<?xml version="1.0" encoding="UTF-8"?>
<reference anchor="I-D.mcbride-data-discovery-problem-statement" target="https://datatracker.ietf.org/doc/html/draft-mcbride-data-discovery-problem-statement-00">
   <front>
      <title>Data Discovery Problem Statement</title>
      <author initials="M." surname="McBride" fullname="Mike McBride">
         <organization>Futurewei</organization>
      </author>
      <author initials="D." surname="KUTSCHER" fullname="Dirk KUTSCHER">
         <organization>Emden University</organization>
      </author>
      <author initials="E." surname="Schooler" fullname="Eve Schooler">
         <organization>Intel</organization>
      </author>
      <author initials="C. J." surname="Bernardos" fullname="Carlos J. Bernardos">
         <organization>Universidad Carlos III de Madrid</organization>
      </author>
      <author initials="D." surname="Lopez" fullname="Diego Lopez">
         <organization>Telefonica I+D</organization>
      </author>
      <date month="July" day="10" year="2020" />
      <abstract>
	 <t>   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.

	 </t>
      </abstract>
   </front>
   <seriesInfo name="Internet-Draft" value="draft-mcbride-data-discovery-problem-statement-00" />
   
</reference>
