traceability, reproducibility and quality assessment of data products. Several data models have been explored to address this need, providing…
Provenance is a record that describes how entities, activities, and agents have influenced a piece of data; it is commonly represented as graphs with relevant labels on both their nodes and edges. With the growing adoption of provenance in…