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Suggested Citation:"Front Matter." National Research Council. 2015. Training Students to Extract Value from Big Data: Summary of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/18981.
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TRAINING STUDENTS TO EXTRACT VALUE FROM

BIG DATA

Summary of a Workshop

Maureen Mellody, Rapporteur

Committee on Applied and Theoretical Statistics

Board on Mathematical Sciences and Their Applications

Division on Engineering and Physical Sciences

NATIONAL RESEARCH COUNCIL
                               OF THE NATIONAL ACADEMIES

THE NATIONAL ACADEMIES PRESS

Washington, D.C.

www.nap.edu

Suggested Citation:"Front Matter." National Research Council. 2015. Training Students to Extract Value from Big Data: Summary of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/18981.
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THE NATIONAL ACADEMIES PRESS     500 Fifth Street, NW     Washington, DC 20001

NOTICE: The project that is the subject of this report was approved by the Governing Board of the National Research Council, whose members are drawn from the councils of the National Academy of Sciences, the National Academy of Engineering, and the Institute of Medicine.

This study was supported by Grant DMS-1332693 between the National Academy of Sciences and the National Science Foundation. Any opinions, findings, or conclusions expressed in this publication are those of the author and do not necessarily reflect the views of the organizations or agencies that provided support for the project.

International Standard Book Number-13: 978-0-309-31437-4
International Standard Book Number-10: 0-309-31437-2

This report is available in limited quantities from:

Board on Mathematical Sciences and Their Applications
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bmsa@nas.edu
http://www.nas.edu/bmsa

Additional copies of this workshop summary are available for sale from the National Academies Press, 500 Fifth Street, NW, Keck 360, Washington, DC 20001; (800) 624-6242 or (202) 334-3313; http://www.nap.edu/.

Copyright 2014 by the National Academy of Sciences. All rights reserved.

Printed in the United States of America

Suggested Citation:"Front Matter." National Research Council. 2015. Training Students to Extract Value from Big Data: Summary of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/18981.
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THE NATIONAL ACADEMIES

Advisers to the Nation on Science, Engineering, and Medicine

The National Academy of Sciences is a private, nonprofit, self-perpetuating society of distinguished scholars engaged in scientific and engineering research, dedicated to the furtherance of science and technology and to their use for the general welfare. Upon the authority of the charter granted to it by the Congress in 1863, the Academy has a mandate that requires it to advise the federal government on scientific and technical matters. Dr. Ralph J. Cicerone is president of the National Academy of Sciences.

The National Academy of Engineering was established in 1964, under the charter of the National Academy of Sciences, as a parallel organization of outstanding engineers. It is autonomous in its administration and in the selection of its members, sharing with the National Academy of Sciences the responsibility for advising the federal government. The National Academy of Engineering also sponsors engineering programs aimed at meeting national needs, encourages education and research, and recognizes the superior achievements of engineers. Dr. C. D. Mote, Jr., is president of the National Academy of Engineering.

The Institute of Medicine was established in 1970 by the National Academy of Sciences to secure the services of eminent members of appropriate professions in the examination of policy matters pertaining to the health of the public. The Institute acts under the responsibility given to the National Academy of Sciences by its congressional charter to be an adviser to the federal government and, upon its own initiative, to identify issues of medical care, research, and education. Dr. Victor J. Dzau is president of the Institute of Medicine.

The National Research Council was organized by the National Academy of Sciences in 1916 to associate the broad community of science and technology with the Academy’s purposes of furthering knowledge and advising the federal government. Functioning in accordance with general policies determined by the Academy, the Council has become the principal operating agency of both the National Academy of Sciences and the National Academy of Engineering in providing services to the government, the public, and the scientific and engineering communities. The Council is administered jointly by both Academies and the Institute of Medicine. Dr. Ralph J. Cicerone and Dr. C. D. Mote, Jr., are chair and vice chair, respectively, of the National Research Council.

www.national-academies.org

Suggested Citation:"Front Matter." National Research Council. 2015. Training Students to Extract Value from Big Data: Summary of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/18981.
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Suggested Citation:"Front Matter." National Research Council. 2015. Training Students to Extract Value from Big Data: Summary of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/18981.
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PLANNING COMMITTEE ON TRAINING STUDENTS TO EXTRACT VALUE FROM BIG DATA: A WORKSHOP

JOHN LAFFERTY, University of Chicago, Co-Chair

RAGHU RAMAKRISHNAN, Microsoft Corporation, Co-Chair

DEEPAK AGARWAL, LinkedIn Corporation

CORINNA CORTES, Google, Inc.

JEFF DOZIER, University of California, Santa Barbara

ANNA GILBERT, University of Michigan

PATRICK HANRAHAN, Stanford University

RAFAEL IRIZARRI, Harvard University

ROBERT KASS, Carnegie Mellon University

PRABHAKAR RAGHAVAN, Google, Inc.

NATHANIEL SCHENKER, Centers for Disease Control and Prevention

ION STOICA, University of California, Berkeley

Staff

NEAL GLASSMAN, Senior Program Officer

SCOTT T. WEIDMAN, Board Director

MICHELLE K. SCHWALBE, Program Officer

RODNEY N. HOWARD, Administrative Assistant

Suggested Citation:"Front Matter." National Research Council. 2015. Training Students to Extract Value from Big Data: Summary of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/18981.
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COMMITTEE ON APPLIED AND THEORETICAL STATISTICS

CONSTANTINE GATSONIS, Brown University, Chair

MONTSERRAT (MONTSE) FUENTES, North Carolina State University

ALFRED O. HERO III, University of Michigan

DAVID M. HIGDON, Los Alamos National Laboratory

IAIN JOHNSTONE, Stanford University

ROBERT KASS, Carnegie Mellon University

JOHN LAFFERTY, University of Chicago

XIHONG LIN, Harvard University

SHARON-LISE T. NORMAND, Harvard University

GIOVANNI PARMIGIANI, Harvard University

RAGHU RAMAKRISHNAN, Microsoft Corporation

ERNEST SEGLIE, Office of the Secretary of Defense (retired)

LANCE WALLER, Emory University

EUGENE WONG, University of California, Berkeley

Staff

MICHELLE K. SCHWALBE, Director

RODNEY N. HOWARD, Administrative Assistant

Suggested Citation:"Front Matter." National Research Council. 2015. Training Students to Extract Value from Big Data: Summary of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/18981.
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BOARD ON MATHEMATICAL SCIENCES AND THEIR APPLICATIONS

DONALD SAARI, University of California, Irvine, Chair

DOUGLAS N. ARNOLD, University of Minnesota

GERALD G. BROWN, Naval Postgraduate School

L. ANTHONY COX, JR., Cox Associates, Inc.

CONSTANTINE GATSONIS, Brown University

MARK L. GREEN, University of California, Los Angeles

DARRYLL HENDRICKS, UBS Investment Bank

BRYNA KRA, Northwestern University

ANDREW W. LO, Massachusetts Institute of Technology

DAVID MAIER, Portland State University

WILLIAM A. MASSEY, Princeton University

JUAN C. MESA, University of California, Merced

JOHN W. MORGAN, Stony Brook University

CLAUDIA NEUHAUSER, University of Minnesota

FRED S. ROBERTS, Rutgers University

CARL P. SIMON, University of Michigan

KATEPALLI SREENIVASAN, New York University

EVA TARDOS, Cornell University

Staff

SCOTT T. WEIDMAN, Board Director

NEAL GLASSMAN, Senior Program Officer

MICHELLE K. SCHWALBE, Program Officer

RODNEY N. HOWARD, Administrative Assistant

BETH DOLAN, Financial Associate

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Suggested Citation:"Front Matter." National Research Council. 2015. Training Students to Extract Value from Big Data: Summary of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/18981.
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Acknowledgment of Reviewers

This report has been reviewed in draft form by persons chosen for their diverse perspectives and technical expertise in accordance with procedures approved by the National Research Council’s Report Review Committee. The purpose of this independent review is to provide candid and critical comments that will assist the institution in making its published report as sound as possible and to ensure that the report meets institutional standards of objectivity, evidence, and responsiveness to the study charge. The review comments and draft manuscript remain confidential to protect the integrity of the deliberative process. We thank the following individuals for their review of this report:

Michael Franklin, University of California, Berkeley,

Johannes Gehrke, Cornell University,

Claudia Perlich, Dstillery, and

Duncan Temple Lang, University of California, Davis.

Although the reviewers listed above have provided many constructive comments and suggestions, they were not asked to endorse the views presented at the workshop, nor did they see the final draft of the workshop summary before its release. The review of this workshop summary was overseen by Anthony Tyson, University of California, Davis. Appointed by the National Research Council, he was responsible for making certain that an independent examination of the summary was carried out in accordance with institutional procedures and that all review comments were carefully considered. Responsibility for the final content of this summary rests entirely with the author and the institution.

Suggested Citation:"Front Matter." National Research Council. 2015. Training Students to Extract Value from Big Data: Summary of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/18981.
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As the availability of high-throughput data-collection technologies, such as information-sensing mobile devices, remote sensing, internet log records, and wireless sensor networks has grown, science, engineering, and business have rapidly transitioned from striving to develop information from scant data to a situation in which the challenge is now that the amount of information exceeds a human's ability to examine, let alone absorb, it. Data sets are increasingly complex, and this potentially increases the problems associated with such concerns as missing information and other quality concerns, data heterogeneity, and differing data formats.

The nation's ability to make use of data depends heavily on the availability of a workforce that is properly trained and ready to tackle high-need areas. Training students to be capable in exploiting big data requires experience with statistical analysis, machine learning, and computational infrastructure that permits the real problems associated with massive data to be revealed and, ultimately, addressed. Analysis of big data requires cross-disciplinary skills, including the ability to make modeling decisions while balancing trade-offs between optimization and approximation, all while being attentive to useful metrics and system robustness. To develop those skills in students, it is important to identify whom to teach, that is, the educational background, experience, and characteristics of a prospective data-science student; what to teach, that is, the technical and practical content that should be taught to the student; and how to teach, that is, the structure and organization of a data-science program.

Training Students to Extract Value from Big Data summarizes a workshop convened in April 2014 by the National Research Council's Committee on Applied and Theoretical Statistics to explore how best to train students to use big data. The workshop explored the need for training and curricula and coursework that should be included. One impetus for the workshop was the current fragmented view of what is meant by analysis of big data, data analytics, or data science. New graduate programs are introduced regularly, and they have their own notions of what is meant by those terms and, most important, of what students need to know to be proficient in data-intensive work. This report provides a variety of perspectives about those elements and about their integration into courses and curricula.

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