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OCR for page 39
Sharing Research Data
in the Social Sciences
Jerome M. Clubb, Enk W. Austin,
Carolyn L. Geda, and Michael W. Traugott
Dunng the past two decades an extensive literature has appeared exploring
issues related to access to basic computer-readable data for empirical social
science research. In the main, the authors of this literature emphasize the
scientific, public policy, and pedagogical values and advantages of data shar-
~ng, and they often advocate a policy of open access to data in maximally us-
able form. Obstacles to data sharing are discussed, specific categories of data
are noted as exceptions to the general sharing Nile, arguments against com-
plete open access to research data are sometimes offered, and the precise na-
ture of obligations to share data are debated, but few if any of the authors cate-
Jerome M. Clubb, Erik W. Austin, Carolyn L. Geda, and Michael W. Traugott are at the
Inter-university Consortium for Political and Social Research, Center for Political Studies,
Institute for Social Research, University of Michigan.
An earlier draft of this paper was discussed at length by Stephen Fienberg, Clifford Hildreth,
Margaret Martin, Miron Straf, Joe Cecil, and Terry Hedrick. Although we were unable to meet
all of their many comments and suggestions, this paper has benefitted greatly from their efforts.
We alone, however, are responsible for its shortcomings.
39
OCR for page 40
40
Jerome M. Clubb et al.
goncally oppose data sharing or some form of open access.
These same two decades have been marked by movement among social
scientists toward implementation of the general principle of open access to ba-
sic research data. Institutional mechanisms have appeared to facilitate access
to data, and venous agencies that fund research in the social sciences have
stressed that the resultant data collections should be made available to other
researchers. One consequence of these developments is that abundant, if
somewhat unsystematic, concrete evidence of the value of open access to ba-
sic research data is now available.
At the same time, however, discussion and disagreement continue, and ac-
ceptance and implementation of the general principle of data sharing are far
from complete. Social scientists are still often refused access to data, or if ac-
cess is granted, copies of data are sometimes received in technically unusable
form. In some cases data are shared, but only after prolonged delay. In oth-
er cases data are shared only within relatively limited networks of researchers,
often within a single discipline or subdiscipline. Access to data by people
outside such networks is either difficult or precluded. Difficulties in gaining
access to data are not simply the product of unwillingness of researchers and
research groups to share, but also result because mechanisms to provide infor-
mation about the availability of data, and particularly mechanisms that oper-
ate across disciplinary boundaries, are not yet well developed. It is only in
very recent years, for example, that concerted efforts to develop bibliographic
control over computer-readable data collections have begun, and there is as
yet no centralized reference service for computer-readable social science data.
Failure to move more rapidly toward acceptance and implementation of the
principle of open access to basic data is sometimes asserted to be a reflection
of the supposed transitional nature of the social sciences—from essentially lit-
erary values, with their emphasis upon private and unique individual creativi-
ty, to the scientific values of public and cooperative pursuit of cumulative
knowledge. In our view such an explanation is neither particularly useful nor
accurate. If it were accurate, other areas of inquiry would also have to be
seen as transitional in nature, since difficulties and disagreements concerning
access to data and to data collection facilities are also encountered in other
sciences. In our reading much more obvious and, in some respects, more
useful explanations are also available. First, there are serious concrete tech-
nical obstacles to effective data sharing, although at least some of them could
be readily overcome. Second, there are reasonable arguments against a gen-
eralized norm of data shanug and against complete open access to research da-
ta, arguments that reflect conflicting values and goals as well as the reward
structure characteristic of science. These issues constitute the most serious
obstacles to data sharing.
In this paper we examine the issues confronted in sharing basic social
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Sharing Data in the Social Sciences
41
science data. The initial section summarizes scientific and other values and
advantages gained through open access to data. The second section provides
an indication of the magnitude of data sharing that now occurs. The third sec-
tion considers technical obstacles to generalized access to basic data in usable
form and suggests means by which some of these obstacles might be over-
come. The fourth section considers further arguments against data sharing
and the conflicting values, goals, and obligations that seem open to underlie
disagreement and discussions of data sharing; for these, solutions that go sig-
nif~cantly beyond continued exhortation are less easily identified. The fifth
section considers modes and facilities for data sharing, and the sixth section
briefly considers practices of data sharing in several other areas of inquiry.
We offer conclusions and recommendations in the final section.
This paper has a number of limitations that should be made explicit.
Data-sharing practices vary rather widely in the social sciences, and it is un-
likely that the full range of this variation has been adequately taken into ac-
count. While data-sharing practices in several rather specific areas of the na-
tural and biomedical sciences are examined, this examination is somewhat un-
systematic and far less than complete. To explore in anything approaching
comprehensive fashion questions of data sharing and access to data collection
facilities in the many and diverse areas of the other sciences would be a major
research undertaking in its own right. Thus we are able to offer here only a
few highly tentative generalizations.
There are a very large number of organizations and facilities in the academ-
ic, government, and private sectors that function in some way to share and
provide access to computer-readable data relevant to social science research.
Our discussion of these facilities is most complete for academically based or-
ganizations; it is significantly less complete in the case of organizations in The
public and private sectors. Our discussion of data-sharing practices and facil-
ities is also heavily based on the United States; practices, facilities, and ex-
periences in other nations are less to computer-readable data collected and
processed more or less specifically to serve the goals of social science re-
search and the purposes of monitoring social processes. We distinguish be-
tween computer-readable data for research and computer-readable
information of the sort found in data bases containing bibliographic citations
and abstracts of published textual material. The latter are shared through
many mechanisms and are outside the scope of this paper. There are similar
questions regarding access to other categories of research source material,
such as oral histories, and it is likely that somewhat similar principles and im-
peratives would apply to these other categories of source material as apply to
computer-readable data for social science research. The personal papers of
statesmen, political, government, and other public figures constitute primary
source materials for the research of historians and other social scientists as
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Jerome M. Clubb et al.
well as of scholars of literature and the arts, and access to such materials is of-
ten restricted and is at best uneven. However, the issues confronted in deal-
ing with such materials are complex, controversial, and widely debated, and
we have been forced to rule them outside the scope of the present paper.
The operational records of government agencies and other organizations are
also not considered in this paper. These records constitute research resources
of very considerable value for investigation of social processes, and they are
also of central importance for purposes of policy and performance evaluation
and public accountability. Such records, moreover, are increasingly main-
tained in computer-readable form so that transactions and activities are docu-
mented in greater detail than formerly, and the records can also be manipu-
lated for analytic purposes. However, these records fall within the purview
of governmental, business, and other organizational archives that are today
largely ill-equipped to manage them in their computer-readable form or to
make them available for scientific use. A recent collection of essays (Geda et
al., 1980) provides a useful summary of the issues and problems presented by
these materials and calls attention to the risk of loss of major research oppor-
tunities. These issues and problems are not reviewed in the present paper.
VALUES AND ADVANTAGES OF DATA SHARING
Beginning in the early 1960s, numerous books and articles have appeared that
discussed the values and advantages to be gained through open access to basic
social scientific data and that explore means for providing this access. Much
of the early literature emphasized the impact of change in the technology of
social science research. It was recognized that the social sciences were un-
dergoing the introduction of complex technologies analogous in some ways to
the costly instrumentation of the natural sciences. The consequences of this
new technology were seen as providing abundant research opportunities, but
these opportunities were also seen as accompanied by need for change in work
practices and uneven access among social scientists to research resources and
as interposing new obstacles to effective research.
The advent of computer technology and its application to social science re-
search meant Hat researchers had the capacity to manipulate large data collec-
tions and to use complex methods of analysis in ways Hat previously had been
virtually precluded. At the same time, however, researchers faced high costs
for data collection arid for processing data to computer-readable form, uneven
access to computational facilities and capabilities among social scientists, and
the possibility and value of multiple uses of data collections. Hence the early
literature emphasized need for mechanisms that would facilitate generalized
access to data and to computational capabilities required for their use.
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Sharing Data in the Social Sciences
43
It also became increasingly clear that standard publishing mechanisms of-
fered few effective solutions to the problems of access to research data: the
size of research data collections, and the attendant high costs of publishing ba-
sic data, precluded this option. Furthermore, publication of scientific re-
search data that already exist in computer-readable form was seen to add an
unnecessary and expensive loop to the process of data sharing: to be used ef-
fectively in research applications, such published data must be reconverted to
computer-readable form by each and every analyst who wishes to use them in
research. Finally, in more recent years numerous observers have noted that
the publishing of research results falls far short of satisfying goals represented
by the term "data sharing." Few if any professional journals or monographs
permit or encourage the depth of exposition of research data and methods that
underlie reported research findings; it is therefore rarely the case that pu-
blished research reports satisfy a reader seeking to evaluate the basic data and
techniques used in a research investigation.
Increased use of sample surveys as a primary mode of data collection con-
stituted a furler impetus to data sharing. By the 1960s, numerous collec-
tions of sample survey data existed, some of them dating to the mid-1930s,
and the survey method of data collection had attained highly sophisticated
form. It was clear, however, that mounting a large-scale sample survey was
beyond the financial reach of most social scientists and, consequently, many
researchers were increasingly disadvantaged. Again, the possibility of multi-
ple research applications and the cumulative values of data from well-
designed sample surveys was stressed.
To realize new research opportunities and to capitalize on new technology
required creation of new data facilities. These facilities were viewed, in
some cases, as functioning analogously to the laboratories and the research in-
stallations of the physical sciences. They would provide mechanisms to
implement the obligations of original data collectors to share their data with
other researchers. They would devise and implement standards for data col-
lection and processing, contribute to the development of general-purpose
computational capabilities, and provide training in new approaches to social
science research.
Some of these same themes continue to underlie much of the literature since
the 1960s. (A partial list of the earlier and subsequent literature is provided in
the references and bibliography section.) Like the earlier literature, subse-
quent contributions to this general discussion explore a variety of more specif-
ic advantages and values of generalized access to basic computer-readable so-
cial scientific data. In view of this large body of literature, we need only
briefly summarize those values and advantages here.
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Jerome M. Clubb et al.
Replication and Verification
Improved capacity to verify and replicate reported research findings is among
the most commonly discussed advantage of generalized access to data.
Obviously, use of computers and computer-readable data and increased use of
large bodies of data that are costly to collect increase the complexity of venfi-
cation and replication as compared with more traditional data sources and re-
search methods. The costs of a major survey are large, and repetition of the
survey for purposes of replication and verification of an original effort is
usually precluded. Thus replication and verification can often be accom-
plished only through access to the data from the original survey. In addition,
many of the phenomena studied by social scientists are in some senses nonre-
curnng. National elections are, of course, repetitive, but the specific con-
texts and characteristics of elections van. As a consequence, findings based
on data collected for one election often cannot be verified and replicated with
data collected for a subsequent election. Hence, the values of verification
and replication can often be served by access to the original data.
The need for simple verification of research findings is frequently mini-
rnized since fraudulent research reports are thought to be rare. The risks of
datacollection or analysis errors are greater, and erroneous findings due to
such errors are probably more common. However, there are also occasional
reports of fraudulent research, some of them with continuing and even dire
consequences. For these reasons the opportunity for verification using ori-
ginal data is often seen as a vital element of the research process and as dictat-
ing generalized access to data.
Access to basic data is often seen as facilitating three somewhat different
forms of replication of reported findings. One of these might be described as
"exact" replication. In this case the same data and methods are used to deter-
mine whether He same results are obtained. The second form replicates and
tests reported findings using the same data but different analytic methods or
assumptions. Both of these are obviously forms of verification and are some-
times seen as particularly important when data and research bear directly on
current social policy concerns. The third form of replication looks toward
testing the generality of reported findings. In tills case data from different
contexts national or temporal, for example are used to discover the condi-
tions under which particular relations do or do not apply and, hence, to gener-
alize research hmdings.
Methodological Improvement
Further values served by open access to basic data are improvement of mea-
surement and data collection methods. In this view, the obligation to share
data with other researchers subjects data and data collection methods metho-
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Sharing Data in the Social Sciences
45
dological improvement is encouraged. In somewhat similar fashion, the
availability of extended collections of data is seen as holding benefits for the
design of new data collection efforts: in opportunities for exploratory research
to determine in differing contexts the adequacy of question wordings, unob-
trusive scales, and indicators, leading to improved measures and measure-
ment validation.
Secondary Analysis
The value of data collections for extended, or secondary, analysis is, of
course, frequently discussed. The research potential of a welldesigned data
collection is rarely exhausted by the original data collector, and data collec-
tions usually have value beyond those for which they were originally de-
signed. Thus data collections generally have multiple research applications.
Moreover, the availability of extended collections of data provide a basis for
realization of further values: in the possibilities of combining data, derived
measures, or analytic results from diverse collections in order to address new
research questions and in the comparative and longitudinal perspectives pro-
vided by the availability of data collected at different times and in different
places. Realization of the latter values, it should be noted, not only dictates
that data be shared, but also that data be preserved and remain accessible for
extended periods of time.
Further values of data sharing for research are economic in nature and fol-
low from opportunities for secondary analysis. Generalized use of data is be-
lieved to reduce research costs. The ready availability of data means that re-
searchers often do not need to collect data de novo but can pursue research
interests and goals by drawing on existing data. In this way, duplication of
data collection efforts and investments are reduced, and the research value of
investments in data collection are more fully realized. Opportunities to carry
out meaningful research are, in effect, democratized, and more social scien-
tists are able to conduct research and contribute to the development of
knowledge. ~
Generalized access to basic research data in readily usable form is also seen
as serving a variety of additional values, including pedagogical ones.
Original data are now frequently used in both substantive and methodological
instruction at the graduate and undergraduate levels as well as, occasionally,
at the secondary school level. Probably the best-known and most widely
used examples of instructional applications of this sort are the SETUPS
(Supplementary Empirical Teaching Units for Political Science) series deve-
loped collaboratively by We American Political Science Association and the
Inter-university Consortium for Political and Social Research.
Twenty-one of these units have been prepared and more are now being
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Jerome M. Clubb et al.
developed or are planned. Each unit includes a brief monograph that poses a
substantive or methodological problem or set of problems and a specially tai-
lored data file to address that problem. By using original data in this fashion,
students are able to more directly experience the research process and come to
better understand the empirical bases and the contingent nature of research
findings. In a more general sense, instructional use of empirical data im-
proves social scientific and numeric literacy and enhances students' critical
capacity to evaluate the results of applications of social science methods,
whether reported in scholarly publications or in the mass media.
Ready access to data is also seen as holding values for public policy pur-
poses. The availability of data facilitates and encourages use of empirical
data in policy formation and evaluation and so improves policy. Ready ac-
cess to data also means, in this view, a capacity to more rapidly address policy
questions.
Numerous illustrations of the values summarized above could be cited.
Three somewhat diverse illustrations are touched upon here. One example is
provided through research by James S. Coleman and his colleagues ( 1966) on
the equality of educational opportunity. The second is taken from a quite
different area of inquiry: research into the economic history of the antebellum
Soup and the economics of slavery, carried out by Robert W. Fogel and
Stanley L. Engerman and reported in Time on the Cross (1974~. In bow
cases, the reported research engendered widespread debate and controversy,
sometimes acrimonious, among both scholars involved in the areas of inquiry
and others. However, because the original data on which the research was
based were generally available, scholarly debate could often be conducted on
empirical rather than purely speculative grounds.2 The underlying data could
be explored and evaluated and the findings empirically tested and contested.
The consequence in both cases was ~at, despite controversy, debate was of a
higher order and more effectively conducted; weaknesses of original data col-
lection and research were better identified, and new and potentially rewarding
areas for furler research found.
A third illustration is of a still different order and is provided by the
American National Election Studies, which are directed by Warren E. Miller.
These surveys have been conducted by He Survey Research Center and the
Center for Political Studies of the Institute for Social Research (located at the
University of Michigan) for each national election since 1952. Data from the
surveys provide an incomparable resource for cross-sectional and longitudinal
investigation of the formation and durability of political attitudes and of
American political processes. In more recent years, moreover, similar
studies stimulated in part by these studies—have been conducted in many
other nations, including Australia, Austria, Canada, Denmark, Finland,
France, Israel, Italy, Japan, the Netherlands, Norway, Spain, Sweden, He
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Sharing Data in the Social Sciences
47
United Kingdom, and West Germany. In some of these nations, their series
now span well over two decades. The venous studies show marked similarity
in theoretical foci, in the structure of questions and measures, and in other de-
sign characteristics. Thus, taken collectively, the data from these surveys
constitute a powerful resource for both longitudinal inquiry and cross-national
comparison, and they also exemplify the advantages, for purposes of design-
ing new data collection efforts, of general availability of data collections.
Distinctions and Reservations
While the values summarized above are recognized and stressed, discussions
of data sharing also draw distinctions, both explicitly and implicitly, between
different categories of data in terms of the importance of sharing and the obli-
gations of researchers to provide access. Data collections that threaten priva-
cy or place individuals or organizations "at risk" are usually seen as requiring
special treatment, although such concerns were less frequently expressed in
the earlier literature than they are now, and distinctions are also made in the
case of proprietary data collected for the purposes of private enterprise.
Issues of privacy and confidentiality and questions of proprietary data are dis-
cussed in a subsequent section; here we are concerned with distinctions that
center on such issues as the presumed intrinsic importance of data collections,
the purposes they were designed to serve, and He relative ease with which
particular categories of data collections can be replicated.
Distinctions are often drawn between large-scale data collections, particu-
larly sample survey data collected at public expense, and smaller bodies of
data collected at personal expense. There is widespread agreement that the
former category of data should be shared and made generally available in a
timely fashion, although there is less agreement as to what constitutes
"timely." Sharing smaller data collections, particularly those created at indi-
vidual expense, is often seen as less important, and obligations to provide ac-
cess to such data are considered less pressing. These distinctions seem to be
based on the presumed lesser value of smaller data collections for the purposes
of secondary analysis, the sources of financial support for data collection, and
the greater ease and lower cost at which smaller data collections can be dupli-
cated. A similar distinction is sometimes also made for data collected from
published or other public record sources. The presumption seems to be that
because the original data can be found in published or otherwise publicly
available sources, they can also be collected and processed by the secondary
user; consequently, sharing is less obligatory or useful.
Further and more specific distinctions are also sometimes made in terms of
the purposes data collections are intended to serve and their potential for af-
fecting government, public affairs, and human life. Hedrick et al. (1978)
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Jerome M. Clubb et al.
suggest, for example, the importance of general and immediate access to data
collected for purposes of formulating and evaluating public policy. And their
views might be extended to include other categories of data for applied social
science research. Such data are designed to provide a basis for social pro-
grarn and policy decisions, and their potential for directly affecting people's
lives is great. Thus in this view there is greater need for rapid evaluation of
data and for replication of analytic findings than in the case of data designed to
serve the purposes of more basic social science research.
Distinctions such as these may be useful and even necessary in pragmatic
terms. Obviously, it would not be realistic to envision sharing and open ac-
cess to all data collected by social scientists. However, distinctions of this
sort may be difficult to implement in practice, and they may appear in conflict
win the values and advantages summarized above. It is, after all, difficult to
anticipate the potential secondary research applications of data collections
whatever their size, focus, or content. Even data from the most limited case
study, for example, can sometimes be combined with other data to provide a
basis for more extended explorations. The view that data collected from pub-
lic sources and processed to computer-readable form can be readily duplicated
is at best only partly correct. Such data collection efforts usually involve
large investments of time and energy, and to duplicate them is obviously
wasteful. Of greater importance, data collections of this sort often draw on
multiple sources, some of which may not be easily accessible, and often use
complex derived measures and aggregations. Given the imperfections of the
mechanics of citation, it is frequently impossible to completely identify pre-
cise sources and methods and to reconstruct derived measures and indexes.
Hence duplication of such data collections and replication and verification of
reported findings are often difficult if not impossible.
The recent controversy centering upon research reported by Martin S.
Feldstein that shows social security as a disincentive to saving is a case in
point (Feldstein, 1974, 1980; Leimer and Lesnoy, 1980~. In this instance,
Me original sources from which the data were obtained were not as easily
identified or available to others as was apparently assumed, and complex
derived indexes could not be readily reconstructed. Because the data were
not shared, He process of replicating and verifying the reported findings was
slowed, a programming error Hat marred the original analysis was not more
promptly discovered, and effective debate and evaluation of the findings were
delayed.
It is likely that few people would contest the importance of early and gener-
al access to data explicitly designed to provide a basis for policy formation or
evaluation or for social action. However, to argue that access to data for
more basic research is of lesser importance presents difficulties. It is worth
noting that Isaac Ehrlich's research on the deterrent effects of capital punish-
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Sharing Data in the Social Sciences
49
meet, one of the controversial recent examples of contestable research with
immediate policy consequences (Ehrlich, 1975; Bowers and Pierce, 1975;
Passell and Taylor, 1975) was apparently not commissioned to provide a basis
for policy decisions. The capacity to predict that particular research will or
will not have policy consequences is far from perfect, and it is plausible to,
argue that most research has the potential for policy consequences.
It may well be that for practical reasons distinctions such as discussed in
this section must be made. However, the values and advantages of general
and timely access to data appear commanding, and the rule should be, it
would seem, to err on the side of these values and advantages rather than to
move prematurely to distinctions.
INCIDENCE OF DATA SHARING
The importance and value of data sharing in the social sciences can be ~llus-
trated in a number of concrete, albeit somewhat unsystematic, ways. As will
be noted at several points below, nothing approaching comprehensive infor-
mation is available documenting either the incidence of data sharing or the
multiple use of data collections. Several illustrations indicate, however, that
very considerable sharing occurs and that data sharing is one of the vital un-
derpinnings of research and instruction in the social sciences. The illustra-
tions below also suggest that significant progress has been made toward real-
ization of the values summarized in the preceding section.
Social Science Data Archives
Data sharing occurs in a variety of ways, including informal sharing among
individual scholars and research groups as well as through organizations that
function as data repositories and dissemination services. Indeed, one indica-
tion of the importance of data sharing is the development in the United States
and other nations during the past two decades of numerous organizations that
serve as mechanisms to provide general access to the basic data of social
science research. These facilities include national indeed, international
"social science data archives" in the academic sector, venous private organi-
zations that provide access to data, as well as organizations that maintain and
disseminate data collected by government agencies. In addition, numerous
local facilities maintain data collections, usually obtained from national data
organizations, for use by a particular university community, government
agency, or private firm. (A selected list of data organizations appears as the
appendix to this paper.) The existence of these facilities and the resources in-
vested in them suggests, of course, the value and importance of data sharing
and multiple use of data collections.
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78
Jerome M. Clubb et al.
Machine-Readable Archives, Public Archives of Canada, 395 Wellington Street, Ottawa,
Ontario, Canada K1A ON3
Machine-Readable Archives Division, (NNR), National Archives and Records Service,
Washington, D C. 20408
National Center for Education Statistics, Data Systems Branch, 205 Presidential Building, 400
Maryland Avenue, S.W., Washington, D.C. 20202
National Center for Health Statistics, Scientific and Technical Information Branch, Room 1-57
Center Building, 3700 East-West Highway, Hyattsville, Maryland 20782
National Center for Social Statistics, Office of Information Systems, Washington, D.C. 20201
National Opinion Research Center, University of Chicago, 6030 South Ellis Avenue, Chicago,
Illinois 60637
National Technical Information Service, U.S. Department of Commerce, 5285 Port Royal Road,
Springfield, Virginia 22151
Northwestern University Information Center, Vogelback Computing Center, Northwestern
University, Evanston, Illinois 60201
Norwegian Social Science Data Services, Universiteet i Bergen, Christiesgate 1~19, N-5014
Bergen-University, Norway
Oklahoma Data Archive, Center for the Application of the Social Sciences, Oklahoma State
University, Stillwater, Oklahoma 74074
Polimetrics Laboratory, Department of Political Science, Ohio State University, Columbus, Ohio
43210
Political Science Data Archive, Department of Political Science, Michigan State University, East
Lansing, Michigan 48823
Political Science Laboratory and Data Archive, Department of Political Science, 248 Woodburn
Hall, Indiana University, Bloomington, Indiana 47401
Project Impress, Dartmouth College, Hanover, New Hampshire 03755
Project TALENT Data Bank, American Institutes for Research, P.O. Box 1113, Palo Alto,
California 94302
Public Opinion Survey Unit, University of Missouri, Columbia, Missouri 65201
Roper Public Opinion Research Center, Box U-164R, University of Connecticut, Stores,
Connecticut 06268
Social Data Exchange Association, 229 Waterman Street, Providence, Rhode Island 02906
Social Science Computer Research Institute, 621 Mervis Hall, University of Pittsburgh,
Pittsburgh, Pennsylvania 15260
Social Science Data Archive, Laboratory for Political Research, 321A Schaeffer Hall, University
of Iowa, Iowa City, Iowa 52240
Social Science Data Archive, Survey Research Laboratory, 414 David Kinley Hall, Urbana,
Illinois 61810
Social Science Data Archive, Box 596, University of Notre Dame, Notre Dame, Indiana 46556
Social Science Data Archives, Department of Sociology and Anthropology, Carleton University,
Colonel By Drive, Ottawa, Ontario, Canada K1S SB6
Social Science Data Center, University of Connecticut, Stom, Connecticut 06268
Social Science Data Center, University of Pennsylvania, 353 McNeil Building, CR, 3718 Locust
Walls, Philadelphia, Pennsylvania 19104
Social Science Data Library, Manning Hall 026A, University of Norm Carolina, Chapel Hill,
Norm Carolina 27514
Social Science User Service, Princeton University Computer Center, 87 Prospect Avenue,
Princeton, New Jersey 08540
Social Security Administration, Office of Research and Statistics, Room 1120,, Universal North
Building, 1875 Connecticut Avenue, N.W., Washington, D.C. 20009
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Sharing Data in the Social Sciences
SSRC Survey Archive, University of Essex, Wivenhoe Park, Colchester, Essex, England
State Data Program, 2538 Channing Way, University of Califomia, Berkeley, California 94720
State Government Data Base, Council of State Governments, Iron Works Pike, Lexington,
Kentucky 40578
Statistics Canada, 1006-General Purpose Building, Ottawa, Ontano, Canada K1A OT6
Steinmetzarchief, Herengracht 41~12, 1017 BX Amsterdam, The Netherlands
lithe United Nations Statistical Office, The United Nations, New York, New York 10017
Zentralarchiv fur empirische Sozialforschung, Universitaet zu Koeln, Bachemer Strasse 40,
W5000 Koeln 41, West Germany
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1973 Problems in the Use of Archival Data. Prepared for the Panel on Research Problems in
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Benson, L.
1968 The empirical and statistical basis for comparative analysis of historical change. In
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Representative terms from entire chapter:
data collections