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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2018. Methods to Foster Transparency and Reproducibility of Federal Statistics: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/25305.
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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2018. Methods to Foster Transparency and Reproducibility of Federal Statistics: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/25305.
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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2018. Methods to Foster Transparency and Reproducibility of Federal Statistics: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/25305.
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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2018. Methods to Foster Transparency and Reproducibility of Federal Statistics: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/25305.
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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2018. Methods to Foster Transparency and Reproducibility of Federal Statistics: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/25305.
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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2018. Methods to Foster Transparency and Reproducibility of Federal Statistics: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/25305.
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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2018. Methods to Foster Transparency and Reproducibility of Federal Statistics: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/25305.
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Page viii Cite
Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2018. Methods to Foster Transparency and Reproducibility of Federal Statistics: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/25305.
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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2018. Methods to Foster Transparency and Reproducibility of Federal Statistics: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/25305.
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Prepublication Copy  Uncorrected Proofs Methods to Foster Transparency and Reproducibility of Federal Statistics PROCEEDINGS OF A WORKSHOP Michael L. Cohen, Rapporteur Committee on National Statistics Division on Behavioral and Social Sciences and Education

PREPUBLICATION COPY, UNCORRECTED PROOFS  THE NATIONAL ACADEMIES PRESS 500 Fifth Street, NW, Washington, DC 20001 This activity was supported by contracts between the National Academy of Sciences and the National Science Foundation (#SES-1024012). This grant provides support for the work of the Committee on National Statistics from a consortium of federal agencies. Any opinions, findings, conclusions, or recommendations expressed in this publication do not necessarily reflect the views of any organization or agency that provided support for the project. International Standard Book Number-13: 978-0-309-XXXXX-X International Standard Book Number-10: 0-309-XXXXX-X Digital Object Identifier: https://doi.org/10.17226/25305 Additional copies of this publication 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 2018 by the National Academy of Sciences. All rights reserved. Printed in the United States of America Suggested citation: National Academies of Sciences, Engineering, and Medicine. 2018. Methods to Foster Transparency and Reproducibility of Federal Statistics: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: https://doi.org/10.17226/25305.

PREPUBLICATION COPY, UNCORRECTED PROOFS  The National Academy of Sciences was established in 1863 by an Act of Congress, signed by President Lincoln, as a private, nongovernmental institution to advise the nation on issues related to science and technology. Members are elected by their peers for outstanding contributions to research. Dr. Marcia McNutt is president. The National Academy of Engineering was established in 1964 under the charter of the National Academy of Sciences to bring the practices of engineering to advising the nation. Members are elected by their peers for extraordinary contributions to engineering. Dr. C. D. Mote, Jr., is president. The National Academy of Medicine (formerly the Institute of Medicine) was established in 1970 under the charter of the National Academy of Sciences to advise the nation on medical and health issues. Members are elected by their peers for distinguished contributions to medicine and health. Dr. Victor J. Dzau is president. The three Academies work together as the National Academies of Sciences, Engineering, and Medicine to provide independent, objective analysis and advice to the nation and conduct other activities to solve complex problems and inform public policy decisions. The National Academies also encourage education and research, recognize outstanding contributions to knowledge, and increase public understanding in matters of science, engineering, and medicine. Learn more about the National Academies of Sciences, Engineering, and Medicine at www.national-academies.org.

PREPUBLICATION COPY, UNCORRECTED PROOFS  Consensus Study Reports published by the National Academies of Sciences, Engineering, and Medicine document the evidence-based consensus on the study’s statement of task by an authoring committee of experts. Reports typically include findings, conclusions, and recommendations based on information gathered by the committee and the committee’s deliberations. Each report has been subjected to a rigorous and independent peer-review process and it represents the position of the National Academies on the statement of task. Proceedings published by the National Academies of Sciences, Engineering, and Medicine chronicle the presentations and discussions at a workshop, symposium, or other event convened by the National Academies. The statements and opinions contained in proceedings are those of the participants and are not endorsed by other participants, the planning committee, or the National Academies. For information about other products and activities of the National Academies, please visit www.nationalacademies.org/about/whatwedo.

PREPUBLICATION COPY, UNCORRECTED PROOFS  STEERING COMMITTEE ON TRANSPARENCY AND REPRODUCIBILITY IN FEDERAL STATISTICS WILLIAM EDDY (Chair), Department of Statistics, Carnegie Mellon University GEORGE ALTER, Inter-university Consortium for Political and Social Research JEREMY FREESE, Department of Sociology, Stanford University GRAHAM KALTON, Westat AUDRIS MOCKUS, University of Tennessee, Knoxville SUSAN OFFUTT, U.S. Government Accountability Office (retired) MICHAEL L. COHEN, Study Director MICHAEL SIRI, Program Associate v

PREPUBLICATION COPY, UNCORRECTED PROOFS  COMIITTEE ON NATIONAL STATISTICS ROBERT M. GROVES (Chair), Office of the Provost, Department of Mathematics and Statistics, and Department of Sociology, Georgetown University MARY ELLEN BOCK, Department of Statistics, Purdue University (emeritus) ANNE C. CASE, Woodrow Wilson School of Public and International Affairs, Princeton University MICHAEL CHERNEW, Department of Health Care Policy, Harvard Medical School JANET M. CURRIE, Woodrow Wilson School of Public and International Affairs, Princeton University DONALD A. DILLMAN, Social & Economic Sciences Research Center, Washington State University DIANA FARRELL, JPMorgan Chase Institute, Washington, DC DANIEL KIFER, Department of Computer Science and Engineering, The Pennsylvania State University THOMAS L. MESENBOURG, U.S. Census Bureau (retired) SARAH M. NUSSER, Office of the Vice President for Research, and Department of Statistics, Iowa State University COLM O’MUIRCHEARTAIGH, Harris School of Public Policy, The University of Chicago JEROME P. REITER, Department of Statistical Science, Duke University JUDITH A. SELTZER, Department of Sociology, University of California, Los Angeles C. MATTHEW SNIPP, Department of Sociology, Stanford University BRIAN A. HARRIS-KOJETIN, Director CONSTANCE F. CITRO, Senior Scholar vi

PREPUBLICATION COPY, UNCORRECTED PROOFS  Acknowledgments We would first like to thank the National Science Foundation (NSF), particularly Amy Friedlander, deputy director, Office of Advanced Cyberinfrastructure, and her colleague, Patricia Knezek, senior advisor, Mathematical and Physical Sciences Directorate (until January 2018), for their support of this project, and for Amy Friedlander’s presentation, which kicked off the workshop. In addition, John Gawalt, director (until April 2018), NSF National Center for Science and Engineering Statistics, attended the workshop and provided helpful advice on the importance of this topic for the agencies in the federal statistical system. Most importantly, we want to thank the presenters, who prepared extremely useful presentations and were candid about current practices at their institutions: John Abowd (U.S. Census Bureau), David Barraclough (Organisation for Economic Co-operation and Development), Wesley Basel (U.S. Census Bureau), Peter Brodie (UK Office for National Statistics), Michaela Denk (International Monetary Fund), John Eltinge (U.S. Census Bureau), Daniel Gillman (Bureau of Labor Statistics), Brian Harris-Kojetin (Committee on National Statistics), Sarah Henry (UK Office for National Statistics), H.V. Jagadish (University of Michigan), Ruth Ann Killion (U.S. Census Bureau), Tom Louis (Johns Hopkins University), Jennifer Madans (National Center for Health Statistics), Peter Miller (U.S. Census Bureau), Juan Munoz Lopez (Instituto Nacional de Estadística y Geografía), Eric Rancourt (Statistics Canada), Robert Sienkiewicz (U.S. Census Bureau), Sally Thompson (Bureau of Economic Analysis), and Lars Vilhuber (Cornell University). Finally, we are also indebted to John Eltinge (U.S. Census Bureau) for helpful comments on the structure of the workshop, and to Hermann Habermann, Nancy Kirkendall, and Michael Siri (Committee on National Statistics) for contributing to the planning meeting of the steering committee in October 2016 and workshop in June 2017. Furthermore, we thank Yvonne Wise, Eugenie Grohman, and Kirsten Sampson Snyder, staff members of the Division of Behavioral and Social Sciences and Education, for their efforts in editing, review, and report preparation. This Proceedings of a Workshop was reviewed in draft form by individuals chosen for their diverse perspectives and technical expertise. The purpose of this independent review is to provide candid and critical comments that will assist the National Academies of Sciences, vii

PREPUBLICATION COPY, UNCORRECTED PROOFS  Engineering, and Medicine in making each published proceedings as sound as possible and to ensure that it meets the institutional standards for quality, objectivity, evidence, and responsiveness to the charge. The review comments and draft manuscript remain confidential to protect the integrity of the process. We thank the following individuals for their review of this Proceedings: David Barraclough, Statistics and Data Directorate, Smart Data Practices and Solutions Division, Organisation for Economic Co-operation and Development, and Patrick J. Cantwell, Sampling/Estimation, U.S. Census Bureau. Although the reviewers listed above provided many constructive comments and suggestions, they were not asked to endorse the content of this proceedings, nor did they see the final draft before its release. The review of this proceedings was overseen by Colm O’Muircheartaigh, Harris School of Public Policy, The University of Chicago. He was responsible for making certain that an independent examination of this proceedings was carried out in accordance with standards of the National Academies and that all review comments were carefully considered. Responsibility for the final content rests entirely with the rapporteur and the National Academies. Michael L. Cohen, Study Director Steering Committee on Transparency and Reproducibility in Federal Statistics viii

PREPUBLICATION COPY, UNCORRECTED PROOFS  Contents 1 Introduction 2 Existing Guidance Related to Transparency 3 Benefits and Costs of Transparency: Views from Three Statistical Agencies 4 Benefits and Costs of Transparency: Views from the United Kingdom and Canada 5 Two U.S. Examples: SAIPE and LEHD 6 Operationalizing Transparency 7 Summarizing Day 1 8 Standards for Metadata and Work Processes 9 Possible Next Steps Appendixes A Workshop Agenda B List of Participants ix

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In 2014 the National Science Foundation (NSF) provided support to the National Academies of Sciences, Engineering, and Medicine for a series of Forums on Open Science in response to a government-wide directive to support increased public access to the results of research funded by the federal government. However, the breadth of the work resulting from the series precluded a focus on any specific topic or discussion about how to improve public access. Thus, the main goal of the Workshop on Transparency and Reproducibility in Federal Statistics was to develop some understanding of what principles and practices are, or would be, supportive of making federal statistics more understandable and reviewable, both by agency staff and the public. This publication summarizes the presentations and discussions from the workshop.

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