Name
Abstract | ||
|---|---|---|
Reproducibility of scientific research relies on accurate and precise citation of data and the provenance of that data. Earth science data are often the result of applying complex data transformation and analysis workflows to vast quantities of data. Provenance information of data processing is used for a variety of purposes, including understanding the process and auditing as well as reproducibility. Certain provenance information is essential for producing scientifically equivalent data. Capturing and representing that provenance information and assigning identifiers suitable for precisely distinguishing data granules and datasets is needed for accurate comparisons. This paper discusses scientific equivalence and essential provenance for scientific reproducibility. We use the example of an operational earth science data processing system to illustrate the application of the technique of cascading digital signatures or “hash chains” to precisely identify sets of granules and as provenance equivalence identifiers to distinguish data made in an an equivalent manner. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1016/j.procs.2011.04.057 | Procedia Computer Science |
Keywords | Field | DocType |
provenance,equivalence,reproducibility,data identifiers,data citations | Data mining,Data processing,Information retrieval,Identifier,Computer science,Data processing system,Complex data type,Earth science,Equivalence (measure theory),Hash function,Workflow,Scientific method | Journal |
Volume | ISSN | Citations |
4 | 1877-0509 | 1 |
PageRank | References | Authors |
0.37 | 5 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Curt Tilmes | 1 | 91 | 13.91 |
| Ye. Yesha | 2 | 1 | 0.37 |
| M. Halem | 3 | 20 | 1.90 |