TY - GEN
T1 - Provenance-enabled data exploration and visualization with vistrails
AU - Silva, Cláudio
AU - Freire, Juliana
AU - Santos, Emanuele
AU - Anderson, Erik
PY - 2010
Y1 - 2010
N2 - Scientists are now faced with an incredible volume of data to analyze. To explore and understand the data, they need to assemble complex workflows (pipelines) to manipulate the data and create insightful visual representations. Provenance is essential in this process. The provenance of a digital artifact contains information about the process and data used to derive the artifact. This information is essential to preserve the data, to determining the data's quality and authorship, as well as for reproducing and validating results-all important elements of the scientific process. In this survey, we aim to inform computational and visualization scientists, users and developers about different approaches to provenance management. Using the VisTrails system as a basis and real application scenarios, we will cover different approaches to acquiring and reusing provenance, including techniques that attendees can use to provenance-enable their own tools. We will also present a series operations and user interfaces that leverage provenance for tasks that go beyond reproducibility, such as aiding users in the process of pipeline design and refinement, in performing comparative analysis and visualization, supporting collaborative data exploration as well as the publication of documented, reproducible results.
AB - Scientists are now faced with an incredible volume of data to analyze. To explore and understand the data, they need to assemble complex workflows (pipelines) to manipulate the data and create insightful visual representations. Provenance is essential in this process. The provenance of a digital artifact contains information about the process and data used to derive the artifact. This information is essential to preserve the data, to determining the data's quality and authorship, as well as for reproducing and validating results-all important elements of the scientific process. In this survey, we aim to inform computational and visualization scientists, users and developers about different approaches to provenance management. Using the VisTrails system as a basis and real application scenarios, we will cover different approaches to acquiring and reusing provenance, including techniques that attendees can use to provenance-enable their own tools. We will also present a series operations and user interfaces that leverage provenance for tasks that go beyond reproducibility, such as aiding users in the process of pipeline design and refinement, in performing comparative analysis and visualization, supporting collaborative data exploration as well as the publication of documented, reproducible results.
KW - comparative visualization
KW - data exploration
KW - provenance
KW - visualization systems
UR - http://www.scopus.com/inward/record.url?scp=79957823911&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79957823911&partnerID=8YFLogxK
U2 - 10.1109/SIBGRAPI-T.2010.9
DO - 10.1109/SIBGRAPI-T.2010.9
M3 - Conference contribution
AN - SCOPUS:79957823911
SN - 9780769542331
T3 - Proceedings - 23rd Conference on Graphics, Patterns and Images Tutorials, SIBGRAPI-T 2010
SP - 1
EP - 9
BT - Proceedings - 23rd Conference on Graphics, Patterns and Images Tutorials, SIBGRAPI-T 2010
T2 - 23rd Conference on Graphics, Patterns and Images Tutorials, SIBGRAPI-T 2010
Y2 - 30 August 2010 through 3 September 2010
ER -