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Access to data and material for research: putting empirical evidence into perspective

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The aim of this article is to put into critical perspective the empirical findings on …

The aim of this article is to put into critical perspective the empirical findings on
secrecy and withholding in research. In other words, by taking existing
empirical literature into account, it is intended that a crucial question is
answered: Is secrecy and withholding in research harmful or innocuous to
science? To understand how secrecy and withholding in research have
affected academic science, empirical studies have been placed in the wider
context of Mertonian underpinnings of the anticommons threat. The turning
point in testing the effects of secrecy and withholding of data and material
on scientific research was marked by statistical studies based on surveys and
bibliometric measures. These two types of empirical studies have given
answers to the basic question since academia was threatened by different
modes of practicing science.

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  • 1. New Genetics and Society Vol. 28, No. 1, March 2009, 67–86 Access to data and material for research: putting empirical evidence into perspective Victor Rodriguezà TNO, Innovation Policy Group, Delft, The Netherlands The aim of this article is to put into critical perspective the empirical findings on secrecy and withholding in research. In other words, by taking existingDownloaded By: [Radboud University Nijmegen] At: 10:22 17 September 2009 empirical literature into account, it is intended that a crucial question is answered: Is secrecy and withholding in research harmful or innocuous to science? To understand how secrecy and withholding in research have affected academic science, empirical studies have been placed in the wider context of Mertonian underpinnings of the anticommons threat. The turning point in testing the effects of secrecy and withholding of data and material on scientific research was marked by statistical studies based on surveys and bibliometric measures. These two types of empirical studies have given answers to the basic question since academia was threatened by different modes of practicing science. Keywords: research data; research material; secrecy; witholding; open science 1. Introduction Concern over the flow of data and material in research, which may be critical inputs for the success of a research project, is not new nor has it gone unaddressed (National Academies 2003). It is worth noting that not only secrecy but also data and material withholding are typical phenomena of commerce, whose logic is motivated by profit maximization. For that reason, refinements have been made when scientists affiliated with not-for-profit organizations conduct research commissioned by for-profit organizations, or when scientists’ employees aim at patenting and licensing their research results. Thus, a significant number of scholars (e.g. Dasgupta and David 1994, Eisenberg 2003, Mowery et al. 2004, Nelson 2004) shaped by Merton’s norms, have articulated their concern that the privatization of the scientific commons may undermine the traditional norms of academic openness and scientific advance itself by restricting access to data and material in research. As a resource is prone to underuse in a tragedy of the anticommons when multiple owners each have a right to exclude others from a scarce resource and no one has an effective privilege of use, Heller and Eisenberg (1998) warned à Email: victor.rodriguez@tno.nl ISSN 1463-6778 print/ISSN 1469-9915 online # 2009 Taylor & Francis DOI: 10.1080/14636770802670274 http://www.informaworld.com
  • 2. 68 V. Rodriguez that privatization of upstream biomedical research may create anticommons prop- erty. The anticommons hypothesis has been empirically tested with dedicated measures and surveys. In a bibliometric approach, Murray and Stern (2005) found evidence for a modest anticommons effect. As pointed out by them, the citation rate after the patent grant declines by between 9% and 17%. This decline becomes more pronounced with the number of years elapsed since the date of the patent grant. In particular, the decline is salient in articles authored by researchers with public sector affiliations. In the survey of Hansen et al. (2005) for members of the American Association for the Advancement of Science, industry reported higher rates of patented technology acquisitions than academia. Biosciences reported higher rates of patented technology acquisition than that of other fields, and had more protracted negotiations than anyDownloaded By: [Radboud University Nijmegen] At: 10:22 17 September 2009 other field. Acquisitions of technologies from industry were completed more quickly than those from academia. Industrial biosciences reported delay, change or abandonment of research at the highest rate. It seems that academia may have been less affected than industry by more restrictive and formal practices in the acquisition of patented technologies for research. Substantial research efforts have been devoted to gather statistical evidence to study secrecy, data and material withholding in research. Statistically, the existence of secrecy and its consequences have been quantified as perceived phenomena in surveys (e.g. Hagstrom 1974, Swazey et al. 1993, Anderson et al. 1994, Louis et al. 1995, Blumenthal et al. 1996, 1997, Walsh and Hong 2003, Blumenthal et al. 2006) or as a result of dedicated measures (e.g. Grushcow 2004). The withholding of data and material, its consequences and attitudes have been quantified as perceived phenomena in surveys (e.g. Ceci 1988, McCain 1991, Blumenthal et al. 1997, Campbell et al. 2000, 2002, Dalton 2000, Campbell and Bendavid 2003, Cho et al. 2003, Vogeli et al. 2006) or as a result of dedicated measures (e.g. McCain 1991, 1995). The aim of this article is to put into perspective critically the empirical findings on secrecy and withholding in research. In other words, by taking into account existing empirical literature, it is intended that a crucial question is answered: Is secrecy and withholding in research harmful or innocuous to science? The remainder of the article is organized as follows. To begin with, Merton and Ziman’s modes of science are referred to in section 2. Then, the issue of openness and secrecy is analyzed in section 3. The existence of secrecy in academic science has raised questions as to whether the repudiation of secrecy is an exclusive feature of modern academic science or whether openness really exists in post-modern academic science. Next, the problem of data and material withholding is studied in section 4. The reality of data and material withholding has also raised questions as to whether standard practices to facilitate such a sharing really exist in the academic community or whether putative standards are accepted by, and commonly applied to, all researchers. Finally, concluding remarks are made in section 5.
  • 3. New Genetics and Society 69 2. Merton and Ziman’s modes of science Academic scientific behavior has been characterized by the norms of communism, universalism, disinterestedness and organized skepticism (Merton 1942). It is generally believed that academicians who adhere to the Mertonian norms are ethically superior, and likewise those who follow the counter-norms are more likely to be involved in academic misconduct. Upon reviewing empirical research of ethical behavior in a university setting, Counelis (1993) underscored the university’s substantial information deficit as regards its own ethical behavior. In addition, Louis et al. (1995) found that a number of articles and research budgets were positively associated with adherence to the traditional norms, and that consulting, industry support, patenting and competitiveness were negativelyDownloaded By: [Radboud University Nijmegen] At: 10:22 17 September 2009 associated with adherence to the traditional norms. According to Rai (1999), the fact that individuals in a group may depart from group norms occasionally, does not mean that the norms do not exist or lack moral or psychological force. Rather, norms will persist so long as norm violations are relatively infrequent and are met with disapproval from the relevant community. Moreover, behavior that violates certain norms may be tolerated because it is perceived as being in the service of other norms. Regarding the central element of the Mertonian norms that promotes openness and sharing in academic research, there exists the view that scientific knowledge is ultimately a shared resource. Sharing and openness in academic research falls within the norm of communism and disinterestedness. Communism, sometimes called communalism as a euphemism, refers to the common ownership of scientific discoveries, according to which scientists give up intellectual property rights in exchange for recognition and esteem – the gift model. In other words, academic scientists must publish articles in academic journals or be doomed to oblivion. In this way, the results of science are public and free for anyone to use. The norm of communism is closely connected with the norm of disinterested- ness: academic scientists are expected to achieve their self-interest by serving the community interest. That is to say, disinterestedness represents scientists who seek new knowledge for its own sake rather than seeking to further their own interests. Academic scientists who do not benefit from royalties or equity derived from university patents can be considered disinterested. The essence of these two Mertonian norms includes sharing and openness (Ziman 2000). That is why withholding and secrecy in academic science is seen as immoral or as a form of misconduct (Bok 1982). As to the reward system of science, eponymy in science is the practice of naming a scientific discovery after its inventor. Nonetheless, Stigler (1980) pointed out that Laplace employed Fourier Transforms in print before Fourier published on the topic; that Lagrange presented Laplace Transforms before Laplace began his scientific career; that Poisson published the Cauchy distribution in 1824, 29 years before Cauchy touched on it in an incidental manner; and that Bienayme ´
  • 4. 70 V. Rodriguez stated and proved the Chebychev Inequality a decade before and in greater generality than Chebychev’s first work on the topic. For that matter, the Pythagorean theorem was known before Pythagoras; Gaussian distributions were not discovered by Gauss. The idea that credit does not align with discovery, Stigler reveals at the very end of his essay, was in fact first put forth by Merton. Residual norms of academic research may even have had some influence on the conduct of industry actors. Consider the example of Celera, a joint venture between the Institute for Genomic Research (a private, non-profit genetics laboratory) and Perkin-Elmer (a manufacturer of DNA-sequencing instruments). Celera refrains from claiming certain intellectual property rights in the human genome. More specifi- cally, Celera publicly releases all raw sequence data. Part of the reason for this may be that the value of intellectual property rights in DNA sequence data has been dimin-Downloaded By: [Radboud University Nijmegen] At: 10:22 17 September 2009 ished by the public consortium data release. In addition, the interest of Perkin- Elmer could be well served by having DNA sequence data disseminated widely so the company can create a demand for its sequencing machines (Wade 1998). From the beginning of the Cold War, academic science began deviating more and more from the long-established mode. This change was accelerated after the Bayh-Dole Act in the US in 1980. Most European countries, except for Sweden, mirrored the Bayh-Dole Act to allow universities to become the owner of patents for inventions made by their employees according to certain conditions. Univer- sities have the obligation to give a fair return to inventors through royalties or equity. In this manner, the privatization of academic science subverted the social order of academia and post-academic ethos emerged, the counter-Mertonian norms. Ziman (2000) gave the emerging system the name post-academic science. What is changing is the definition of science itself: the new regime shows that the idealized picture of academic science no longer holds. The term post-academic science suggests that science now fits neither the academic nor the industrial model. Nowadays, science may be characterized for being proprietary, local, authoritarian, commissioned and expert. Because of the Bayh-Dole Act and mirroring regimes elsewhere, technology transfer officers (TTOs) multiplied their presence among universities and govern- ment agencies. TTOs, selected by university authorities, are essentially mandated to protect the financial interests of the university, while researchers of university and government agency laboratories, selected by their peers, are ultimately man- dated to push the frontiers of knowledge forward. It is worth noting that these two different visions of what is the raison d’etre of universities have caused ˆ tension between the two communities. Sometimes these two missions might con- flict: some TTOs have complained in the 2007 Annual Meeting of Association of University Technology Managers (AUTM) that university promotions and tenures are mostly based on publication, which is why some professors prefer to publish their research in academic journals rather than as patents. Moreover, TTOs have argued about the selection of professors because it is done by peers on the basis of publication track and not on the basis of patents or royalties.
  • 5. New Genetics and Society 71 Commercialism in academia is not exclusive to current life science, biomedicine and biotechnology. For instance, the semiconductor industry has developed close ties with academia from the mid-1950s. In both domains, neither the quality of the education nor academic freedom appeared to suffer substantially; in fact, all were probably enhanced (Office of Technology Assessment 1984). Nevertheless, the research goals of life science, biomedicine and biotechnology are quite different from those of microelectronics. The prevention of human suffering and premature death from disease are ultimate research goals in life science, biomedicine and biotechnology. Just as a physician has a moral responsibility to do no harm, so does a researcher engaged in life science, biomedicine and biotechnology have the same responsibility (Rosenberg 1996). Deliberately withholding useful information or reagents is a violation of thisDownloaded By: [Radboud University Nijmegen] At: 10:22 17 September 2009 principle. If secrecy slows the progress of science, then human suffering may be prolonged and unnecessary death may occur. Although it is not the intention of scientists who withhold information to do harm deliberately, this harm is a logical consequence of such secrecy and data or material withholding. These are the reasons why scholarly studies have focused on academic research practices in life science, biomedicine and biotechnology. 3. Openness and secrecy in academia The concept of openness itself applies to various forms of communication practices in academic science. In this respect, openness refers to the academician’s willing- ness to disclose research findings, methods, instruments, data and materials. While academicians have been concerned to discourage secrecy with respect to the content, secrecy has consistently reigned in the refereeing process (Hull 1985). Openness in academe has been promoted by traditional norms, joint beliefs that openness promotes good science, freedom of speech, ability to share and publish information, international scientific networks and the rise of information and communication technologies. Secrecy, on the other hand, has been prompted by increasing commercial and military value of scientific information, growth in global economic and political competition, reduction in the delay between research and its applications, fiscal constraints at the university and scarcity of academic faculty vacancies (Chalk 1985). Publishing is critical in securing scientific credit and is vital to promotion, future funding and historical recognition. Verbal sharing, however, never provides closure in the same way as published collaboration. Verbal withholding is present in spoken exchanges about unpublished research, for example intentionally withholding information in conversations with doctoral students, postdoctoral fellows or peers, in seminars in or outside a department. Publishing withholding is present in the publishing process, for example, by omitting pertinent information from a manuscript submitted for publication to protect a scientific lead or commer- cial value; delaying publication for more than six months to honor an agreement
  • 6. 72 V. Rodriguez with a collaborator, protect the scientific lead or the priority of a graduate student, postdoctoral fellow or junior faculty member; and meeting the requirements of a non-industrial sponsor; allowing time for a patent application (Blumenthal et al. 2006). The privatization of scientific commons challenged the very existence of openness. In this sense, Grobstein (1985) raised these questions: can an open academic environment survive when it is generating commercial property of high value to investigators, universities, investors and companies? Can open scientific communication continue between academicians who are also techno- logists committed to private financial gain? The debate essentially revolves around who held the higher ethical ground: scien- tists who shared their findings in an effort to protect patients from harm, or scientistsDownloaded By: [Radboud University Nijmegen] At: 10:22 17 September 2009 who honored confidentiality agreements with their sponsors. Even when secrecy is a contractual obligation, researchers in life science, biomedicine and biotechnology may believe that the more pressing obligation is to prevent the potential harm to patients that could result from secrecy. It would be up to a court to decide whether public interest in disclosure outweighed a company’s claim of proprietary infor- mation (Shuchman 1998). Anecdotal evidence Scholarly studies have illustrated the practice of secrecy throughout the history of science. McMullin (1985) and Long (2001) found evidence of secrecy in pre- modern science, although pre-modern science was more based on technology rather than intellectual inquiry. Pre-modernists did not view the world as totally natural nor completely impersonal. In late antiquity (200 to 500 AD), secrecy was linked to esoteric and magic texts. Beginning in the thirteenth century, evi- dence of craft secrecy became abundant and signified the development of proprie- tary attitudes toward craft knowledge, processes and products. In the fifteenth century, doctrines inculcating secrecy and esotericism were disseminated widely through the medium of print, and for the authors of such doctrines, the values of openness and secrecy often existed side by side. Sixteenth-century writings on mining, metallurgy and the military arts made an open display of technological practices and of practitioner-authors in tandem with the growing value of novelty and priority that was beginning to clash with openness. With the emergence of modern science in the seventeenth century, the use of devices, instruments and machines to establish claims about the natural world generated the relationship between credit and disclosure. For instance, Galileo’s secrecy regarding telescope construction in order to make further astronomical discoveries and gain future credit was justified by his ambitions to move from his professorship at the University of Padua to a position at the Medici court in Florence as a mathematician and philosopher to the Grand Duke (Drake 1970, van Helden 1984, Winkler and van Helden 1992, Bagioli 2006). Like Galileo,
  • 7. New Genetics and Society 73 the academician Newton withheld a great deal of information about the prism he used in his early experiments on his theory of light and color (Schaffer 1989). As science continued to develop, it became more organized. The growing depen- dence of jobs and income for an increased number of researchers upon intellectual reputations in the nineteenth century both extended and intensified the reputational control of scientific work and integrated reputational goals and standards with employers’ goals and authority structures in universities (Whitley 1984). In the 1950s, the academicians Watson and Crick kept the ongoing research on the struc- ture of DNA temporarily secret, especially from the competitor Linus Pauling, in order to be the first to gain the disclosure priority race and to achieve reputational authority (Watson 2001). Secrecy regarded as a restraint from publishing or presenting findings can alsoDownloaded By: [Radboud University Nijmegen] At: 10:22 17 September 2009 arise from confidentiality agreements signed between academicians and industry, as shown notably in the examples provided by King (1996) and Shuchman (1998). In 1995, Dr Betty Dong’s article showing that cheaper medications are virtually interchangeable with the expensive drugs owned by the company funding the study was pulled out from the Journal of the American Medical Associ- ation because the drug company, after carrying out a campaign to discredit her and suppress her conclusions, threatened to sue her. Her university did not want to defend her in court, but eventually the article was published in 1997. The Trypanosoma brucei consortium rejected a request from Georg Cross of Rockefeller University to publish an annotation of part of the genome because of unfinished work, credit and data piracy. The same issue arose in the Plasmodium falciparum consortium when Lou Miller of the National Institutes of Health offered to publish a preliminary annotation that he had prepared with Eugene Koonin of the National Centre for Biotechnology Information. In this respect, it was argued that if scientists who are not members of the consortium publish preliminary annotations based on raw sequencing data made available voluntarily by sequencing centers, then the final complete sequence may never be published (Macilwain 2000). In 1996, Dr Nancy Olivieri was not authorized to present new findings in a conference by the company funding the clinical trials in which she was the principal investigator. Eventually she presented her findings and later published them, but her university declined to defend her against the company’s threats. In 1997, Dr David Kern was asked to not submit an abstract for presentation by the company where he had been practicing labor medicine as a consultant because of a confidentiality agreement (Shuchman 1998). Statistical evidence Statistically, the existence of secrecy and its consequences have been recognized as perceived phenomena in surveys (e.g. Hagstrom 1974, Swazey et al. 1993, Anderson et al. 1994, Louis et al. 1995, Blumenthal et al. 1996, 1997, Walsh
  • 8. 74 V. Rodriguez and Hong 2003) or as a result of dedicated measures (e.g. Grushcow 2004). In both approaches, the predictors are always factual variables and not perceptions. None- theless, in the survey approach, the existence of secrecy and its consequences are reported by respondents as answers to questionnaires. While in the bibliometric approach, direct measures from records of conferences or publications evidence the existence of secrecy and its consequences. These two complementary methodological approaches have provided significant statistical findings detailed as follows. Secrecy has been studied through surveys as anticipation, secrecy, publishing withholding, or research misconduct as shown in Table 1.Downloaded By: [Radboud University Nijmegen] At: 10:22 17 September 2009 Table 1. Findings from survey evidence on secrecy. Empirics Findings Anticipation As a result of surveying subjects, Hagstrom (1974) observed that the majority of researchers in experimental biology, mathematics and physics had been anticipated by another scientist in the publication of a discovery at least once in their careers, but a minority of researchers were concerned about being anticipated in their current work. Researchers were likely to be anticipated if they published much and had their publications cited often. Researchers were likely to be concerned about being anticipated if they were young and if they had been anticipated previously. Being in competitive situations induced scientists to shift specialties and to be secretive about their research, although those working with collaborators were less secretive. Secrecy In a follow-up survey of Walsh and Hong (2003), secrecy has increased after 30 years and mostly in experimental biology. Secrecy was strongly predicted by scientific competition and industry funding. Patenting had no effect on secrecy. Having industry collaborators was associated with less secrecy. Commercial activity had mixed effect on secrecy. Companies appreciated timeliness and the customization of information more than exclusivity, which was why they were willing to tolerate or encourage their academic collaborator’s participation in the shared conversation of a scientific field. Industry funding was often associated with a university laboratory as a subcontractor and might have produced secrecy. The last hypothesis was confirmed by Blumenthal et al. (1996): faculty members with industrial support in life sciences were significantly more likely than those without it to report that trade secrets had resulted from their work. Publishing A survey of Blumenthal et al. (1997) showed that publications of research results withholding have been delayed to allow time for patent applications, to protect the proprietary value of research results by means other than patenting, to protect the scientific lead, to slow down dissemination of undesired results, to allow time to negotiate license agreements and to resolve disputes over intellectual property. As to predictors, male researchers and higher academic ranks were associated with publication. More recently, another survey of Blumenthal et al. (2006) has shown that verbal and publishing withholding was more common in genetics than in other life sciences, took multiple forms and was influenced by a variety of characteristics of investigators and their training and varies by research field. (Continued )
  • 9. New Genetics and Society 75 Table 1. Continued. Empirics Findings Misconduct Among other acts of misconduct, Swazey et al. (1993) noted the failure of presenting data that contradict the previous findings of professor and students. They found that professors were aware of cases where data that would have contradicted an investigator’s own previous research had not been presented. Although doctoral candidates reportedly engaged in questionable research practices at somewhat lower frequency than professors, the data indicated that substantial numbers of both doctoral candidates and professors had observed such practices by doctoral candidates. There were disciplinary differences among doctoral candidates, but not among professors’ responses. More doctoral candidates in microbiology than in other fields reported direct knowledge of suchDownloaded By: [Radboud University Nijmegen] At: 10:22 17 September 2009 practices by faculty, whereas those in chemistry and microbiology reported highest levels of such practices by their peers. In the same vein, Louis et al. (1995) found that research misconduct of professor and student was predicted only by competitiveness and preferential treatment. Anderson et al. (1994) observed that doctoral students who benefit from advisors’ feedback were less likely to witness research misconduct. Nonetheless, the longer a doctoral student was in the program, the more likely he or she was to witness research misconduct. There was little evidence of departmental structure or climate effects on research misconduct. Although the literature has focused on misconduct in biomedicine, there were no disciplinary differences to note in research misconduct. Following a bibliometric approach, Grushcow (2004) evaluated scientists’ secrecy by measuring the delay between a scientist’s presentation of data at a scien- tific meeting and the publication of that work in a peer-review journal. A short time gap before publication thereby indicated that the scientist maintained data in secret, withholding the meeting presentation until the work was substantially complete. Conversely, a long gap before publication indicated that the scientist readily shared data that was far from complete, unveiling data at the meeting that was years from being ready for publication. The statistical results showed a shorter time delay between conference presentation and formal publication for academi- cians who sought patents than the time delay for academicians who did not seek patents. Grushcow also found that those academicians not seeking patents became more secretive during the Bayh-Dole Act era. 4. Sharing and withholding data and material Following Weinberg (1993), there are two types of data in life sciences, each deriving from a distinct approach to doing research: survey and manipulation. Examples of survey data include clinical trials of drug regimens, DNA sequencing, epidemiological studies, ecological surveys and gathering of x-ray crystallographic data. Illustrations of manipulative data are projects designed to clone a gene,
  • 10. 76 V. Rodriguez develop a genetically complex organismic strain or purify a protein and examine its mechanism of action. As to research materials, there are two types: standard organisms and reagents. Examples of standard organisms include mice, rats, rabbits, chickens, frogs and so forth. Illustrations of reagents are: a purified protein, a mouse strain, a monoclonal antibody, a DNA clone or a synthesized chemical that is created as a product of experimental work. Sharing data and material involves two parties either in the initial request or later in the transfer. In the request, the two parties are the owner or holder, and the petitioner or requester. In the transfer, the two parties are the supplier or provider, and the receiver or recipient. Data and materials can be kept secret or disclosed in an article or patent by researchers affiliated to for-profit or not-for- profit organizations.Downloaded By: [Radboud University Nijmegen] At: 10:22 17 September 2009 If the analysis of academic science as a fine balance between cooperation and competition is accurate, science can be characterized as cumulative knowledge. The communal character of science is manifested in recognition by scientists of their dependence upon a cumulative heritage. Newton’s aphorism, that says “If I have seen farther it is by standing on the shoulder of giants”, reflects this sense of indebtedness to predecessors. Even Kuhn (1996), who argues that scientific revolutions are non-cumulative transitions between incommensurable worldviews, stresses that normal science is cumulative. Scientists cooperate in that they use each other’s work in their own research. In science, therefore, use is the surest sign of worth, and the sincerest compliment is to incorporate a colleague’s findings into one’s own research through citation. In this respect, Hedrik (1988) has catalogued the following reasons for sharing data: reinforcement of open scientific inquiry; verification, refutation or refinement of original results; replications with multiple datasets; explorations of new questions; creation of new datasets through data file linkages; encouragement of multiple perspectives; reductions in the incidence of faked and inaccurate results; development of knowledge about analytic techniques and research; provision of resources for training; reduction of respondent burden. Meanwhile Ceci and Walker (1983) have referred to the following reasons for refusal to share data: administrative reasons (e.g. security reasons for non- release; financial costs of duplication, dataset inadequacies, poor communication); ethical reasons (e.g. concern about the qualification of data requesters, violations of confidentiality agreements with human subjects or sponsors); research reasons (e.g. fear that procedural or computational errors will be discovered; fear that divulging unpublished data could result in research by others that pre-empts the investigators’ subsequent planned publications). Other reasons are: time constraints and the lack of rewards (Stanley and Stanley 1988). Rapid changes in the life sciences have led to withholding, contention about the responsibilities to share them, lack of enforcement of standards for sharing, differ- ential treatment for sharing, uncertainties about the application of the principle to various types of data and material, and conflicts with legislation that encourages
  • 11. New Genetics and Society 77 commercialization of the results of publicly funded research. A review of the litera- ture reveals that secrecy has been studied through anecdotal evidence, surveys and bibliometric analyses. Anecdotal evidence Scientific literature has exemplified cases of the withholding of data and material. Controversies over withholding, particularly in biomedical research, are increas- ingly visible in the news media. Kamin reported a refusal of access to data in studies that were at odds with the scientific literature on the genetic basis of schizo- phrenia. Access to data was first refused due to subjects’ identities and then later because of unfinished work. These explanations were offered by the AmericanDownloaded By: [Radboud University Nijmegen] At: 10:22 17 September 2009 Cancer Society when a committee of 10 senior scientists requested access to the data of the Million-Person Study (Sterling 1988). In another case, Shyh-Ching Lo of the Armed Forces Institute of Pathology pub- lished a paper in the Journal of the American Society of Tropical Medicine and Hygiene, in which he claimed to have discovered a new virus-like infectious agent in AIDS patients, but he refused to give samples to other researchers, even those working for public laboratories. The director of the Armed Forces Institute of Pathology said that Lo had applied for patents and that the laboratory would not share the reagents with researchers unless they entered into collaborative research agreements with the institute (Booth 1989). The drive for personal recog- nition and an unwillingness to share data and material were contentious issues in AIDS research (Barnes 1987). Statistical evidence The existence of withholding data and material, consequences and attitudes have been quantified as perceived phenomena in surveys (e.g. Ceci 1988, McCain 1991, Blumenthal et al. 1997, Campbell et al. 2000, 2002) or as a result of dedicated measures (e.g. McCain 1991, 1995). In both approaches, the predictors are always factual variables and not perceptions. Nonetheless, in the survey approach, the existence of withholding and its consequences are reported by the respondents as answers to the questionnaire. While in the bibliometric approach, direct measures use objective sources, such as records of conferences or publi- cations, which are able to evidence the phenomenon of withholding and its consequences. These two complementary methodological approaches have pro- vided significant statistical findings detailed as follows. Withholding has been studied through surveys as shown in Table 2. Following a bibliometric approach, McCain (1991) obtained statistical evidence of data and material sharing by looking at personal credits in the method and materials sections, and acknowledgement notes. Moreover, McCain (1995) has also documented the existence of policy statements of natural science, medical
  • 12. 78 V. Rodriguez Table 2. Findings from survey evidence on refusal to share. Empirics Findings Attitude In an attitude survey, McCain (1991) posed questions on general attitudes, expectations and experiences as requesters and providers of research materials, the development or use of novel techniques and perceptions of the level of competition and extent of secrecy in particular specialties. Nelkin (1982) has documented the tendency among some researchers who receive public funds to view the products of their research as their private intellectual property. Academicians In a survey of Blumenthal et al. (1997), refusing to share research results or refusal to share materials was carried out to protect the scientific lead, the university or researcher financial interest or because of a previous formal or informalDownloaded By: [Radboud University Nijmegen] At: 10:22 17 September 2009 agreement with a company, or because of the limited supply or high costs of the material requested. As to predictors, there was no significant association between the refusal to share research results or materials and the respondents’ gender or academic rank. According to the survey of Ceci (1988), whenever respondents were permitted by any contract to comply with colleagues’ requests for their raw data, they professed to do so in all research fields. The overwhelming majority of respondents reported that they routinely honored requests by colleagues for their pre-published findings or data. The majority of respondents claimed that their colleagues were not prone to sharing data, even when it was obtained with the benefit of public funds, when asked to describe their experiences trying to obtain their colleagues’ data or to comment on their colleagues’ attitude regarding data sharing. The reason for the reluctance to share data varied across fields. For instance, the main reason in biotechnology was financial: the fear of losing patent rights or obtaining future grants. In social sciences, the fear was one of being pre-empted in the publication of the findings. The survey of Campbell et al. (2000) studied frequency and predictors of denial of data and reagents in academic biomedicine and they found that young researchers, researchers without medical degrees, those who publish a lot, those who are full time researchers or those who applied, obtained or licensed a patent, investigators seeking patents, and professors who had been a member of a review panel, editor of a journal or a scientific consultant to government are those most likely to be denied access to biomedical data and reagents. It also noted that researchers who withhold data gain a reputation for this and experience more difficulty themselves in obtaining data from others (Dalton 2000). In another survey, Campbell et al. (2002) found that data withholding occurs in academic genetics and this affects essential scientific activities such as the ability to confirm published results. Lack of resources and issues of scientific priority might have played a role in scientists’ decisions to withhold data, material and information from other academic geneticists. However, other life scientists were less likely to report that withholding information had a negative impact on their own research as well as their field of research. (Continued )
  • 13. New Genetics and Society 79 Table 2. Continued. Empirics Findings In academic biomedicine, Walsh et al. (2005) found that when non- compliance with transfer requests of data and material exists, it is associated with some traits of the petitioner (scientific competition, drug) and supplier such as commercial orientation, scientific competition, publication activity and request burden. This has an impact on the petitioner’s research such as research delays greater than one month or abandonment of the project. It seems that non-compliance appears to be growing. Trainees refusal to As to data and material withholding, its predictors and effects for academic share trainees in life sciences, computer science and chemical engineering, Vogeli et al. (2006) found that when withholding (denial of request) occurred, itDownloaded By: [Radboud University Nijmegen] At: 10:22 17 September 2009 was associated with some aspects of the petitioner (industry support, high competition research groups, or European racial origins) and supplier (scientific competition) and had negative consequences for many trainees on: the progress of their own research, the quality of their relationships with other academic scientists, the level of communication within their research group, the quality of their education, the rate of discovery in their own research group) and their research (delay of more than six months in their research, inability to confirm others’ published research, abandonment of a promising line of research, significant delay in their publication, and inability to publish the research results). Withholding data may contribute to delays in research, inefficient training programs and foster a culture of mistrust and isolation in academia. It has been recommended that faculties should assist trainees to buffer the negative impact of withholding. Reducing competition for recognition or priority within research groups or redefining the role of industry support in academia might improve trainees’ access to research resources as well as courses in research ethics. Laboratory directors The survey of Cho et al. (2003) has shown that information sharing between clinical genetic laboratories, on average, had decreased. Laboratory directors may feel more strongly than geneticists that patents have a negative effect on research. Technology transfer In another survey, Campbell and Bendavid (2003) have investigated the officers attitudes of TTOs; individuals working for universities and laboratories that manage transfer of information from their employer institution. The study demonstrated that TTOs are more likely to withhold information until after publication and that TTOs feel scientists should be more careful when sharing information to protect publication interests. Most TTOs work at institutions that do not have policies relating to information sharing. Finally, TTOs think that publication may hurt a university’s commercial interests, since the information is dispersed among competing researchers and the public at large. and engineering journals concerning deposition of sequence or structure data in a databank before publication, deposition or sharing research materials upon request, and the availability of supplementary publication services by looking at the journal scope statement and instructions to authors.
  • 14. 80 V. Rodriguez 5. Concluding remarks To understand how secrecy and withholding in research have affected academic science, empirical studies have been placed in the wider context of Mertonian underpinnings of the anticommons threat. In the beginning, it was the fear that privatized research practices in academia would undermine the progress of research. Such was the background of the scholarly studies reviewed here. Since the Bayh-Dole Act and mirroring regimes elsewhere, the anticommons threat has had a strange progression in scholarly studies. At first, it was simply issued, apparently in the profoundly held belief that anecdotal evidence would be enough to accept the anticommons hypothesis. The turning point in testing the effects of secrecy and withholding of data and materialDownloaded By: [Radboud University Nijmegen] At: 10:22 17 September 2009 on scientific research was marked by statistical studies based on surveys and bibliometric measures. In particular, bibliometric approaches have marked a radical departure not only from the anecdotal evidence, but also from the attitudinal approach of surveys. Empiricists used statistical evidence in the survey of percep- tions and dedicated measures through bibliometrics. These two types of empirical studies have given answers to the basic questions that had gone unasked since academia was threatened by different modes of practicing science. Repudiation of secrecy If openness is accepted as a norm in academic science, secrecy raises some con- siderations. From a Mertonian perspective based on communism and disinterested- ness, modern academic scientists have repudiated secrecy against the doctrine of esotericism of pre-modern science and the doctrine of commercialism of post- modern science. Even in the middle of World War II, the journal Nature (1941) published a declaration of scientific principles that included intellectual freedom and unrestricted international exchange. During McCarthyism, 17 American Nobel laureates, responding in 1959 to a letter from Senator Thomas Henning, agreed (with one exception) that the free exchange of information was the life- blood of scientific progress, and that restrictions of this flow were destructive (Science 1959). Because secrecy limits feedback and restricts the flow of knowledge, it hampers the scientist’s capacity to correct estimates according to new information, to see connections and to take unexpected leaps of thought. Secrecy too is expensive in that it fosters needless duplication of efforts, postpones the discovery of errors and leaves mediocre work without criticism and peer review (Bok 1982). Nonethe- less, even under the Mertonian framework, some motives for secrecy might not constitute unethical conduct in academic science. Examples of those motives are military secrets (for projects under government sponsorship), trade secrets (for industry-funded projects), matters pertaining to privacy (of human subjects in experimentation, for instance), scientific competition (with limited resources), frontier knowledge (with similar projects), highly specialized research fields
  • 15. New Genetics and Society 81 (with restricted mobility for researchers), ongoing research (because of the fear of being anticipated in a priority race), unfinished work (for scientific creativity or originality) and so forth. In the era of the Bayh-Dole Act or mirroring regimes, academic secrecy is toler- ated for additional reasons, such as university patent prosecution, but not endorsed by the academic community at large. An inventor seeking worldwide patent rights cannot divulge the invention publicly before applying for a patent, but data can be published once an application is filed without sacrificing patent rights. Secrecy is necessary only until the application is filed. Having this in mind, Cook-Deegan and McCormack (2001) pointed out emphatically that what is missing is the norm of disclosure immediately or soon after applying for a patent.Downloaded By: [Radboud University Nijmegen] At: 10:22 17 September 2009 Sharing data and material Major research universities, such as the Massachusetts Institute of Technology, Harvard University and Stanford University, have sought to maintain certain aspects of traditional scientific norms even while embracing the development- promoting aspects of intellectual property rights. The approach used attempts to maintain the free flow of information required by communalism even while it recognizes the concern that, in certain situations, product development will require exclusivity (Rai 1999). According to Taylor (2007), research sharing should be recognized as practically indispensable. Several initiates offer evidence of acceptance of the principle of data and material sharing in various scientific disciplines. In addition, some scientific journals and funding agencies encourage authors to submit raw data or support data sharing. As to DNA sequencing, publicly funded, large-scale, high-throughput sequen- cing centers agreed in Hamilton, Bermuda, in 1996, not to patent any of the human genome sequences that they determined, but instead to deposit them immediately in a public database, where they would be freely available to all. According to Ashburner (2001), the Bermuda Agreement had three essential elements. First, such knowledge remained public to simply hold, to ponder, to study and analyze or to exploit it. Secondly, such public access would foster pro- gress in sequencing. Thirdly, openness would allow gene-centric and holistic approaches. As a response to the initiative challenging the withholding of data and material, researchers’ behavior while carrying out scientific work and such like, and their recommendations for sharing data and materials have been exten- sively examined (e.g. Caveman 2001, Kornberg 2000, 2003, Marshall 2002a, 2002b, Patrinos and Drell 2002, Theologis and Davis 2004). In complementary DNA microarrays, several examples have been provided, such as microarray data sharing from private, local databases, to web-accessible published paper supplements, institute-based or project-based databases, and to large public and proprietary commercial databases (e.g. Becker 2001, Geschwind
  • 16. 82 V. Rodriguez 2001, Mirnics 2001). The analyses for each class of sharing initiatives showed that all of those examples have potential value but most of them could suffer from poor data input, changing technologies, undocumented experiments and lack of database maintenance. In cognitive sciences, journals and professional associations (e.g. the Journal of Cognitive Neuroscience, Institute of Medicine of the National Academy of Sciences) have requested or recommended the deposit of experimental data in repositories, such as the National Functional Magnetic Resonance Imaging Data Centre, National Neural Circuitry Database, and so forth (Aldhous 2000). These initiatives have caused negative reactions based on technical and cultural grounds (see for instance the analysis of Chicurel 2000, Koslow 2000, 2002, Nature Neuro- science 2000, 2003, Fox and Lancaster 2002, Toga 2002, Van Horn and GazzanigaDownloaded By: [Radboud University Nijmegen] At: 10:22 17 September 2009 2002, Gardner et al. 2003, Insel et al. 2003, van Horn et al. 2004). In environmental sciences, the journal Nature (2001) has recommended that funding agencies devote more resources to a long-term maintenance of open archives of geoscientific data and to the tools with which to exploit them. The Inter- national Geosphere-Biosphere program’s core project on past global changes and the World Data Center for Paleoclimatology have provided publicly available paleoen- vironmental data archives among other facilities (Alverson and Eakin 2001). The National Science Foundation asked that all raw data generated in each climate- related project must be stored together with the meta-information in the international repository (Dittert et al. 2001). As to the escalatory policy for handling complaints based on non-compliance, Nicholas Cozzarelli, editor-in-chief of the Proceedings of the National Academy of Sciences, commented that if an author does not provide requested material after receiving a letter from the journal, it will threaten not to publish future papers by that author and any co-authors. Laurie Goodman, executive director of the journal Genome Research, indicated that the journal would remove a paper from its online version and insert a note that the paper had been removed if an author failed to comply with the journal’s policy for sharing materials or data. Philip Campbell, editor-in-chief of the journal Nature, expressed the view that editors were acting in isolation in trying to impose sanctions and that knowing what sanctions would be vigorously supported if the editor contacted a non- complying author’s research institution or funding agency beforehand might have made it easier to enforce compliance in the first place (National Academies 2003). In the absence of institutional sanctions, the most powerful motivations are rewards and punishments from peers (Cohen 1995). Finally, the National Academies (2003) established the uniform principle for sharing publication-related data and materials expeditiously, which was articulated in five principles. The first three principles deal with data and the last two principles deal with materials. Based on the uniform principle, 10 recommendations were provided, such as financial resources for dissemination, referees’ and journal’s roles, acknowl- edgements for the use of data and material, and the responsibility of the employers.
  • 17. New Genetics and Society 83 Acknowledgements I would like to express my gratitude to the anonymous reviewers for their remarkable observations. I acknowledge TNO Innovation Policy Group for supporting this study under project No. KIP-2008 031.12974/01.01. Personal thanks go to Nicholas Neill-Fraser for editing the final manuscript. References Aldhous, P., 2000. Prospect of data sharing gives brain mappers a headache. Nature, 406, 445–446. Alverson, K. and Eakin, C., 2001. Making sure that the world’s paleodata do not get buried. Nature, 412, 269. Anderson, M., Seashore, K., and Earle, J., 1994. Disciplinary and departmental effects on observation of faculty and graduate student misconduct. Journal of Higher Education, 65, 331–350.Downloaded By: [Radboud University Nijmegen] At: 10:22 17 September 2009 Ashburner, M., 2001. Privatising our genes? Open Democracy [online]. Available from: http:// www.opendemocracy.net/content/articles/PDF/407.pdf [Accessed 6 January 2009]. Bagioli, M., 2006. Galileo’s instruments of credit: telescopes, images, secrecy.. Chicago, IL: Univer- sity of Chicago Press. Barnes, D., 1987. Meeting on AIDS drugs turns into open forum. Science, 237, 1287–1288. Becker, K., 2001. The sharing of cDNA microarray data. Nature Reviews Neuroscience, 2, 438–440. Blumenthal, D., et al., 1996. Participation of life-science faculty in research relationships with industry. New England Journal of Medicine, 335, 1734–1739. Blumenthal, D., et al., 1997. Withholding research results in academic life sciences. Journal of the American Medical Association, 277, 1224–1228. Blumenthal, D., et al., 2006. Data witholding in genetics and the other life sciences: prevalences and predictors. Academic Medicine, 81, 137–145. Bok, S., 1982. Secrecy and openness in science: ethical considerations. Science, Technology & Human Values, 7, 32–41. Booth, W., 1989. AIDS researchers upset by refusal to share probes on mysterious microbe. Science, 244, 416. Campbell, E. and Bendavid, E., 2003. Data-sharing and data-withholding in genetics and the life sciences: results of a national survey of technology transfer officers. Journal of Health Care Law and Policy, 6, 241–255. Campbell, E., et al., 2000. Data withholding in academic medicine: characteristics of faculty denied access to research results and biomaterials. Research Policy, 29, 303–312. Campbell, E., et al., 2002. Data withholding in academic genetics: evidence from a national survey. Journal of the American Medical Association, 287, 473–480. Caveman, 2001. Send me all of your reagents and ideas: we want to work on the same experiments. Journal of Cell Science, 114, 1037–1038. Ceci, S., 1988. Scientists’ attitudes toward data sharing. Science, Technology & Human Values, 13, 45–52. Ceci, S. and Walker, E., 1983. Private archives and public needs. American Psychologist, 38, 414–423. Chalk, R., 1985. Overview: AAAS project on secrecy and openness in science and technology. Science, Technology & Human Values, 10, 28–35. Chicurel, M., 2000. Databasing the brain. Nature, 406, 822–825. Cho, M., et al., 2003. Effects of patents and licenses on the provision of clinical genetic testing services. Journal of Molecular Diagnostics, 5, 3–8. Cohen, J., 1995. Share and share alike isn’t always the rule in science. Science, 268, 1715–1718. Cook-Deegan, R. and McCormack, S., 2001. Intellectual property: patents, secrecy, and DNA. Science, 293, 217.
  • 18. 84 V. Rodriguez Counelis, J., 1993. Toward empirical studies on university ethics: a new role for institutional research. Journal of Higher Education, 64, 74–92. Dalton, R., 2000. Young, worldly and unhelpful all miss out on data sharing. Nature, 404, 6. Dasgupta, P. and David, P., 1994. Toward a new economics of science. Research Policy, 23, 487–521. Dittert, N., Diepenbroek, M., and Grobe, H., 2001. Scientific data must be made available to all. Nature, 414, 393. Dong, B., et al., 1997. Bioequivalence of generic and brand-name levothyroxine products in the treat- ment of hypothyroidism. Journal of the American Medical Association, 277, 1205–1213. Drake, S., 1970. Galileo studies. Ann Arbor, MI: University of Michigan Press. Eisenberg, R., 2003. Patent swords and shields. Science, 299, 1018–1019. Fox, P. and Lancaster, J., 2002. Mapping context and content: the BarinMap model. Nature Reviews Neuroscience, 3, 319. Gardner, D., et al., 2003. Towards effective and rewarding data sharing. Neuroinformatics, 1, 289–295. Geschwind, D., 2001. Sharing gene expression data: an array of options. Nature Reviews Neuro-Downloaded By: [Radboud University Nijmegen] At: 10:22 17 September 2009 science, 2, 435–438. Grobstein, C., 1985. Biotechnology and open university science. Science, Technology & Human Values, 10, 55–63. Grushcow, J., 2004. Measuring secrecy: a cost of the patent system revealed. Journal of Legal Studies, 33, 59–84. Hagstrom, W., 1974. Competition in science. American Sociological Review, 39, 1–18. Hansen, S., Brewster, A., and Asher, J., 2005. Intellectual property in the AAAS scientific community. Washington, DC: American Association for the Advancement of Science. Hedrik, T., 1988. Justifications for the sharing of social science data. Law and Human Behavior, 12, 163–171. Heller, R. and Eisenberg, R., 1998. Can patents deter innovation? The anticommons in biomedical research. Science, 280, 698–701. Hull, D., 1985. Openness and secrecy in science: their origins and limitations. Science, Technology & Human Values, 10, 4–13. Insel, T., et al., 2003. Data-sharing in an information age. Public Library of Science Biology, 1, 9–11. King, R., 1996. Bitter pill: how a drug company paid for university study, then undermined it. Wall Street Journal, 25 April, pp. A1, A6. Kornberg, A., 2000. Ten commandments: lessons from the enzymology of DNA replication. Journal of Bacteriology, 182, 3613–3618. Kornberg, A., 2003. Ten commandments of enzymology, amended. Trends in Biochemical Sciences, 28, 515–517. Koslow, S., 2000. Should the neuroscience community make a paradigm shift to sharing primary data? Nature Neuroscience, 3, 863–865. Koslow, S., 2002. Sharing primary data: a threat or asset to discovery? Nature Reviews Neuroscience, 3, 311–313. Kuhn, T., 1996. The structure of scientific revolutions. Chicago, IL: University of Chicago Press. Long, P., 2001. Openness, secrecy, authorship: technical arts and the culture of knowledge from Antiquity to the Renaissance. Baltimore, MD: Johns Hopkins University Press. Louis, K., Anderson, M., and Rosenberg, L., 1995. Academic misconduct and values: the depart- ment’s influence. Review of Higher Education, 18, 393–422. Macilwain, C., 2000. Biologists challenge sequencers on parasite genome publication. Nature, 405, 601–602. Marshall, E., 2002a. DNA sequencer protests being scooped with his own data. Science, 295, 1206–1207. Marshall, E., 2002b. Clear-cut publication rules prove elusive. Science, 295, 1625.
  • 19. New Genetics and Society 85 McCain, K., 1991. Communication, competition, and secrecy: the production and dissemination of research-related information in genetics. Science, Technology & Human Values, 16, 491–516. McCain, K., 1995. Mandating sharing: journal policies in the natural sciences. Science Communi- cation, 16, 403–431. McMullin, E., 1985. Openness and secrecy in science: some notes on early history. Science, Technology & Human Values, 10, 14–23. Merton, R., 1942. Science and technology in a democratic order. Journal of Legal and Political Science, 1, 115–126. Mirnics, K., 2001. Microarrays in brain research: the good, the bad and the ugly. Nature Reviews Neuroscience, 2, 444–447. Mowery, D., et al., 2004. Ivory tower and industrial innovation: university-industry technology transfer before and after the Bayh-Dole Act. Palo Alto, CA: Stanford University Press. Murray, F. and Stern, S., 2005. Do formal intellectual property rights hinder the free flow of scientific knowledge? An empirical test of the anti-commons hypothesis. NBER WorkingDownloaded By: [Radboud University Nijmegen] At: 10:22 17 September 2009 Paper Series 11465. National Academies, 2003. Sharing publication-related data and materials: responsibilities of authorship in the life sciences. Washington, DC: National Academies Press. Nature, 1941. The Commonwealth of science. Nature, 148, 393. Nature, 2001. Make the most of paleodata. Nature, 411, 1. Nature Neuroscience, 2000. A debate over fMRI data sharing. Nature Neuroscience, 3, 845–846. Nature Neuroscience, 2003. Neuroscience in the post-genome era. Nature Neuroscience, 6, 1. Nelkin, D., 1982. Intellectual property: the control of scientific information. Science, 216, 704–708. Nelson, R., 2004. The market economy and the scientific commons. Research Policy, 33, 455–471. Office of Technology Assessment, 1984. Commercial biotechnology: an international analysis [online]. Washington, DC: US Congress, Office of Technology Assessment, OTA-BA-218. Avail- able from: http://www.princeton.edu/ota/disk3/1984/8407_n.html [Accessed 6 January 2009]. Patrinos, A. and Drell, D., 2002. The times they are a-changin’. Nature, 417, 589–590. Rai, A., 1999. Regulating scientific research: intellectual property rights and the norms of science. Northwestern University Law Review, 94, 77–152. Rosenberg, S., 1996. Secrecy in medical research. New England Journal of Medicine, 334, 392–394. Schaffer, S., 1989. Glass works: Newton’s prism and the uses of experiment. D. Gooding, T. Pinch and S. Schaffer, eds. The uses of experiment. Cambridge: Cambridge University Press, 67–104. Science, 1959. Views on secrecy by American Nobel prize-winners. Science, 130, 85–86. Shuchman, M., 1998. Secrecy in science: the flock worker’s lung investigation. Annals of Internal Medicine, 129, 341–344. Stanley, B. and Stanley, M., 1988. Data sharing: the primary researcher’s perspective. Law and Human Behavior, 12, 173–180. Sterling, T., 1988. Analysis and reanalysis of shared scientific data. Annals of the American Academy of Political and Social Science, 495, 49–60. Stigler, S., 1980. Stigler’s law of eponymy. Transactions of the New York Academy of Science. Series II, vol. 39. 147–157. Swazey, J., Anderson, M., and Louis, K., 1993. Ethical problems in academic research. American Scientist, 81, 542–553. Taylor, P., 2007. Research sharing, ethics and public benefit. Nature Biotechnology, 25, 398–401. Theologis, A. and Davis, R., 2004. To give or not to give? That is the question. Plant Physiology, 135, 4–9. Toga, A., 2002. Neuroimage databases: the good, the bad and the ugly. Nature Reviews Neuroscience, 3, 302–309.
  • 20. 86 V. Rodriguez ` Van Helden, A., 1984. Galileo and the telescope. P. Galluzzi, ed. Novita celesti e crisi del sapere. Florence: Giunti, 149–158. Van Horn, J. and Gazzaniga, M., 2002. Databasing fMRI studies: towards a “discovery science” of brain function. Nature Reviews Neuroscience, 3, 314–318. Van Horn, J., et al., 2004. Sharing neuroimaging studies of human cognition. Nature Neuroscience, 7, 473–481. Vogeli, C., et al., 2006. Data withholding and the next generation of scientists: results of a national survey. Academic Medicine, 81, 128–136. Wade, N., 1998. Scientist’s plan: map all DNA within 3 years. New York Times, 10 May, p. A1. Walsh, J., Cho, C., and Cohen, W., 2005. View from the bench: patents and material transfer. Science, 309, 2002–2003. Walsh, P. and Hong, W., 2003. Secrecy is increasing in step with competition. Nature, 422, 801–802. Watson, J., 2001. The double helix: a personal account of the discovery of the structure of DNA. New York: Touchstone.Downloaded By: [Radboud University Nijmegen] At: 10:22 17 September 2009 Weinberg, R., 1993. Reflections on the current state of data and reagent exchange among biomedical researchers. In: Panel on Scientific Responsibility and the Conduct of Research, National Academy of Sciences, National Academy of Engineering, Institute of Medicine, eds. National academies, responsible science: ensuring the integrity of the research process. Washington, DC: National Academy Press, 66–78. Whitley, R., 1984. The intellectual and social organization of the sciences. Oxford: Clarendon Press. Winkler, M. and van Helden, A., 1992. Representing the Heavens: Galileo and visual astronomy. Isis, 83, 214–216. Ziman, J., 2000. Real science: what it is and what it means. Cambridge: Cambridge University Press.

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