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Definitions, Products, and Distinctions in Data Sharing Robert F. Boruch For simplicity's sake, data sharing here is defined as the voluntary provision of information from one individual or institution to another for purposes of le- gitimate scientific research. In practice there are, of course, a great many variations on this theme. Some of the variations are suggested by the factors that influence data sharing and its products. THE PURPOSES AND PRODUCTS OF DATA SHARING The products of data sharing can serve a variety of beneficial purposes, in- cluding: · verifying, failing to verify, or examining the conclusions of earlier ana- Robert F. Boruch is a professor in the Department of Psychology and the School of Education and codirector of the Center for Statistics and Probability, Northwestern University. Background research for this paper was supported by a stipend from the National Research Council and a grant from the National Science Foundation to Northwestern University, Center for Statistics and Probability. 89
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go Robert F. Boruch lyses, as in public program evaluation or economic research on subsidy pro- grams; · facilitating education and training through active examples; · testing new hypotheses or theories using existing data, as in a good deal of economic research; · facilitating tests of new methods of analysis when the original data are well understood, as in attempts to better estimate cognitive ability using Rasch models or mortality using dual-system estimates; · using the data collected in one study or series to design other studies and programs, for example, in social programs or for physical or chemical con- structions in engineering; · combining several sets of data to facilitate syntheses of knowledge, deci- sion making, establishing limits or bounds on generalization, as in psycholog- ical and other research. The expected products of data sharing will not always appear, of course, and may not fulfill their purposes when they do. For example, poor research can often be identified from reports or tables, reducing the need for access to raw data. Replicating a study independently is often far more important than reanalyzing the results of the original effort, and this approach also reduces the need for access to raw records. Even when the information is pertinent to a scholar and is of good quality, the stress on sharing can be dysfunctional, for several reasons. The products may be pedestrian, for example, because it can be hard to reason ably and in original ways from data that have already been well analyzed. The process of sharing may lead to self-interested or inept as- saults on adequate work, as it has in the past. Perhaps more important, the stress on repeated analysis of observational data, from surveys for instance, can divert resources from the collection of better data, say, from field experiments, that could yield less ambiguous con- clusions. Data may be analyzed because they are available rather than be- cause they are interpretable and clearly material to a problem at hand, produc- ing work that is pedestrian or wrong repeatedly. And so on. In summary, it is reasonable to expect a variety of outcomes, positive and negative, from data sharing. The position taken here is that sharing in princi- ple is warranted simply because it is part of a durable scientific ethic to com- municate results in a way that permits confirmation. In practice, its appropri- ateness, feasibility, and utility depend on other factors. Voluntary Versus Involuntary Sharing There are cases of forced data sharing, in responses to demands for disclosure of information by a court, in the interest of assessing a scientist's claim.
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Definitions, Products, and Distinctions 91 Time and resources are not sufficient to examine such sharing in detail here, but a couple of cases do deserve brief attention: the Longs' efforts to obtain data from the Internal Revenue Service for research purposes and Forsham v. Harris. Dr. Susan Long, a sociologist at Princeton, and Mr. Philip Long, head of a business, have for the past 10 years been involved in efforts to secure statisti- cal and other data from the U.S. Internal Revenue Service (IRS) for research purposes. Susan Long's professional interest lies partly in examining consol- idated administrative data and IRS procedures manuals to determine how ad- ministrative discretion is used in applying tax law, i.e., how rate of audits var- ies by geographic region, income level of the taxpayer, etc. (see Long, 1979, 1980a, 1980b). The Longs maintain that the information they request falls within the coverage of the Freedom of Information Act (FOIA). Moreover, since the records on individuals that they need are anonymous, acceding to their request violates no privacy statutes. The IRS has disagreed, refusing, for example, to disclose counts of audits by income category and internal doc- uments on operating procedures for audits. In different court cases dealing with the requests, the IRS has maintained that disclosure of the data tapes or procedures would help taxpayers avoid audits, that the FOIA is not relevant, and that the privacy law will be violated, so the information should not be dis- closed. The Longs have also attempted to obtain information on the sampling frmne and results of studies generated in IRS probability sample audits; this information has also been refused. They have brought a number of such cases to the courts, winning access to some data under the FOIA in the lower courts. In particular, federal circuit courts have ruled that data tapes were discloseable under FOLD and not subject to laws governing disclosure of IRS records (26 U.S. Code &6103) when identifiers are deleted and the risk of deductive disclosure cannot be shown to be appreciable. The Longs have tes- tified before Congress on the need to make such information more accessible (P. Long and S. Long, 1974a, 1974b, 1976; S. Long and P. Long, 19731. In Forsham v. Harris, which was heard by the Supreme Court in 1979-1980, researchers were trying to obtain and reanalyze data generated in the University Group Diabetes Project (UGDP). The project, supported by the National Institutes of Health (NIH), was designed as a randomized field test of alternative methods of treating diabetes and resulted in the conclusion that one of the drugs tested, a popular one, appeared to have had strong nega- tive effects. The study generated a good deal of controversy, and the results were debated by the companies that produce He drug, physicians using it for treatment, interest groups, and statisticians. The original investigator refused requests by independent investigators for the data. The requesters filed suit under the Freedom of Information Act, maintaining that the data were col- lected under a federal contract for the National Institutes of Health and so
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92 Robert F. Boruch must be regarded as public, except for identification of individual participants in the study. In a 7-2 decision, the court ruled against disclosure. Writing for the majority opinion, Justice William Rehnquist maintained that the law applies to records actually in the government's hands. Because NIH had not asked for the data (at that time), the agency could not be used as a vehicle for getting the data. See Cecil and Griffin (in this volume) for details. Research Versus Administrative Functions of Data The emphasis in this paper is on sharing information for scientific research purposes. There is much less stress on sharing for commercial purposes, and no attention is given to data shared in the interest of making specific adminis- trative or judicial decisions about an individual. The distinction between re- search function and the administrative function of information here is impor- tant. It parallels one drawn by the Privacy Protection Study Commission (1977) and adopted in some recently proposed bills on privacy in research and statistics. The distinction is important since the rules that govern access to records for purposes of making a decision about an individual must differ from those go- verning access for research. For instance, access for administrative purposes can carry major consequences for an individual, as in credit reporting and cri- minal records. Access by researchers generally carries no such direct conse- quences. To judge from evidence obtained by the Privacy Protection Study Commission, abuses are more likely in the administrative use of data; thus, We focus of government rules and professional codes needs to differ depend- ing on who collected the records, who has access to them, and what the pur- pose of access is. Despite differences in function, administrative records can often be used for research purposes: see, for example, Chelimsky (1977) on the use of cn- minal justice records in evaluating crime control programs; Conger et al. (1976) and Peng et al. (1977) on using records to assay accuracy of response in educational surveys; Del Bene and Scheuren (1979) on statistical uses of administrative records from Social Security Administration and other govern- ment files for studies of disability; and Bishop (1980) on energy consumption experiments. The uses of administrative records in public health research are sufficient to justify an annual conference on records and statistics that is spon- sored by the National Center for Health Statistics and other agencies. Access to administrative records for research purposes can be at least as im- portant as sharing data originally collected for research purposes, but it raises different problems. The laws or rules governing confidentiality of adminis- trative records on individuals or institutions, for example, can impede re- searcher access unless special exemptions are created. Such exemptions do
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Definitions Products, and Distinctions 93 appear for certain kinds of research in the Privacy Act of 1974, governing fed- eral records, and similar exemptions appear in the laws of other countries (Mochmann and Muller, 1979; Plaherty, 19801. However, the opportunity for access to addresses of taxpayers maintained by the IRS virtually disap- peared with the Tax Reform Act. Rules ill the commercial sector vary con- siderably and decisions about permitting access appear to be mostly ad hoc, systematic only for the larger companies. Because the situation for private companies is so poorly explored—very little data on access practice exist for administrative records most of the material here focuses on public adminis- trative or research records. Contract and Grant Requirements Two common funding mechanisms for publicly supported research are con- tracts and grants. Contracts can be and often are written to ensure that the products? a report and the information on which it is based, are provided to government at the contract's end. The idea of data sharing emerges most of- ten in contract work, where the data belong, at least in principle, to the gov- ernment agency that asked for them. In practice, the accessibility may be ex- plicit in contract provisions (Garner, 1981), but it may be debated in the courts regardless of such provisions. Research grants also result in data that can be shared, but there has been lit- tle stress on routine sharing of such data partly because the data have been tre- ated as property of the principal investigator. Another reason for less atten- tion to data sharing in grants is that most grants are for the support of laborato- ry research in which replication of the research rather than reanalysis of indi- vidual records is paramount. Precedents for contract requirements to share data are easy to find. The data used in the Coleman et al. (1981) analysis of the relative effectiveness of private and public schools are part of a national longitudinal study of high school students conducted for the National Center for Education Statistics (NCES) by the National Opinion Research Center (NORC). The contract be- tween NCES and NORC specifies that data would be turned over to NCES for storage and distribution. However, although the data were available to other analysts when controversy erupted over the Coleman et al. work, few critics had actually reanalyzed the raw data. Since then, other analysts have worked with the data (Antonoplos, 1981~. Of course, access alone will not resolve some policy arguments about the work. For example, measurement of family income was based on children's responses to multiple choice questions, a pro- cess that warrants special attention and defense. Analogous provisions were incorporated into Department of Energy re- quirements for 16 recent public utility demonstration projects on peak-load
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94 Robert F. Boruch pncing. The data produced and their documentation must be furnished to the department (Federal Energy Administration, 1976) for synthesis and reanaly- sis. Provisions to ensure that information will be made available to the re- search community have also been incorporated into contracts by the National Institute of Education for the National Assessment of Education Progress, an annual survey of student performance conducted for the Education Commission of He States, and by the National Center for Health Services Research for Michigan State University's Data Center on Long Term Health Care (Katz et al., 1979), and others. THE NATURE OF SHARED INFORMATION AND VEHICLES FOR SHARING The nature of the information that is made accessible varies a great deal. Alloy phase diagram data are consolidated and made available to scientists and engineers through the National Bureau of Standards and the American Society for Metals. The Materials Properties Data Center stores and disse- minates machine-readable data on tests on metals and ceramics to govern- ment, commercial, and academic users through a facility at Battelle Laboratories, and analogous on-line facilities are under development by the Copper Development Association, the Materials Properties Council, and oth- ers (see National Research Council, 1980~. The National Bureau of Standards has a major brokerage role in these and in the Fundamental Particle Data Center, Diffusion in Metals Center, the Data Center for Atomic Transition Probabilities, and the Crystal Data Center, to which physical scien- tists and engineers contnbute. Videotapes of selected commercial and public television broadcasts are ac- cessible to communications researchers, historians, and others at the National Archives, in specialized libraries at George Washington University, Vanderbilt University, and elsewhere (Adams and Schreibman, 19781. Oral history tapes are maintained at Columbia University and elsewhere. Results of acoustic tests are shared, too. One of the dramatic recent examples of the latter involves Bell Telephone Laboratory's audio recordings, generated as part of research under Arthur C. Keller during the 1930s, which recorded, among others, the Philadelphia Orchestra under Leopold Stokowski. The audio products of these technical tests on stereophonic recording methods, amplification, processing, and the like are maintained at the Rogers and Hammerstein Archives at the New York Public Library. Educational data from large-scale surveys are often made available through a variety of private and public agencies, as are health statistics and welfare data from surveys and social experiments (see below). Such data have been used in basic sociological research to test ~eroretical models, but they are
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Definitions, Products, and Distinctions 95 probably used more often in applied research to anticipate or estimate the ef- fects of changes in tax law, Social Security and welfare rules, and the like. The administrative vehicles for distribution of these data include general gov- ernment facilities, such as the National Archives (see Dollar and Ambacher, 1978), specialized ones, such as the Bureau of Labor Statistics, National Center for Health Statistics, and others (see the review by Duncan and Shelton, 1978), academic data banks at the University of Michigan, the University of California, the University of North Carolina, and elsewhere, and private distributors such as DUALabs. The U.S. National Oceanic and Atmospheric Administration (NOAA) op- erates a variety of agencies that facilitate or serve as a vehicle for sharing nu- mencal information internationally. At the National Oceanographic Data Center, for instance, routine observation data from private and public sources continually are pooled and updated. The National Geophysical and Solar Terrestrial Data Center archives and distributes data relating to solid earth physics, e.g., volcanoes and earthquakes, geothermics, etc. The National Geodetic Survey Information Center distributes mapping information in machine-readable and other forms to federal, state, and local agencies and . . sclentlsts. Whatever the administrative vehicles for sharing data and the nature of the shared data, the process can be remarkably interdisciplinary. For example, economists Cain and Watts (1970) have reanalyzed data produced by educa- tional researchers Coleman et al. (1966) to reach conclusions about the effec- tiveness of compensatory education. Criminal sociologists Bowers and Pierce (1975) have rebutted Ehrlich's (1975) econometric analyses of the ef- fect of capital punishment on homicide rates, based on publicly available da- ta. Anthropologists have used satellite photos that were initially archived for agricultural and geophysical research to understand herd migration and the ef- fect of new wells in Norm Africa. The productivity of cross-discipline con- versations is also reflected in reanalyses of meteorological experiments (e.g., Braharn, 1979, and his critics). Of course, the feasibility of storing and distributing data depends on the information's character. It seems fair to say that machine-readable numerical data tapes are more suitable for routine sharing and that more is understood about efficiency in their production and distribution than for some other kinds of information, such as videotapes, pardy because experience with others is more recent. The problem of ensuring individual privacy and confidentiality has received more attention and appears to be more tractable for statistical re- search data than for other information. For example, blocking out faces is possible in videotape research on behavior of children or adults in classrooms, but it is difficult. Voiceprint analysis and other methods may make identifi- cation possible in analysis of videotapes and audio-taped oral histones.
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96 Robert F. Boruch Because of the diversity of the kinds of data that research on for scientific pur- poses have to recognize major differences in the nature of information that is shared. Source Lists There is of course no universal list of the ~nforTr~ation that is routinely made available for scientific analysis, although archives that handle machine- readable data often issue regular reports on the data maintained. For in- stance, the National Technical Information Service (NTIS) and the Office of Statistical Policy and Standards (OFSPS) have regularly issued a Directory of Federal Statistical Data Files to assist users in locating what they need. Similar lists are issued by operating agencies for special user groups, e.g., the Directory of Federal Agency Education Data Tapes (Mooney, 19791. The problem of maintaining useful inventories of data tapes that can be shared is complicated and severe enough to have received the attention of President Carter's Reorganization Project on the Federal Statistical System. At least one commercial directory is available, the Encyclopedia of Information Systems and Services (pizzas and Sullivan, 1978), which covers bibliograph- ic as well as numerical machine-readable data, but it is not as thorough in cov- erage as the government listings noted above. Such lists pertain to data that are stored and distributed by standing archives rather than by individual scientists. To identify new data Mat may eventually be shared, formally or informally, by scientists or institutes, the annual re- ports of research supported by private foundations or public agencies can be helpful. Catalogs of applied research and evaluation projects are issued regu- larly by the U.S. Department of Education and the U.S. Department of Heals and Human Services (for example, 1983), the NTIS, and others. The U.S. General Accounting Office issues the Federal l~formation Sources and Systems (for example, 1976, 1980b) describing about 1,000 federal systems bearing on fiscal, budgetary, and program-related data, and Federal Evaluations (for example, 1980a), covering over 1,700 reports on specific programs. Either of these reports can be used to guide searches to numerical data that can be reanalyzed by independent researchers. The final broad class of sources includes statistical reports issued by the government or commercial vendors. The federal government, for instance, serves as a broker in consolidating statistics from disparate sources in such periodicals as Copper: Quarterly Report, Forest Products Review, Printing and Publishing Quarterly Report, Condition of Education, and others. Some of the statistics in these publications are based on microrecords Hat are avail- able from government agencies, such as the Social Security Administration, and from commercial sources, such as Dun and Bradstreet and McGraw-Hill
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Definitions, Products, and Distinctions 97 Information Systems Company. No formal research appears to have been pu- blished on the utility of directories such as these, nor have there been any pu- blished critiques of the documents. International Aspects Data sharing is not confined to researchers in the United States, of course. Danish and German data archives, for instance, serve European social scien- tists with an interest in accessing and storing social data from field studies (see, e.g., Kaase et al., 1980~. New professional organizations such as the American Society of Access Professionals, the International Association for Social Science Information Service and Technology, and the International Federation of Data Organizations have helped to consolidate social scientists' interests in analyzing machine-readable data (Mochmann and Muller, 19791. The International Federation of Television Archives was created by represen- tatives of the broadcasting companies' television archives, and membership is extended to university-based and other TV archives (Schreibman, 1978~. International organizations such as the Organization for Economic Cooperation and Development and UNESCO have begun to try to establish guidelines on data sharing. International exchanges are not uncommon in en- gineenng, to judge from the American Society for Metals/National Bureau of Standards joint effort on data sharing for construction of alloy phase dia- grams. A collaborative 12-country effort to assay academic achievement of students, the International Educational Assessment (Jaeger, 1978; Postlewaite and Lewy, 1979), illustrates a similar cooperative effort in educational re- search. At We level of the individual researcher, examples of sharing across nation- al boundaries are not difficult to find. The randomized field experiments on nutrition and educational enrichment in Colombia are, for instance, some- thing of a milestone in demonstrating effects of such programs (McKay et al., 1978), and a small group of Colombian and U.S. researchers continue to reanalyze machine-readable results. Exchanges and cooperative projects are not as frequent as they ought to be in engineering, according to the National Research Council (1980) because of problems in nonuniform nomenclature and testing and reporting methods, quality of input, and language. Similar problems doubtless affect sharing in the social and behavioral sciences. Aside from single projects such as the international Educational Assessment and sporadic individual sharing, the stress in social, behavioral, and educa- tional research is on one's own county data. Rules governing international information flows are generally designed for commercial record systems, but they may also apply to scientific data (see Boruch and Cordray, below).
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98 Robert F. Boruch Consolidation Level of Statistical Data The level of consolidation of the data that are shared also varies. In educa- tion, for instance, some archives store individual (and anonymous) student re- sponses to items in achievement tests and make the data available for reanaly- sis along with over information: for example, Gomez (1981 ) on tests of abili- ty measures for children of Colombian barrios. More commonly, however, test data on individuals are consolidated to produce a total score. Such totals for achievement tests, indices of functional or social mobility, or in- dices of income—have typically been available for reanalysis in educational, psychological, and sociological research. In the archives that make institutional data available, on banks for example, the data may be aggregated in such a way as to prevent analysis of individual banks, since disclosure of confidential information on the institution may be illegal or unethical. Rather, the independent analyst has access only to sum- mary data on a sample of small clusters of banks, as in the Wisconsin Income and Assets File (Bauman et al., 1970), or on data aggregated to regional or state level, as in most published reports of the U.S. Census Bureau. In still other cases, the data may be made available as summary statistics, obtained from a facility that analyzes the raw data according to prescription of the data requester, e.g., some research on Social Security Administration files (Alexander and Jabine, 1978) and on Internal Revenue Service files under the Tax Reform Act of 1976 (Alexander, 1981~. Much less fine-grained data are customarily available as the summary sta- tistics published in research reports or journal articles, and a good deal can be learned from these. Indeed, what is learned may eliminate or reduce the need for access to the raw data. To the extent that tabulated statistics are designed to exploit all the information in a sample and one is willing to trust that the analysis is appropriate and carried out as described, there may be no need for the raw data from a particular study. 'That journal publication of even crude details of analysis can be useful in detecting errors in analysis and Mat some errors will be important and warrant obtaining original data is clear, however: see, for example, Good (1978) and Wolins (1982) for lessons, based on jour- nal articles, about mistakes in analysis and inference. There are no generally accepted guidelines on what to publish and, partly as a consequence, practice is not uniform.2 In the interest of ensuring Mat read- ers can understand the original analysis and can verify it or not, at least super- ficially, suggestions on what to publish have been developed by Krusk˘al (1978) for science indicators, Mosteller et al. (1980) and Chalmers et al. (1981) for journal editors, and the U.S. General Accounting Office (1978) for federal evaluation reports. Such guidelines stress including information
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Definitions, Products, an~Distinctions 99 about the nature of samples and randomization, statistical power and signifi- cance levels for tests, confidence intervals, the model underlying analysis, and so on. PRIVACY AND CONFIDENTIALITY AND PROPRIETARY INTERESTS Two issues in data sharing are debated often. They bear on confidentiality of information and privacy of individuals on whom records are shared and pro- pneeary interests in capitalizing on data. The value of the data themselves, less often debated, is at least as important as are other matters treated in the re- mainder of the report. Privacy and Confidentiality If the information shared for scientific purposes bears on individuals or insti- tutions, then privacy may be a critical issue. Partly as a consequence, a good deal of work has been done on understanding when information on identifi- able individuals should remain confidential and how to ensure confidentiality. The work is international, having been undertaken in the United States, Canada, Germany, Sweden, and elsewhere. It spans disciplines, solutions to related problems being developed by statisticians, lawyers, social and be- havioral scientists, and others. The following sketch of some developments is based on Boruch and Cecil (19791. General strategies for ensuring confidentiality can be classified into three broad categories: statistical, procedural, and legal. Statistical strategies in- clude those used in initial data collection, e.g., randomized response, contam- ination, response aggregation methods, and so ameliorate problems of later data distribution. They also include methods used in the data distribution process to protect against deductive disclosure of information about identifi- able individuals based on nominally anonymous records. Deductive disclo- sure here refers to the possibility of deducing that a particular record, stripped of identifiers, belongs to a particular known individual, or deducing that iden- tif~ed individuals have certain characteristics from published statistical tables (or public-use tapes) and collateral information on the individual. Staff of census bureaus in the United States, He United Kingdom, and Sweden, for in- stance, have developed algorithms to determine if deductive disclosure is possible in releases of series of statistical tables. The strategies developed to reduce the likelihood of such disclosure include special numerical rounding techniques, error inoculation, and repeated subsampling. Procedural strategies generally involve nontechnical approaches to reduc- ing privacy or confidentiality problems. The simplest include not obtaining
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112 Robert F. Boruch Mindlin and Kovacs (1979), the difficulties include: (1) obtaining access to data, especially in view of propnetary interests; (2) reformatting input data to accord with output criteria; (3) instructing potential users about the system; (4) user suspicion of data that were not generated by the user's agency; and (5) marketing. The alloy phase diagram program is a joint venture of the American Society for Metals and the National Bureau of Standards. It is dedicated to acquiring, evaluating, and distributing data on microstructural change in alloys as a func- tion of temperature and alloy composition, the data being summarized in stan- dardized phase diagrams. Both private and publicly supported research la- boratories supply the basic data. Cooperation among a variety of institutions is necessary since it is impractical for any single institution to undertake pro- duction of data on all types of alloys. The effort is international, involving research units in the United States, Germany, Japan, and other industrialized counties. The phase diagram program stresses distribution heavily. Diagrams are published as final or provisional in a journal, Bulletin of Phase Diagrams, whose editorial board is international. The journal also carries information on how to use the diagrams, references to source articles, and reports and re- l~ted information (see Bennett, 1980; National Bureau of Standards, 1980a, 1980b). Combining Studies Pooling data on Me same topic from several sources or examining several stu- dies simultaneously can be an effective vehicle for better understanding of the topic, Cough technical problems can be severe (e.g., nonindependence of We separate data). In Me simplest case, of course, a review of literature consti- tutes one kind of common pooling. The more numerically oriented combina- tions take several forms (Glass, 19761. In some research, for example, one level of combination addresses only statistics available in published articles, not raw microrecords. The approach has been used by Gilbert et al. (1977) to understand likelihood of success in innovative surgery, by Light and Smith (1971) to reconcile conflicting results, by Smith and Glass (1977) to assay distribution of successful and unsuccess- ful methods of psychotherapy, by Gordon and Morse (1975) in examining likelihood of success and failure in public programs, and elsewhere. There are many such routine uses in engineering. As described above, data on properties of materials and phase diagrams are constructed from data supplied by a variety of sources (National Research Council, 1980~. Combining raw data on individuals from surveys and social experiments with records from administrative archives is not common, but it has become
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Definitions, Products, and Distinctions 113 more so over the past 10 years, partly because the results are illuminating. Some of the effort is designed to understand the structure of error in adminis- trative records or survey responses or both. The interagency linkage study conducted by the Census Bureau, Social Security Administration, and Internal Revenue Service illustrates the type, though sharing is confined to the federal agencies; the same is true for some program evaluations in health care and social welfare (Boruch and Cecil, 19791. In social research, the purpose of combining data sets often is for policy research. Michigan's Archive on Long TerTn Care, which acquires data on long-term care field experiments, puts it into uniform format, and makes the files available for policy analyses (Katz et al., 1979), and Columbia's Housing Survey Project (Beneridge and Dhrymes, 1981) fall into this category. So do recent contracts of the U.S. Department of Energy with Research Triangle Institute for compilation and standardized analysis of state utility demonstration projects on peak-load pric- ing that were analyzed earlier in nonuniform, different ways by the individual state utilites (Research Triangle Institute, 1978~. EVALUATION OF DATA-SHARING EFFORTS While the idea of data sharing in principle is agreeable to many scientists, at least for publicly supported research, what good the sharing does is not often assayed systematically. To be sure, peer review constitutes a kind of immediate evaluation when plans for large-scale sharing are drawn up and projects that hinge on data shar- ing are proposed. But these reviews He often neither open to scrutiny nor, more importantly, directed at the utility of the product. The more arrogant directors of a data collection effort may not say that the worth is self-evident, but the implication is there insofar as very little hard evidence on utility of the information Is published. The problem of evidence has become more crucial for federally supported work as a consequence of restrictions in resources for collecting new information and increasing congressional and administrative interest in evaluating basic and applied research programs. Apart from politi- cal incentives, the problem of understanding how to evaluate the product of data-sharing systems, how to improve them, and when to encourage or ter- minate them seems a reasonable intellectual problem. The state of the art in evaluation of information collection efforts, including the product data sharing is underdeveloped. Systematic theory on cost/benefit analysis of data has only recently been developed (Spencer, 1980) and only for social survey data used in allocating resources by the Congress. Use of data, much less its value, is difficult to measure even when mission- oriented research Is carried out and the resulting data subjected to competing analyses (Boruch and Cordray, 19801. Nonetheless, some crude methods are
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114 Robert F. Boruch available, and they could be applied and refined. The documents issued as a result of analyses of shared data constitute one indicator of productivity of an archive. But frequency counts of publications and bibliographies that summarize the products and why they are important are not common. Exceptions include Peng et al. (1977) and Taylor et al. (1981) on NCES's national longitudinal studies, Bielby et al. (1977) on the Department of Labor's national study of labor supply, Postlewaite and Lewy (1979) on the international educational assessment, and related products issued by the NRC medical follow-up study, Project Talent, Northwestern's Project on Secondary Analysis, etc. Logs sometimes maintained by data- sharing institutions, such as those of the National Assessment of Educational Progress and National Center for Education Statistics, on requests for tape files, documentation, etc., constitute a major vehicle for tracing further prod- ucts and their utilization (see Peng et al., 19771. Frequency counts are at least partly corruptible and insufficient. The corruptibility is fair game for measurement research. Sufficiency might be achieved with other indicators. Quality of the product is important, but systematic research on this is even less common. Exceptions are confined to a few evaluations of medical and oceanographic research programs, and of the use of peer ratings and citation counts as bases for judging the adequacy of institutional work (National Research Council, 1981~. The strategies developed in those approaches are generalizable perhaps to products generated by data archives but have not been applied. The process of sharing data, as well as products such as reports, can also be evaluated in some sense. The questions that might be addressed include: How easy is it to find out about data? How easy and efficient is the process of acquisition or distribution? What are the costs and are they reasonable? How well are data updated, corrected, documented? And so on. Managerial questions such as these are examined at times within archives. But the ex- penence itself is not often discussed in published papers, seems to be less ord- erly than it might be, and probably would profit from more concerted atten- tion. There are a sufficient number-of efforts to develop standards of docu- mentation by Robbin (1981b) and others to make some evaluations of this sort possible. But evaluations of processes of other sorts and especially of prod- uct utility are likely to be more difficult. Vehicles for simple routine monitoring of extent and nature of sharing are sometimes available. For instance, the American Chemical Society's jour- nals department head, Charles Birch, maintains records, for articles published since 1974, on the provision of supplements by authors (e.g., raw data) to the Journal of the American Chemical Society. The supplements in microfiche form are available through subscription or ad hoc requests, and estimates of rates of requests for venous ACS journals are available (see Borsch and
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Deft nitions, Products, and Distinctions 115 Cordray, in this volume). Not all journals have a data supplement service of this type, and a monitoring system for those that simply require authors them- selves to make data available would have to be invented. Establishing the impact of sharing regardless of quality or number of the physical products and regardless of the process is likely to be most difficult. Most management decisions based on such data, e.g., at the level of the Assistant Secretary for Policy in the U.S. Department of Health and Human Services, are likely to be barely visible and tangled with other information. Consequently, making an inference about whether the data actually influ- enced the decision is risky. Design decisions in engineering and experimentation He typically small and forgettable, and utility of infonnation hard to obtain. Deciding whether a scholarly paper, published on the basis of shared information (or for that matter on unshared information), is a distinctive contribution to scholarship is frustrating, difficult, and will be impossible for some. The whole matter be- comes much more difficult with multiple users, of course, when users are barely identifiable. In summary, formal evaluations of data-sharing efforts are not common, the state of the art in evaluation is underdeveloped, formal evaluation may be warranted to understand the worth of the activity, and a variety of types of evaluation may be possible. NOTES 1. Some formal research on levels of accessibility of administrative records has been done by Gordon and Heinz (1979) and Sasfy and Siegel (1982) to understand the influence of practice and policy of government agencies and the nature and source of demand for information. 2. The quality of reporting summary data and other aspects of research seems to have im- proved considerably since Pigman and Carmichael (1950) identified good reporting as an ethical obligation of scientists (p. 644): '`Even casual inspection (showed) that many articles are not writ- ten so that the work can be repeated." 3. The time-genes data underlying Feldstein's work and used by Leimer and Lesnoy are ac- cessible in published statistical abstracts, e.g., Annual Statistical Supplement to the Social Security Bulletin, Handbook of Labor Statistics, Current Population Reports of the Census Bureau, and others (see Leimer and IRsnoy, 1980, Appendices D and E). REFERENCES Adams, W., and Schreibman, F.C., eds. 1978 Television Nenvork News: Issues in Current Research. Washington, D.C.: School of Public and International Affairs, George Washington University. Alexander, L. 1981 Proposed Legislation to Improve Statistical Research Access to Federal Records. Unpublished report. Social Security Administration, U.S. Department of Health and Human Services, Washington, D.C.
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116 Robert F. Boruch Alexander, L., and Jabine, T. 1978 Access to Social Security rnicrodata files for research and statistical purposes. Social Security Bulletin 41:~17. Antonoplos, D., ed. 1981 Proceedings of the National Institute of Education Conference on Conflicting Research Results. National Institute of Education, Washington, D.C Battelle Columbus Laboratories 1980a Metals and Ceramics Information Center List of Technical Publications. Columbus, Ohio: Battelle. Battelle Columbus Laboratories, Mechanical Properties Data Center 1980b Descriptive brochure. Battelle, Columbus, Ohio. Battelle Columbus Laboratones, Metals and Ceramics Information Center. 1980c Descriptive brochure. Battelle,Columbus,Ohio. Bauman, R.A., David, M.H., and Miller, R.F. 1970 Working with complex data files: the Wisconsin assets and income studies archive. Pp. 112-136 in R.L. Biscoe, ea., Data Bases, Computers, and the Social Sciences. New York: Wiley-Interscience. Bejar, I., and Rezmovic, V. 1981 Assessing educational and nutritional findings in the Call experiment. In R.F. Boruch and D.S. Cordray, eds., Reanalyzing Program Evaluations. San Francisco: Jossey- Bass. Benendge, A.A., and Dhrymes, P.J. 1981 Annual Housing Survey Project. Center for the Social Sciences, Columbia University. Bennett, L. 1980 Editor's coiner. Bulletin ofAlloyPhaseDiagrams 1(1):5. Bernstein, J. 1978 Experiencing Science. New York: Basic Books. Bielby, W.T., Hawley, C.B., and Bills, D. 1977 Research Uses of the National Longitudirml Surveys of Labor Market Experience. Madison, Wisc.: Institute for Research on Poverty. Bishop, L. 1980 Consideration in Analyzing and Generalizing from Time of Use Electricity Pricing Studies. Paper presented at the Electric Rate Demonstration Conference, Denver. Boruch, R.F., and Cecil, J.S. 1979 Assuring the Confidentiality of Data in Social Research. Philadelphia: University of Pennsylvania Press. Borsch, R.F., and Cordray, D.S., eds. 1980 An Appraisal of Educational Program Evaluations: Federal, State, and Local Agencies. Report to the Congress. Office of the Assistant Secretary for Management, U.S. Department of Education, Washington, D.C. Boruch, R.F., Cordray, D.S., Pion, G., and Leviton, L. 1981a A mandated appraisal of evaluation practices: digest of recommendations to the Congress and to the Department of Education. Educational Researcher 10(April): 1~13,31. Boruch, R.F., Worunan, P.M., and Cordray, D.S., eds. 198 lb Reanalyzing Program Evaluations. Son Francisco: Jossey-Bass. Boruch, R.F., and Wortman, P.M. 1978 An illustrative project on secondary analysis. New Directions for Program Evaluation 4:8~1 10. 1979 Implications of educational evaluation for evaluation policy. In D. Berliner, ea., Review of Research in Education 7:309-361.
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118 Robert F. Boruch Director, S. 1981 Examining potential bias in manpower training evaluations. Pp. 35~361 in R.F. Boruch, P.M. Wortrnan, and D.S. Cordray, eds., Reanalyzing Program Evaluations. San Francisco: Jossey-Bass. Dollar, C.M., and Ambacher, B.I. 1978 The national archives and secondary analysis. New Directions for Program Evaluation: Secondary Analysis 4:1~. Duncan, I.W., and Shelton, W.C. 1978 Revolution in United States Government Statistics. Washington, D.C.: Office of Statistical Policy and Standards, U.S. Department of Commerce. Ehrlich, I 1975 The deterrent effect of capital punishment: a question of life and death. American Economic Review 65:397~17. 1981 Capital punishment as deterrent: challenging reanalysis. Pp. 262-282 in R.F. Boruch, P.M. Worunan, and D.S. Cordray, eds., Reanalyzing Program Evaluations. San Francisco: Jossey-Bass. Federal Energy Administration, Regulatory Institutions Office 1976 Experiment Guidelines for Electric Utility Demonstration Projects. Unpublished me- morandum, November 8. U.S . Department of Energy, Washington, D.C. Feldstein, M. 1974 Social security, induced retirement, and aggregate capital accumulation. Journal of Political Economy 82(5):905-926. Flaherty, D.H. 1980 Privacy and Government Data Banks: An International Perspective. London: Mansell. Garner, J. 1981 National Institute of Justice access and secondary analysis. Pp. 43~9 in R.F. Boruch, P.M. Worunan, and D.S. Cordray, eds., Reanalyzing Program Evaluations. San Francisco: Jossey-Bass. Gilbert, J.P., McPeek, B., and Mosteller, F. 1977 Progress in surgery and anesthesia: benefits and risks of innovative therapy. Pp. 124-169 in J.P. Bunlcer, B.A. Barnes, and F. Mosteller, eds., Costs, Risks, and Benefits of Surgery. New York: Oxford University Press. Glass, G.V. 1976 Primary, secondary, and meta-analysis of research. 5(10):~8. Educational Researcher Gomez, H. 197? Evaluating Longitudinal Data with the Use of Rasch Model. Paper presented at the 41st Session of the International Statistical Institute, December =15, New Delhi, India. 1978 The Analysis of Growth. Ph.D. dissertation, psychology department, Northwestern University. (Available from University Microfilms, Ann Arbor, Mich.) 1981 Reevaluating educational effects in the Call experiment. Pp. 28~295 in R.F. Boruch, P.M. Worunan, and D.S. Cordray, eds., Reanalyzing Program Evaluations. San Francisco: Jossey-Bass. Good, I.J. 1978 Statistical fallacies. Pp. 337-349 in W.H. Kruskal and J.M. Tanur, eds., international Encyclopedia of Statistics (Vol. 1). New York: Free Press. Gordon, A.C., and Heinz, J.P., eds. 1979 PublicAccesstoInformation. New Brunswick,N.J.: Transaction.
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120 Robert F. Boruch 1~22 in J.A. Graham, ea., Use of Computers in Managing Material Property Data. MPG-14. New York: American Society of Mechanical Engineers. Mochmann, E., and Muller, P.J., eds. 1979 Data Protection and Social Science Research. Franl~urt, Germany: Campus Verlag. Mooney, E.D. 1979 Directory of Federal Agency Education Data Tapes. Center for Education Statistics. Moskowitz, J., and Worunan, D.M. 1981 Reassessing the impact of school desegregation. Pp. 322-340 in R.F. Boruch, D.M. Worunan, and D.S. Cordray, eds., Reanalyzing Program Evaluations. San Francisco: Jossey-Bass. Mosteller, F., Gilbert, J.P., and McPeek, B. 1980 Reporting standards and research strategies for controlled teals: agenda for the editor. Controlled Clinical Trials 1:37-58. NIoynihan, D.P., and Mosteller, F., eds. 1972 On Equality of Educational Opportunity. New York: Vintage Books. MuMell, A. 1974 The Effect of Social Security on Personal Savings. Cambridge, Mass.: Ballinger. National Bureau of Standards, Alloy Data Center 1980a ASM/NBS Alloy Phase Diagram Program. Unpublished memo. Washington, D.C. 1980b Alloy Data Center Publications. National Bureau of Standards, unpublished bibliogra- phy, September. Washington, D.C. National Center for Education Statistics 1981a Policy seminar sponsored by NCES in conjunction with the Horace Mann Learning Center. NCES Announcement, April. 1981b NCES data tapes now available for High School and Beyond. NCES 81-226a. NCES Announcement, February. National Research Council 1977 Perspectives on Technical Information for Environmental Protection. Steering Committee for Analytic Studies for the U.S. Environmental Protection Agency. Washington, D.C.: National Academy of Sciences. 1980 Mechanical Properties Data for Metals and Alloys: Status of Data Reporting, Collecting, Appraising, and Disseminating. Panel on Mechnical Properties Data for Metals and Alloys, Numencal Data Advisory Board Washington, D.C.: National Academy Press. 1981 Synopsis of the Ad Hoc Meeting on Private and Public Schools. Unpublished report. Committee on National Statistics, National Academy of Sciences, Washington, D.C. Page, E.B., and Keith, T.Z. 1981 Effects of U.S. private schools: a technical analysis of two recent claims. Educational Researcher 10:1-7. Peng, S.S., Stafford, C., and Talbert, R.J. 1977 Review and Annotation of Study Reports: National Longitudinal Study. Washington, D.C.: National Center for Education Statistics. Pigman, W., and Carmichael, E.B. 1 950 An ethical code for scientists. Science 111 :643~45. Postlewaite, T.N., and Lewy, A. 1979 Annotated Bibliography of IEA Publications (1962-1978). Stockholm: International Educational Assessment, University of Stockholm. 1977 Personal Privacy ire an Information Society. Supt. Doc. No. 052 003 00395-3. Washington, D.C.: U.S. Government Printing Office. Washington, D.C.: National
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Deft nitions, Products, and Distinctions 121 Research Triangle Institute 1978 Project Pooled Analyses: Feasibility of Combining Data from Several Electric Utility Rate Demonstration Projects. Report prepared by the U.S. Department of Energy' Office Utility Systems. Research Triangle Institute, Research Tnangle Park, N.C. Robbin, A. 1981a Strategies for improving utilization of computerized statistical data by the social scien- tificcommunity. SocialScienceInformationStud~es 1:~109. Robbin, A. 1981b Technical guidelines for preparing and documenting statistical data for secondary ana- lyses. In R.F. Boruch, P.M. Worunan, and D.S. Cordray, eds., Reanalyzing Program Evaluations. San Francisco: Jossey-Elass. Rossi, P.H., and Lyall, K.C. 1976 Reforming Public Welfare: An Evaluation of the New Jersey Income Maintenance Experiment. New York: Russell Sage. Sasfy, J., and Siegel, L. 1982 A Study of Research Access to Conf dential Criminal Justice Agency Data. McLean, Va.: Mitre Corp. Schreibman, F.C. 1978 Television news archives: a guide to major collections. Pp. 89~110 in W. Adams and F. Schreibman, eds., Television Network News: Issues in Current Research. Washington, D.C.: School of Public and International Affairs. Smith, M.L., and Glass, G.V. 1977 Meta-analysis of psychotherapy outcome studies. American Psychologist 32:752-760. Spencer, B.D. 1980 Ben~fit-Cost Analysis of Data Used to Allocate Funds. New York: Springer-Verlag. Taylor, M.E., Stafford, C.E., and Place, C. 1981 National Longitudinal Study of the High School Class of 1972 Stay Reports Update: Review andAnnotation. Washington, D.C.: National Center for Education Statistics. U.S. Department of Health and Human Services 1983 Compendium of HAS Evaluation Studies. Washington, D.C.: U.S. Department of Health and Human Services. U.S. General Accounting Office 1976 Federal Information Sources and Systems: A Directoryfor the Congress. Washington, D.C.: U.S. General Accounting Office. 1978 Assessing Social Program impact Evaluations: A Checklist Approach. Washington, D.C.: U.S. General Accounting Office. 1980a Federal Evaluations: A Directory Issued by the Comptroller General. Washington, D.C.: U.S. General Accounting Office. 1980b Federal Information Sources and Systems: A Directoryfor the Congress. Washington, D.C.: U.S. General Accounting Office. van Hippel, F., and Primack, J. 1972 Publicinterest science. Science 177:116~1171. Walberg, H., Anderson, R.E., Miller, J.D., and Wright, D.3. 1981a Policy Analysis of National Assessment Data. University of Illinois, Chicago Circle. 1981b Probing a model of educational productivity in science with national assessment sam- ples of early adolescence. American Educational Research Journal 18(2):23~249. Wolins, L. 1982 A Critical Commentary on Research in the Social and Behavioral Sciences. Ames, Iowa: Iowa State University Press.
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122 Robert F. Boruch Woranan, P.M., Reichardt, C.S., and St. Pierre, R.G. 1978 The first year of the education voucher demonstration: a secondary analysis of student achievement scores. Evaluation Quarterly 2:19~214. Zirkel, C. 1954 Citation of fraudulent data. Science 120:189-190.
Representative terms from entire chapter: