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词条 Berkeley Institute for Data Science
释义

  1. Working groups

  2. Notable fellows

  3. References

  4. External links

{{Infobox organization
| image = Berkeley_Institute_for_Data_Science_-_Logo.png
| name = Berkeley Institute for Data Science
| website = {{URL|http://bids.berkeley.edu}}
| parent_organization = University of California, Berkeley
| leader_title = Faculty Director
| leader_name = Saul Perlmutter
| leader_title2 = Executive Director
| leader_name2 = David Mongeau
| established = November 2013
}}

The Berkeley Institute for Data Science (BIDS) is a central hub of research and education within UC Berkeley designed to facilitate data-intensive science and earn grants to be disseminated within the sciences.[1][2] BIDS was initially funded by grants from the Gordon and Betty Moore Foundation and the Sloan Foundation as part of a three-year grant with data science institutes at New York University and the University of Washington.[3][4][5] The objective of the three-university initiative is to bring together domain experts from the natural and social sciences, along with methodological experts from computer science, statistics, and applied mathematics.[6] The organization has an executive director and a faculty director, Saul Perlmutter, who won the 2011 Nobel Prize in Physics.[7] The initiative was announced at a White House Office of Science and Technology Policy event to highlight and promote advances in data-driven scientific discovery, and is a core component of the National Science Foundation's strategic plan for building national capacity in data science.[8][9][10]

Working groups

There are six working groups that are common across the three universities included in the original Moore/Sloan grant. The working groups are intended to "address the major challenges facing advances in data-intensive research" and include Career Paths and Alternative Metrics, Reproducibility and Open Science, Education and Training, Ethnography and Evaluation, Software Tools and Environments, and Working Spaces and Culture. and while all three are separate aspects of one division, they were awarded different grant money.

Notable fellows

A primary objective of BIDS is to build a community of data science fellows and senior fellows across academic disciplines. The 23 current fellows constitute the majority of the onsite liveware at the Institute, which supports a number of notable initiatives (via Fellow support). The following list is a subset of notable fellows to date:

  • Nick Adams, fellow, principal investigator of the Deciding Force project[11][12]
  • Fernando Pérez, senior fellow, creator of Jupyter and IPython[13][14]
  • Dan Hammer, fellow, Presidential Innovation Fellow and former Chief Data Scientist at the World Resources Institute[15][16]
  • Kathryn Huff, fellow, author of Effective Computation in Physics[17][18]
  • Daniela Ushizima, fellow, DOE Early Career Research Award,[19] staff scientist at Lawrence Berkeley National Laboratory[20]
  • Stéfan Van Der Walt, computational fellow, author of scikit-image[21][22]
  • Laura Waller[23]

References

1. ^{{Cite news|url = http://www.fastcompany.com/3021614/fast-feed/white-house-to-universities-we-need-more-data-scientists|title = White House to Universities: We Need More Data Scientists|last = Ungerleider|first = Neal|date = 13 November 2013|work = Fast Company|access-date = 25 October 2015|via = }}
2. ^{{Cite book|title = Machine Learning Models and Algorithms for Big Data Classification: Thinking with Examples for Effective Learning|last = Suthaharan|first = Shan|publisher = Springer|year = 2015|isbn = 9781489976413|location = |pages = 10}}
3. ^{{Cite news|url = http://www.nyu.edu/about/news-publications/news/2013/11/12/nyu-part-of-five-year-initiative-to-harness-potential-of-data-scientists-big-data-with-support-from-moore-sloan-foundations.html|title = NYU Part of Initiative to Harness Potential of Data Scientists, Big Data with Support from Moore, Sloan Foundations|last = |first = |date = 12 November 2013|work = New York University|access-date = 26 October 2015|via = }}
4. ^{{Cite news|url = https://honingds.com/blog/uw-berkeley-nyu-collaborate-in-37-8m-data-science-initiative|title = UW, Berkeley, NYU collaborate in $37.8M data science initiative|last = |first = |date = 7 November 2013|work = University of Washington eScience Institute|access-date = 26 October 2015|via = }}{{dead link|date=July 2017 |bot=InternetArchiveBot |fix-attempted=yes }}
5. ^{{Cite journal|title = Data science: Industry allure|last = Baker|first = Monya|date = 8 April 2015|journal = Nature|volume = 520|issue = 7546|pages = 253–255|doi = 10.1038/nj7546-253a|pmid = }}
6. ^{{Cite web|url = https://www.icpsr.umich.edu/icpsrweb/content/DSDR/bigdata-examples.html|title = Examples of Big Data Initiatives and Funding Projects|date = 2015|accessdate = 26 October 2015|website = Data Sharing for Demographic Research|publisher = Eunice Kennedy Shriver National Institute of Child Health and Human Development|last = |first = }}
7. ^{{Cite web|url = https://www.youtube.com/watch?v=8f-11pyJ-cU|title = Launch of the Berkeley Institute for Data Science|date = 12 December 2013|accessdate = 5 November 2011|website = |publisher = CITRIS|last = |first = |type = YouTube|location = Berkeley, California}}
8. ^{{Cite news|url = http://bits.blogs.nytimes.com/2013/11/12/program-seeks-to-nurture-data-science-culture-at-universities/|title = Program Seeks to Nurture 'Data Science Culture' at Universities|last = Lohr|first = Steve|date = 12 November 2013|work = New York Times|access-date = 25 October 2015|via = }}
9. ^{{Cite web|url = https://www.whitehouse.gov/sites/default/files/microsites/ostp/Data2Action%20Announcements.pdf|title = Data to Knowledge to Action|date = 12 November 2013|accessdate = 25 October 2015|website = Fact Sheet|publisher = White House|last = |first = |archive-url = https://web.archive.org/web/20151021100327/https://www.whitehouse.gov/sites/default/files/microsites/ostp/Data2Action%20Announcements.pdf|archive-date = 2015-10-21|dead-url = yes|df = }}
10. ^{{Cite book|title = Final Report from StatSNSF subcommittee|last = Johnstone|first = Iain|publisher = National Science Foundation|isbn = |location = |pages = |access-date = 5 November 2015|url = https://www.nsf.gov/mps/members_only/presentations_0714/johnstone-roberts_statsnsf-to-post.pdf|last2 = Roberts|first2 = Fred|date = 18 July 2014}}
11. ^{{Cite news|url = http://www.heraldextra.com/news/local/north/saratoga-springs/deciding-force-what-we-learned-from-ferguson/article_8a9c8cc0-4ee1-5b20-97b5-8a244c371e6b.html|title = Deciding Force: What we learned from Ferguson|last = Allred|first = Cathy|date = 17 September 2014|work = Daily Herald|access-date = 5 November 2015|via = }}
12. ^{{Cite news|url = http://america.aljazeera.com/opinions/2015/9/decriminalize-dissent.html|title = Decriminalize dissent|last = McMillan|first = Cecily|date = 17 September 2015|work = Al Jazeera America|access-date = 6 November 2015|via = |last2 = Gould-Wartofsky|first2 = Michael}}
13. ^{{Cite news|url = http://www.businesswire.com/news/home/20150707006377/en/6M-UC-Berkeley-Cal-Poly-Expand-Enhance|title = $6M for UC Berkeley and Cal Poly to Expand and Enhance Open-Source Software for Scientific Computing and Data Science|last = |first = |date = 7 July 2015|work = Business Wire|access-date = 5 November 2015|via = }}
14. ^{{Cite news|url = http://www.infoworld.com/article/2610411/data-visualization/ipython-founder-details-road-map-for-interactive-computing-platform.html|title = IPython founder details road map for interactive computing platform|last = Krill|first = Paul|date = 14 February 2014|work = InfoWorld|access-date = 6 November 2015|via = }}
15. ^{{Cite journal|url = http://spectrum.ieee.org/energy/environment/google-earth-engine-brings-big-data-to-environmental-activism|title = Google Earth Engine Brings Big Data to Environmental Activism|last = Strickland|first = Eliza|date = 16 April 2014|journal = IEEE Spectrum|doi = |pmid = |access-date = 5 November 2015}}
16. ^{{Cite journal|url = http://sciencecareers.sciencemag.org/career_magazine/previous_issues/articles/2015_07_13/caredit.a1500176|title = Putting women at the controls at NASA|last = Benderly|first = Beryl|date = 13 July 2015|journal = Science|doi = |pmid = |access-date = 5 November 2015}}
17. ^{{Cite book|title = Effective Computation in Physics|last = Scopatz|first = Anthony|publisher = O'Reilly Media|year = 2015|isbn = 9781491901595|location = |pages = |url = https://books.google.com/books?id=DYoNCgAAQBAJ|last2 = Kathryn|first2 = Huff}}
18. ^{{Cite web|url = http://cds.nyu.edu/women-data-science-kathryn-huff/|title = Women in Data Science: Kathryn Huff|date = 14 September 2014|accessdate = 6 November 2015|website = Center for Data Science|publisher = New York University|last = Lowery|first = Jack}}
19. ^{{Cite news|url = https://science.energy.gov/early-career/|title = U.S. Department of Energy Early Career Research Program|access-date = 28 July 2017|via = }}
20. ^{{Cite news|url = https://insidehpc.com/2017/07/testing-brain-inspired-chips-big-data-problems-berkeley-lab/|title = Testing Brain-Inspired Chips for Big Data Problems|last = Vu|first = Linda|date = 10 July 2017|work = insidehpc.com|access-date = 28 July 2017|via = }}
21. ^{{Cite book|title = SciPy and NumPy: An Overview for Developers|last = Bressert|first = Eli|publisher = O'Reilly Media|year = 2012|isbn = 9781449361624|location = |pages = 43}}
22. ^{{Cite web|url = https://pypi.python.org/pypi/scikit-image|title = scikit-image|date = |accessdate = 5 November 2015|website = |publisher = Python Package Index|last = |first = }}
23. ^{{cite web|url=https://bids.berkeley.edu/people/laura-waller|title=Laura Waller|website=Berkeley Institute for Data Science}}

External links

  • Official website

2 : University of California, Berkeley|2013 establishments in California
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