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| Content Provider | ACM Digital Library |
|---|---|
| Author | Willis, Craig McHenry, Kenton Lambert, Mike Kirkpatrick, Christine |
| Abstract | The growing size of high-value sensor-born or computationally derived scientific datasets are pushing the boundaries of traditional models of data access and discovery. Due to their size, these datasets are often accessible only through the systems on which they were created. Access for scientific exploration and reproducibility is limited to file transfer or by applying for access to the systems used to store or generate the original data, which is often infeasible. There is a growing trend toward providing access to large-scale research datasets in-place via container-based analysis environments. This paper describes the National Data Service (NDS) Labs Workbench platform and DataDNS initiative. The Labs Workbench platform is designed to provide scalable and low-barrier access to research data via container-based services. The DataDNS effort is a new initiative designed to enable discovery, access, and in-place analysis for large-scale data, providing a suite of interoperable services to enable researchers, as well as the tools they are most familiar with, to access and analyze these datasets where they reside. |
| Starting Page | 1 |
| Ending Page | 4 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781450352727 |
| DOI | 10.1145/3093338.3104164 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2017-07-09 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Research data Container-based analysis environments |
| Content Type | Text |
| Resource Type | Article |
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