Name
Abstract | ||
|---|---|---|
The adoption of large-scale distributed computing for high-energy physics presents new opportunities and challenges for physicists analyzing the data from the Large Hadron Collider experiments. With petabytes of data to manage, accessed by thousands of systems and used by thousands of collaborators, effective provenance is critical to the understanding of how the physics results were produced. In this article, the authors discuss several uses of data provenance in high-energy physics workflows and the opportunities for improvements in data analysis workflows that result from decentralized provenance collection and fine-grained object annotations. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/MCSE.2008.81 | Computing in Science and Engineering |
Keywords | Field | DocType |
fine-grained object annotation,high-energy physic,new opportunity,large hadron collider experiment,high-energy physics workflows,physics result,data provenance,data analysis workflows,decentralized provenance collection,effective provenance,data models,object oriented programming,metadata,distributed computing,large hadron collider,data analysis,production,high energy physics,distributed databases,physics | Data science,Large Hadron Collider,Metadata,Data modeling,Object-oriented programming,Petabyte,Computer science,Theoretical computer science,Distributed database,Compact Muon Solenoid,Workflow | Journal |
Volume | Issue | ISSN |
10 | 3 | 1521-9615 |
Citations | PageRank | References |
7 | 0.51 | 5 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Andrew Dolgert | 1 | 7 | 0.51 |
| l gibbons | 2 | 9 | 0.90 |
| c d jones | 3 | 9 | 0.90 |
| Valentin Kuznetsov | 4 | 14 | 1.79 |
| Mirek Riedewald | 5 | 1136 | 84.31 |
| Daniel Riley | 6 | 16 | 2.37 |
| g j sharp | 7 | 125 | 16.48 |
| Peter Wittich | 8 | 7 | 0.85 |