FRONTIERS IN
MASSIVE
DATA
ANALYSIS
Committee on the Analysis of Massive Data
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
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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. The members of the committee responsible for the report were chosen for their special competences and with regard for appropriate balance.
This project was supported by the National Security Agency under contract number NSA H98230-09-C-0407. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the views of the organizations or agencies that provided support for the project.
International Standard Book Number 13: 978-0-309-28778-4
International Standard Book Number 10: 0-309-28778-2
Library of Congress Control Number: 2013944743
Cover: Image courtesy of Jonathan Bachrach, University of California, Berkeley.
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Suggested citation: National Research Council. 2013. Frontiers in Massive Data Analysis. Washington, D.C.: The National Academies Press.
Copyright 2013 by the National Academy of Sciences. All rights reserved.
Printed in the United States of America
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.
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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.
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COMMITTEE ON THE ANALYSIS OF MASSIVE DATA
MICHAEL I. JORDAN, University of California, Berkeley, Chair
KATHLEEN M. CARLEY, Carnegie Mellon University
RONALD R. COIFMAN, Yale University
DANIEL J. CRICHTON, Jet Propulsion Laboratory
MICHAEL J. FRANKLIN, University of California, Berkeley
ANNA C. GILBERT, University of Michigan
ALEX G. GRAY, Georgia Institute of Technology
TREVOR J. HASTIE, Stanford University
PIOTR INDYK, Massachusetts Institute of Technology
THEODORE JOHNSON, AT&T Labs Research
DIANE LAMBERT, Google, Inc.
DAVID MADIGAN, Columbia University
MICHAEL W. MAHONEY, Stanford University
F. MILLER MALEY, Institute for Defense Analyses
CHRISTOPHER OLSTON, Google, Inc.
YORAM SINGER, Google, Inc.
ALEXANDER SANDOR SZALAY, Johns Hopkins University
TONG ZHANG, Rutgers, The State University of New Jersey
Staff
SUBHASH KUVELKER, Study Director (until October 17, 2011)
SCOTT WEIDMAN, Study Director (after October 17, 2011)
BARBARA WRIGHT, Administrative Assistant
COMMITTEE ON APPLIED AND THEORETICAL STATISTICS
CONSTANTINE GATSONIS, Brown University, Chair
MONTSERRAT FUENTES, North Carolina State University
ALFRED O. HERO III, University of Michigan
DAVID M. HIGDON, Los Alamos National Laboratory
IAIN JOHNSTONE, Stanford University
ROBERT E. KASS, Carnegie Mellon University
JOHN LAFFERTY, University of Chicago
XIHONG LIN, Harvard University
SHARON-LISE T. NORMAND, Harvard Medical School
GIOVANNI PARMIGIANI, Dana-Farber Cancer Institute
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 SCHWALBE, Director
BARBARA WRIGHT, Administrative Assistant
BOARD ON MATHEMATICAL SCIENCES AND THEIR APPLICATIONS
DONALD G. SAARI, University of California, Irvine, Chair
GERALD G. BROWN, U.S. Naval Postgraduate School
LOUIS ANTHONY COX, JR., Cox Associates, Inc.
BRENDA L. DIETRICH, IBM T.J. Watson Research Center
CONSTANTINE GATSONIS, Brown University
DARRYLL HENDRICKS, UBS Investment Bank
ANDREW W. LO, Massachusetts Institute of Technology
DAVID MAIER, Portland State University
JAMES C. McWILLIAMS, University of California, Los Angeles
JUAN MEZA, University of California, Merced
JOHN W. MORGAN, Stony Brook University
VIJAYAN N. NAIR, University of Michigan
CLAUDIA NEUHAUSER, University of Minnesota, Rochester
J. TINSLEY ODEN, University of Texas, Austin
FRED ROBERTS, Rutgers, The State University of New Jersey
J.B. SILVERS, Case Western Reserve University
CARL P. SIMON, University of Michigan
EVA TARDOS, Cornell University
KAREN L. VOGTMANN, Cornell University
BIN YU, University of California, Berkeley
Staff
SCOTT WEIDMAN, Director
NEAL GLASSMAN, Senior Program Officer
MICHELLE SCHWALBE, Program Officer
BARBARA WRIGHT, Administrative Assistant
BETH DOLAN, Financial Associate
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Acknowledgments
This report has been reviewed in draft form by individuals 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 for 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 wish to thank the following individuals for their review of this report:
Amy Braverman, Jet Propulsion Laboratory,
John Bruning, Corning Tropel Corporation (retired),
Jeffrey Hammerbacher, Cloudera,
Iain Johnstone, Stanford University,
Larry Lake, University of Texas,
Richard Sites, Google, Inc., and
Hal Stern, University of California, Irvine.
Although the reviewers listed above have provided many constructive comments and suggestions, they were not asked to endorse the conclusions or recommendations nor did they see the final draft of the report before its release. The review of this report was overseen by Michael Goodchild of the University of California, Santa Barbara. Appointed by the National Research Council, he was responsible for making certain that an indepen-
dent examination of this report was carried out in accordance with institutional procedures and that all review comments were carefully considered. Responsibility for the final content of this report rests entirely with the authoring committee and the institution.
The committee also acknowledges the valuable contribution of the following individuals, who provided input at the meetings on which this report is based or through other communications:
Léon Bottou, NEC Laboratories,
Jeffrey Dean, Google, Inc.,
John Gilbert, University of California, Santa Barbara,
Jeffrey Hammerbacher, Cloudera,
Patrick Hanrahan, Stanford University,
S. Muthu Muthukrishnan, Rutgers, The State University of New Jersey,
Ben Shneiderman, University of Maryland,
Michael Stonebraker, Massachusetts Institute of Technology, and
J. Anthony Tyson, University of California, Davis.
Contents
What Has Changed in Recent Years?
Where Are Massive Data Appearing?
Challenges to the Analysis of Massive Data
Trends in Massive Data Analysis
3 SCALING THE INFRASTRUCTURE FOR DATA MANAGEMENT
Scaling the Number of Data Sets
Scaling Computing Technology through Distributed and Parallel Systems
4 TEMPORAL DATA AND REAL-TIME ALGORITHMS
Data Processing, Representation, and Inference
System and Hardware for Temporal Data Sets
5 LARGE-SCALE DATA REPRESENTATIONS
Challenges and Future Directions
6 RESOURCES, TRADE-OFFS, AND LIMITATIONS
Relevant Aspects of Theoretical Computer Science
7 BUILDING MODELS FROM MASSIVE DATA
Introduction to Statistical Models
Common Techniques of Statistical Sampling
Challenges When Sampling from Massive Data
Hybrid Human/Computer Data Analysis