Facilitate Cross-Repository Big Data Discovery and Reuse
| dc.contributor.author | Xie, Zhiwu | en |
| dc.date.accessioned | 2016-06-25T15:03:08Z | en |
| dc.date.available | 2016-06-25T15:03:08Z | en |
| dc.date.issued | 2013-03-13 | en |
| dc.description.abstract | Researchers have accumulated large amount of observational, experimental, and simulation data. Much effort has been made to collect, curate, preserve, and provide open access to them, but putting the data online is only the start. Coined by Jim Gray as the fourth paradigm, the data-intensive science strives to uncover the hidden patterns and correlations across research topics and disciplines by aggregating and cross-interrogating these data silos. The productivity for e-Research may be much improved if we can provide the researchers with fast, easy, and cost-effective methods to discover and reuse these datasets in an ad-hoc and explorative manner. | en |
| dc.identifier.uri | http://hdl.handle.net/10919/71456 | en |
| dc.identifier.url | https://rdmi.uchicago.edu/page/experience-position-papers-1 | en |
| dc.language.iso | en_US | en |
| dc.publisher | Virginia Tech | en |
| dc.relation.ispartof | Research Data Management Implementations Workshop | en |
| dc.rights | Creative Commons Attribution 3.0 United States | en |
| dc.rights.uri | http://creativecommons.org/licenses/by/3.0/us/ | en |
| dc.subject | Research data management | en |
| dc.subject | Big data | en |
| dc.subject | Digital library | en |
| dc.subject | Institutional repository | en |
| dc.title | Facilitate Cross-Repository Big Data Discovery and Reuse | en |
| dc.type | Article | en |