Data Discovery Problem Statement
draft-mcbride-data-discovery-problem-statement-00
| Document | Type | Expired Internet-Draft (individual) | |
|---|---|---|---|
| Authors | Mike McBride , Dirk Kutscher , Eve Schooler , Carlos J. Bernardos , Diego Lopez | ||
| Last updated | 2021-01-11 (Latest revision 2020-07-10) | ||
| Stream | (None) | ||
| Intended RFC status | (None) | ||
| Formats |
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| Stream | Stream state | (No stream defined) | |
| Consensus boilerplate | Unknown | ||
| RFC Editor Note | (None) | ||
| IESG | IESG state | Expired | |
| Telechat date | (None) | ||
| Responsible AD | (None) | ||
| Send notices to | (None) |
https://www.ietf.org/archive/id/draft-mcbride-data-discovery-problem-statement-00.txt
Abstract
If data is the new oil of the 21st century, then we need a standardized way of locating, capturing, classifying and transforming this raw data to generate insights and recommendations. Data, like oil, needs to be discovered and captured in order to be refined and valuable. While the topic of data discovery can be far reaching, this document focuses on the problem of actually locating data, throughout a network of data servers, in a standardized way.
Authors
Mike McBride
Dirk Kutscher
Eve Schooler
Carlos J. Bernardos
Diego Lopez
(Note: The e-mail addresses provided for the authors of this Internet-Draft may no longer be valid.)