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  <title>FDA Collection:</title>
  <link rel="alternate" href="http://hdl.handle.net/2451/38184" />
  <subtitle />
  <id>http://hdl.handle.net/2451/38184</id>
  <updated>2026-04-03T23:06:37Z</updated>
  <dc:date>2026-04-03T23:06:37Z</dc:date>
  <entry>
    <title>ReproZip - reprounzip-vagrant images archive</title>
    <link rel="alternate" href="http://hdl.handle.net/2451/61728" />
    <author>
      <name>Various</name>
    </author>
    <id>http://hdl.handle.net/2451/61728</id>
    <updated>2021-03-15T19:29:06Z</updated>
    <published>2021-03-09T00:00:00Z</published>
    <summary type="text">Title: ReproZip - reprounzip-vagrant images archive
Authors: Various</summary>
    <dc:date>2021-03-09T00:00:00Z</dc:date>
  </entry>
  <entry>
    <title>Example ReproZip package -- Digit segmentation and recognition with scikit-learn and OpenCV</title>
    <link rel="alternate" href="http://hdl.handle.net/2451/60881" />
    <author>
      <name>Rampin, Remi</name>
    </author>
    <id>http://hdl.handle.net/2451/60881</id>
    <updated>2019-11-01T22:01:04Z</updated>
    <published>2016-01-01T00:00:00Z</published>
    <summary type="text">Title: Example ReproZip package -- Digit segmentation and recognition with scikit-learn and OpenCV
Authors: Rampin, Remi</summary>
    <dc:date>2016-01-01T00:00:00Z</dc:date>
  </entry>
  <entry>
    <title>Careers of Data Scientists: Report from 13 Academic Institutions</title>
    <link rel="alternate" href="http://hdl.handle.net/2451/60880" />
    <author>
      <name>Katz, Luba</name>
    </author>
    <id>http://hdl.handle.net/2451/60880</id>
    <updated>2019-10-31T21:21:05Z</updated>
    <published>2019-10-01T00:00:00Z</published>
    <summary type="text">Title: Careers of Data Scientists: Report from 13 Academic Institutions
Authors: Katz, Luba
Abstract: The goal of this study was to document professional duties, challenges, and aspirations of staff data scientists in academia. The study subjects were recommended by leaders of data science entities at dozens of US universities and by data scientists. Of the 72 candidates suggested, 46 met our inclusion criteria and 33 (72%) agreed to a telephone interview. The data presented in this report are based on 28 interviews.</summary>
    <dc:date>2019-10-01T00:00:00Z</dc:date>
  </entry>
  <entry>
    <title>Collaborating to Create a Culture of Data Stewardship</title>
    <link rel="alternate" href="http://hdl.handle.net/2451/38185" />
    <author>
      <name>Steeves, Vicky</name>
    </author>
    <author>
      <name>Read, Kevin B.</name>
    </author>
    <author>
      <name>Gordon, Andrew S.</name>
    </author>
    <id>http://hdl.handle.net/2451/38185</id>
    <updated>2017-02-28T22:10:48Z</updated>
    <published>2016-05-04T00:00:00Z</published>
    <summary type="text">Title: Collaborating to Create a Culture of Data Stewardship
Authors: Steeves, Vicky; Read, Kevin B.; Gordon, Andrew S.
Abstract: Our poster discusses the ways in which we collaborate across the institution to provide comprehensive data management services by identifying overlap, making connections between service offerings, and sharing knowledge and resources around data to enrich the overall mission and strategy of NYU libraries to serve its student and research communities.The new collaboration between NYU Data Services, NYUHSL and special projects like Databrary has served to break down existing institutional silos to provide better research and educational data services to NYU’s student and research communities. This collaboration has been essential for improving upon existing services, identifying new opportunities to support the data needs of institutional stakeholders, and providing increased levels of outreach. By fostering a better understanding of what data services are available across campuses through this ongoing collaboration, we are better able to identify and support our communities’ data needs.</summary>
    <dc:date>2016-05-04T00:00:00Z</dc:date>
  </entry>
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