Download icon

Point of View: Motivating participation in open science by examining researcher incentives

  1. Sarah E Ali-Khan
  2. Liam W Harris
  3. E Richard Gold Is a corresponding author
  1. McGill University, Canada
Feature Article
Cited
0
Views
871
Comments
0
Cite as: eLife 2017;6:e29319 doi: 10.7554/eLife.29319

Abstract

Support for open science is growing, but motivating researchers to participate in open science can be challenging. This in-depth qualitative study draws on interviews with researchers and staff at the Montreal Neurological Institute and Hospital during the development of its open science policy. Using thematic content analysis, we explore attitudes toward open science, the motivations and disincentives to participate, the role of patients, and attitudes to the eschewal of intellectual property rights. To be successful, an open science policy must clearly lay out expectations, boundaries and mechanisms by which researchers can engage, and must be shaped to explicitly support their values and those of key partners, including patients, research participants and industry collaborators.

https://doi.org/10.7554/eLife.29319.001

Introduction

Open science involves making scientific knowledge (in the form of papers, data, research tools, and other outputs) openly and practically available in order to accelerate discovery, innovation and clinical translation (Gold, 2016; Global Alliance for Genomics and Health, 2016; Fecher and Friesike, 2014). In a world first for an academic research institution, in 2016 the Montreal Neurological Institute and Hospital (the MNI) adopted a broad open science policy across all of its research activities. The MNI committed to make publicly available all positive and negative data by the date of first publication, to open its biobank to registered researchers and, perhaps most significantly, to withdraw its support of patenting on any direct research outputs (Figure 1; Poupon et al., 2017; Owens, 2016a; Rouleau, 2017). The span of this openness raises unique hopes and concerns for stakeholders, and also offers an important opportunity to examine and understand the potential benefits and costs of open science.

Guiding principles for the conduct of open science at the Montreal Neurological Institute and Hospital (MNI).

These principles cover five areas: the public release of data and other scientific resources; external research partnerships; the MNI Biobank; researcher and patient autonomy; and intellectual property. The authors developed draft Guiding Principles based on the results of this study. This draft was then presented to the MNI staff, management and researchers, who reviewed and amended the draft during two rounds of discussion and feedback. These Guiding Principles were adopted by the MNI in December 2016.

https://doi.org/10.7554/eLife.29319.002

Despite the benefits offered by open science, it has proven difficult to implement its ideals (Edwards, 2016; Nelson, 2009; Open Research Data Task Force, 2017). Recent evidence suggests that providing incentives for individual researchers to participate is the key rate-limiting step (Kidwell et al., 2016; Longo and Drazen, 2016; Fecher et al., 2015). This has stimulated many to think more deeply about how cultural factors, policies and metrics may affect the uptake of open practices by researchers (European Commission, 2017; Wilsdon, 2015; Harley, 2013; Neylon, 2017). This study builds on this work by providing insight into the perspectives of researchers in the lead up to the adoption of an open science policy within their institution. We conducted semi-structured interviews with 25 researchers, staff and partners, approximately one-third of the MNI's constituency, to identify their attitudes toward open science, the incentives they felt necessary to engage in open science, disincentives, the role of patients, and the eschewal of intellectual property rights. We then applied qualitative thematic content analysis to these data to identify key topics for discussion and to derive the framework for the MNI’s Open Science Policy (Figure 1).

Results

Our analysis yielded a number of key themes which we summarize below. Please see Ali-Khan et al. (2015) for the full research report, and MNI, 2017 for the latest information about the initiative. In this manuscript, we sometimes use proportions or numbers to quantify the number of interviewees who expressed a particular opinion: please see 'Materials and methods: Reporting' below for further details and a caveat.

Nebulous definition breeds uncertainty

Our analysis revealed that MNI researchers were generally favorable toward the notion of open science, reporting that they already engage in significant sharing. Nevertheless, almost half our interviewees noted that the concept is vague (Fecher and Friesike, 2014; Grubb and Easterbrook, 2011; OECD, 2015) and expressed uncertainty about what precisely open science would require of them (Open Research Data Task Force, 2017; Neylon, 2017; Ferguson, 2014). Based on our data, this uncertainty can discourage participation in two ways. First, the absence of clearly articulated definitions raised fears that open science practice may extend beyond comfort levels. Conversely, those who desired greater openness were cautious about taking part lest the lack of clarity prevent meaningful change.

Open science needs to be stakeholder driven

In the context of the MNI’s initiative, just over half of researchers stated that an institution-level open science policy could only be successful if it was developed in close collaboration with researchers, rather than simply imposed in a top-down fashion by management. Researchers were concerned that a broad one-size-fits-all directive may have adverse effects on their scientific priority and curtail their academic freedom by denying them, for example, the right to choose where to publish (Levin et al., 2016), to patent findings (Murray, 2010), to publish first and to control access to research outputs (Fecher et al., 2015).

A further dominant opinion, explicitly mentioned by over a quarter of interviewees, was that open science should not be implemented for ‘its own sake’. Instead, policy should reflect the values and needs of key stakeholders. Misgivings about open science were always tied to perceived negative effects on their careers, on their relationships with the patients who participate in research projects, or on their collaborations with industry.

Current state of sharing

More than three quarters of interviewees reported that they already share data and research tools on request after publication as a standard practice, and that they share with established collaborators before publication. However, outside of the bioinformatics and imaging area, few engaged in large-scale public sharing. Willingness to share varied depending on the data type and the resources involved in their development. Unsurprisingly, interviewees noted that digital data is more shareable. Most said that patients’ clinical and genomic data should be widely shared, subject to consent and ethics protections (Kaye, 2012), due to the limited intellectual contribution made by the researcher who collected the data. Four researchers felt that these data belonged to patients and thus should not be hoarded. On the other hand, two interviewees said it would be unfair to force early sharing of data and materials yielded through resource-intensive processes, such as iPS cell lines, or rare and depletable biosamples. Overall, there was wide agreement among interviewees that it is appropriate to wait until after publication to share experimental data beyond established collaborators. This was true even in the case of bioinformatics and imaging researchers, whom we expected to be the most comfortable with open pre-publication sharing.

Researchers are motivated by ethics and also by career advancement

Approximately three quarters of our interviewees articulated ethical motivations for more rapid, open sharing of data and scientific resources. These include the belief that publicly-funded research outputs ought to be released with minimal delay and that consistent with patients’ wishes, researchers have a duty to ensure that samples are broadly shared to maximize research and discovery. Likewise, many alluded to the negative impact of data ‘bottlenecking’ before publication, and the increased efficiency that would result from earlier and greater access to research outputs (Fecher et al., 2015).

Career advancement was an even more prevalent motivation. All but one interviewee mentioned the potential for open science to bolster their professional standing. Many said that requests for reagents, data or other tools led to diverse and unanticipated collaborations, expanding their interests, visibility and professional impact. Others noted that sharing has a positive impact on publication productivity and citations (Piwowar and Vision, 2013). While many who currently share stated that this is good academic practice, interviewees said they did so anticipating reciprocal behavior (Edwards, 2016).

Related to this, almost all interviewees raised a fundamental concern: that open science may put them at a professional disadvantage if they were compelled to release data and other resources before they have extracted value from their work (Fecher et al., 2015; Harley, 2010; Levin et al., 2016; LERU Research Data Working Group, 2013). Over three-quarters said that they would like to share more broadly and earlier in the research process, but they feared being 'scooped' and/or compromising the possibility of publishing in a high-impact journal. Further, a few were concerned that the MNI would go too far ‘out on a limb’ by adopting open science before other institutions in Montreal, Canada and beyond followed suit. In this case, others might benefit from MNI resources without reciprocating.

Most interviewees stated a preference to fully understand and publish before publicly releasing a dataset or reagent. Further, approximately half of researchers mentioned that it is socially irresponsible to release data before it is fully validated and its quality is assured, as this could waste others’ time and promote erroneous conclusions. Several noted the potential for shared data to be used in research or for applications with which they do not agree (Wouters and Haak, 2017). They worried that their or the MNI’s reputation might be compromised by such associations. Thus, while nearly all interviewees said the culture of science is shifting toward greater openness, more than half cautioned that the MNI should advance with care.

Attribution and publication

Almost every interviewee emphasized the highly competitive nature of biomedical research (Harley, 2010), and the central importance of maintaining strong academic metrics. A third of interviewees underlined that ensuring proper attribution and returns for sharing would motivate their participation in open science practice (Wouters and Haak, 2017). They noted that this could include citation, acknowledgement and in some cases co-authorship for use of shared data, as well as the development of new metrics to measure sharing contributions (so that they could be included in funding and academic advancement decisions).

Infrastructure and resources

All but one interviewee stressed that openness is time- and resource-intensive, including for example, the need for payment of open access publication fees, and for the preparation, formatting and handling of data and other research outputs for sharing (Levin et al., 2016; LERU Research Data Working Group, 2013). More broadly, researchers spoke of the costs inherent in the set-up and management of sharing infrastructure, including cyber and biobanking frameworks. Thus, interviewees emphasized that institutional support will be critical to support open science practice amongst researchers (Das et al., 2016; Poupon et al., 2017).

On patients

The majority of interviewees underlined public and patient benefit as the preeminent goal of open science at the MNI (Rouleau, 2017). The institution’s dual research and clinical functions offer the potential for ongoing data collection from consented patients across multiple research modalities. Opening this platform to outside researchers promises a powerful collaborative discovery resource, but raises familiar concerns about the protection of patients and research participants (Kaye, 2012).

The setting in which patients would be engaged about open science research and the nature of informed consent mechanisms were key points of disagreement. Some interviewees favored engagement solely by treating physicians, while other advocated for a centralized location with dedicated staff. Likewise, some supported broad consent to maximize the future use of samples and data, while others said tiered or dynamic consent (Kaye, 2012) would ensure that the preferences of research participant were properly addressed. However, almost every interviewee emphasized the primacy of safeguarding both patient confidentiality and the autonomy to decline participation without prejudice.

A few researchers said that patients may be concerned about the potential for their data or samples to be shared with as-yet unknown researchers. However, most thought that patients would be strong advocates for open science, given the framework’s promise for advancing new understanding and treatments. Some further suggested that open science would increase patient and public trust (Royal Society, 2012; Grand et al., 2012) given its emphasis on minimizing intellectual property, increasing transparency and channeling benefits to patients, rather than to industry. They noted this could increase the stature of the MNI in attracting high-quality researchers and trainees, greater patient participation in research and augmented private donation. Finally, several interviewees pointed to the potential for open science to allow patients to become more equal and informed research partners due to greater transparency through the research process. Improvement of researcher-participant relationships could enable more patient-responsive studies, enhancing patient satisfaction and research outcomes.

Research ethics

Many interviewees emphasized the key role of the institutional Research Ethics Board (REB) in facilitating their open science practice. One third of interviewees suggested that the REB is sometimes overly stringent and acts as a barrier to efficient sharing of their own research data, or to making use of patient data shared through open web repositories. Conversely, just under two thirds of interviewees said that the REB is evolving in step with open approaches to science, for example partnering with researchers to develop detailed governance mechanisms and patient consent protocols to allow broad sharing (Das et al., 2016; Poupon et al., 2017). Some interviewees underlined that harmonizing ethical requirements across Canada and internationally is a key priority to realize the promise of global open science. One way that harmonization could accelerate open science would be the introduction of standard click-wrap agreements that are signed when patient-derived data are downloaded, thus avoiding the need use traditional (and cumbersome) side agreements that are signed (and sometimes notarized) by central administrators (NKI-RS, 2017).

On intellectual property, industry and collaboration

Forgoing intellectual property, particularly patents, within the context of the MNI’s research activities is unprecedented for a major academic research institution (Stilgoe, 2016). Thus, unsurprisingly, the topic of intellectual property polarized opinion. Many of the basic science researchers we interviewed felt that pursuing patents is inefficient, noting that patenting is rarely worth its costs from either a commercial or translational standpoint. Conversely, many clinical-translational researchers said that the freedom to pursue intellectual property is an important aspect of their academic freedom and professional impact. Several underlined the importance of patents in facilitating partnerships with industry stakeholders (Murray and Stern, 2006). Only five of this latter group mentioned personal material benefit as a motivation. Further, some conceded that patents are often pursued too early in the research process, which may slow scientific progress. However, despite many of the interviewees not being interested in holding intellectual property themselves, there was a widespread belief that patents or other modes of legal protection are essential to ensure the translation of research later in the process.

A key area of resistance to open science concerned relationships with industry. These partnerships can bring researchers valuable professional opportunities and offer important avenues for translation and patient benefit. Some interviewees worried that mandated data sharing may deter industry from sponsoring clinical trials. Indeed, the MNI has said it will not impose a specific timeline for release of trial data by sponsors (Poupon et al., 2017). However, researchers note that all patient-participant data will be captured within the MNI Open Science Clinical Biological Imaging and Genetic (C-BIG) biobank: this means that when information on a therapeutic molecule is disclosed by collaborators, this information can be easily integrated with the corresponding patient data. Further, some interviewees said that making data and biosamples openly accessible might reduce the attractiveness of MNI researchers to potential collaborators, who may want to operate under a more closed model. However, the public launch of open science at the MNI seems to have stoked interest of companies in a range of sectors including pharmaceuticals, imaging, deep learning, big data and information technology (Poupon et al., 2017). The initiative has also impelled major gifts from private donors (Stilgoe, 2016).

Interviewees reported that the absence of intellectual property rights by the MNI over discoveries derived from C-BIG biobank materials or data is a key draw for partners. Nevertheless, there are dissenters. Some interviewees and some of the MNI’s potential industry collaborators stated that they will proceed with care, ‘testing the waters’ as they engage in open practices. Others, however, including the multinational biotechnology company Thermo Fisher Scientific, have rapidly secured open-science-based partnerships with the MNI, noting a shared objective in improving the accountability and efficiency of research. Thermo Fisher stated that the MNI’s open science policy will greatly accelerate the development and commercialization of more relevant reagents, while allowing the sharing of the experimental data with the research community. However, they underlined that maximizing the benefits of open science depends on broad community adoption.

One key problem highlighted by industry interviewees and MNI management is the legal implications of sharing materials that may be encumbered by existing intellectual property rights on tools that have been used in their creation (Rouleau, 2017). This real, but not insurmountable hurdle, has already slowed negotiations with Thermo Fisher. As Guy Rouleau, director of the MNI, said: “The irony is that this is a perfect example of what open science at the MNI seeks to avoid: intellectual property rights over scientific tools that chill research progress, with high social, economic and opportunity costs.”

Discussion

To date, open science has largely depended on bottom-up forces to drive adoption as funders, publishers and governments have often been reluctant to enforce open science norms (Open Research Data Task Force, 2017; Royal Society, 2012). Our analysis reinforces the point that researchers’ sharing behavior is primarily motivated by rational self-interest rather than pure altruism (Fecher et al., 2015; Levin et al., 2016; Haeussler, 2011). Widespread uptake in competitive research environments requires that open science is not only theoretically attractive but that it is beneficial to stakeholder communities. Our analysis revealed key concerns arising from uncertainty about what open science will require of researchers, and the risks open science may pose for professional competitiveness and for relationships with important research partners. To realize the promise of open science for discovery, innovation, research impact and reproducibility, an open science policy must clearly lay out expectations, boundaries and mechanisms for participation, and must be shaped to explicitly support researchers’ values and those of other key stakeholders.

Recent work points to the pivotal role of institutions in influencing open science practice in their constituencies (Fecher et al., 2015; LERU Research Data Working Group, 2013; Huang et al., 2012). In this context, the MNI is an interesting case study because it is the first organization to introduce an institution-wide open-science platform (Rouleau, 2017) and because certain characteristics of biomedical research (it is highly competitive, it involves human subjects and the commercial returns can be very high) make it a challenging field for openness (Tenopir et al., 2011; Haeussler, 2011; Walsh et al., 2007). Our study underlines several relevant points.

First, our analysis emphasized the importance of fostering buy-in and trust by developing the MNI open science policy from the ground-up through researcher engagement. Others have also underlined the benefits of this approach (Open Research Data Task Force, 2017). This current research, which informed the MNI’s framework, represents part of that process. Over the next five years, studies engaging the range of important stakeholders including researchers, patients, philanthropy, governments, research participants and industry partners will contribute to further refining MNI policy (Gold, 2016). It has been reported that social milieu can help overcome the reluctance to share (Haeussler, 2011). The MNI’s policy, sanctioned by all MNI researchers (Poupon et al., 2017), may enhance participation compared with situations in which researchers act without specific institutional policy, support or advocacy on their behalf. Moreover, given the emphasis on open science within the MNI, participation may raise researchers’ social capital, further encouraging a willingness to share (Haeussler, 2011). Increasing adoption of open science practices may place greater pressure on competitors to adopt the same normative practices, as this affects their status in the community (Westphal et al., 1997). Thus, MNI policy may begin to shift norms not only within the institute, but across the broader community (Fauchart and von Hippel, 2008). We will examine these hypotheses in future work.

Second, our study reiterated the importance of clear policies over ownership and control of scientific outputs. For example, researchers want to benefit from their work before broad release (Fecher et al., 2015; Wouters and Haak, 2017). Allowing researchers to exercise reasonable choice over when and how they share, and providing the leeway to adapt practice to different research contexts, may reinforce their trust in open science and promote participation. Consistent with this notion, the MNI policy calls for data release before or on the date of first publication and underlines the principle of autonomy (Figure 1). Notably, while other studies underline researchers’ belief in ownership over data they produced (Fecher et al., 2015; Wouters and Haak, 2017), some of our interviewees suggested that publicly-funded research data and biosamples belong to the public or to patients, rather than the researchers themselves. This perspective may derive from interviewees’ proximity to patients and the needs that open neuroscience seeks to address, or it may be related to the local culture at the MNI (Rouleau, 2017), the local socio-political context or to individual personality differences.

Third, our study, underlined the need for institutional support to encourage open science practice. The MNI is addressing researcher concerns through substantial institutional investment. The development of specialized patient consent and other REB processes, cyber and biobank infrastructure, support staff and streamlined workflow promote clear and efficient sharing (Das et al., 2016; Poupon et al., 2017). These platforms aim to support researcher trust by enabling the discretion to choose when and what to publically share and by protecting researchers’ and partners’ interests within a secure sharing environment. Likewise, the MNI recently partnered with F1000 to launch an open research platform (https://mniopenresearch.org) to allow rapid sharing of articles, data and other outputs. The MNI also offers a stipend to support the use of the platform and for open access publication in journals of the researcher’s choice. These resources are designed to reduce barriers to participation, acting as carrots rather than sticks to encourage open science practices (Ferriera, 2008; Leonelli et al., 2015). Tracking the impact of explicit institutional policy and resources compared to their absence will yield important information on the conditions needed to enhance open practices.

Fourth, our analysis corroborates the need to ensure professional returns to promote open science Fecher et al., 2015; LERU Research Data Working Group, 2013). Developing relevant and effective performance indicators and incorporating them in career advancement and funding processes was highlighted in our study and others (Peekhaus and Proferes, 2016; Borgman, 2015; European Commission, 2017; Wilsdon, 2015; Harley, 2013). A report on research data in the UK recently noted that professional incentives for researchers to share remain weak at best (Open Research Data Task Force, 2017). In the context of open access publication, several studies note that current entrenched academic reward structures can stymie new modes of research and communication (Peekhaus and Proferes, 2016; Eger et al., 2015; Xia, 2010; Bjork, 2004). Advocacy, partnership-building and policy-alignment within and across institutions wishing to encourage openness (including governments, funders, journals and publishers) will be important to evolve reward structures that match policy goals and instigate the desired cultural shift (Leonelli et al., 2015; Neylon and Wu, 2009; Munafò et al., 2017).

Fifth, the role of intellectual property was contentious in our interviews, as has been previously noted (Ferguson, 2014). Recent decades have seen a decided policy focus in North America and beyond on encouraging academics to patent with the goal of augmenting translation and university funding (Nicol, 2008). However, there is little consistent evidence to support this model’s effectiveness (Kenney and Patton, 2009; Williams, 2017). Open science at the institutional level offers the potential for faster dissemination of academic outputs, greater leverage of research investments, and an emphasis on universities as hubs for knowledge generation and dissemination (Nicol, 2008). At the same time, open science is expected to promote the local innovation ecosystem by spreading socio-economic impact (Gold, 2016). Thus, the seeming conflict between commercialization and open science agendas may be more apparent than real. Exploration at the interface of these two streams is needed to clarify how they may cross-pollinate to maximize equity, justice and efficiency in exacting research benefits.

Conclusion

Our study reiterates previously reported researcher concerns toward the adoption of open science practices, and uncovers fresh nuance. In particular, the institutional setting, the broad scope of research undertaken at the MNI and the proximity of patient and industry partners provide a new context to explore these issues. Here, we provide baseline findings that will be important to follow. Ultimately, our analysis underlines that open science should not impose extra burdens on researchers. Rather, policy must make sharing simple and should be structured to enhance researcher competitiveness, research programs and partnerships with patients and industry. Over the next five years, we will monitor the impact of the MNI’s open science policy through the collection of scientific, innovation, economic, social, and stakeholder metrics that will be made publicly available (Gold, 2016). As quantitative and qualitative data accrue through this large-scale experiment, these data will be fed-back to fine-tune best practices at the MNI. At present, many actors may be cautious, yet as the initiative reaches critical mass, it may begin to generate clear evidence of benefits, shift community norms and expectations, and encourage participation. The proof of this open science pudding will be in the eating.

Materials and methods

Study design

This study uses qualitative research methods: in-depth semi-structured interviews, followed by thematic content analysis. This methodology is best suited to in-depth exploration of the experiences and perceptions of research participants, and the meanings they attach to these (Braun and Clarke, 2006; Patton, 2002). As such, it is well-aligned with the needs of case studies undertaken to inform policy, as was the current research (Ritchie and Spencer, 2002). We report these methods according to Consolidated Criteria for Reporting Qualitative Research (COREQ) guidelines (Tong et al., 2007).

Study sample and research design

Due to the small community of relevant research participants, we used a purposive and snowball sample strategy to select invitees. The interviews were conducted in two phases. The first focused on MNI researchers and staff over Summer 2015. We conducted a second phase of interviews in Fall 2016, to address knowledge gaps concerning the viewpoints of researchers’ industry collaborators, and to update perspectives subsequent to launch of the open science initiative (Owens, 2016b). Thus, we re-interviewed three researchers and one whom we had not previously engaged, who all interact with industry partners. We also interviewed one industry collaborator, one industry veteran and one not-for-profit collaborator, and obtained a public statement from Thermo Fisher Scientific on its partnership with the MNI.

To begin the first phase of interviews, the MNI management provided a list of research areas and principal investigators that we independently used to selectively invite participants via email. During interviews we asked for suggestions for others who may provide insight, whom we subsequently invited. In the second phase we re-contacted select participants.

Data collection

One of us (SEA) with LH and/or a colleague (Kendra Levasseur; KL) conducted the interviews. None of these researchers was known to any of the participants prior to receiving the study invitation. ERG, who did not participate in the interviews, may have been known to some, as all are employed at the same institution. We conducted all interviews with MNI researchers face-to-face at locations of the interviewees’ choosing, namely their offices or labs, in June through September 2015. Before beginning interviews, we described our credentials, professional positions, the study context, confidentiality and privacy considerations, and noted the independent, academic nature of our research. All interviews with industry or non-profit collaborators were conducted over the phone.

All but one interview was digitally recorded and transcribed verbatim by LH, KL or other research assistants. One participant declined recording, so manual notes were taken. Interviews lasted between 30 and 90 minutes. We developed the interview guide based on our review of the open science literature and knowledge of the MNI’s research focus (see http://paceomics.org/index.php/interview-guide/), incorporating the feedback of the MNI management on a first draft. The interview process was iterative, feeding forward key issues raised by interviewees to maximize the informativenes of our research.

To start each interview, we collected demographic information to facilitate comparative analysis across interviews. We then asked open-ended, semi-structured questions to explore individual experience and knowledge. In qualitative research, the dataset is considered complete when a point of theoretical saturation is achieved—meaning no new major ideas, information or themes are emerging from interviews (Morse, 1995). Participant recruitment continued until we reached this point, and with consideration for achieving balanced representation across gender and research area. In total, we conducted 21 interviews with MNI researchers and staff in the first phase. In the second we interviewed four MNI researchers, and three external participants as described in ‘Study sample’, resulting in 25 interviewees in total.

Qualitative thematic analysis

We analyzed these data using thematic content analysis methods (Braun and Clarke, 2006; Ritchie and Spencer, 2002) This process consists of seven iterative stages: (i) familiarization; (ii) generation of an initial coding framework and application of these codes to the dataset; (iii) searching for and verification of themes across the entire dataset; (iv) identification of relationships and distinct differences between codes/subgroups of ideas; (v) definition and naming of themes; (vi) re-reading of the interviews and modifying codes based on emerging themes; and finally (vii) mapping and interpretation of the overall narrative identified from the data. We used NVivo 10 software to organize and manage our analysis (QSR International, 2016). This software enables tracking of the research process, thereby facilitating auditability and reproducibility, and thus the credibility of the work.

Development of analytical categories

During the thematic analysis process we developed several analytic categories. These capture what we defined as 1) 'substantive’; 2)’ auxiliary’; and 3)’ key’ data or issues. ‘Substantive’ categories captured interviewees’ opinions, concerns, ideas and motivations regarding open science. Those categorized as ‘auxiliary’ captured contextual information that we used to further our understanding of the ‘substantive categories’, such as the types of resources or stakeholders the interviewees mentioned as relevant. For example, where a researcher expressed concern about sharing iPS cells because of the large investment required to generate them, the text would be coded into a substantive category (“disincentives to sharing or open science – researcher time and money invested in resource creation”) and an auxiliary category (“types of resources – iPS cells and other cell lines”) to give contextual information. ‘Key categories’ represent the subset of interviewees’ opinions, concerns and motivations that we determined are the most relevant to the development of an open science policy at the MNI. Often, this material represents the most significant sources of disagreement or tension about the proposed shift to open science, and material that was the most emphasized by interviewees. See the full coding framework in the supplementary materials.

Validity and reliability of analysis

To support the validity of our analysis three coders (SEA, KL and LH) worked together to develop the initial coding framework and ensure it was consistently applied across interview transcripts. This coding framework was informed by our knowledge of the literature and the focus of our research questions (a top-down or deductive approach), in addition to new ideas that we identified inductively from the ‘grounded’ data (a bottom-up approach; Patton, 2002; Ritchie and Spencer, 2002). LH and KL then divided the interviews amongst them to code individually. SEA, KL and LH met regularly throughout the research process to compare and discuss data interpretation and modify the framework. The entire research team met on a weekly basis to discuss emerging findings (SEA, LH, KL and ERG).

KL and LH also undertook a formal inter-coder reliability analysis using NVivo 10 software (QSR International, 2016), by both coding the same interview and measuring agreement between the two copies. Most inter-coder percentage agreement at each category varied from 80 to 100%, revealing only minimal disagreement between coders. Categories at which agreement was lower were among the ‘auxiliary’ group. When we inspected discrepancies, we observed that this was due to minor differences in the length of the text coders had selected for auxiliary categories, with minimal implications for our analyses. Finally, we triangulated data across interviews and available policy, academic and web resources, further seeking to ensure the accuracy of our findings.

Reporting

Our analysis yielded ten major themes of discussion, which we report here as nine themes after combining the intellectual property and collaboration themes to improve the flow of the text (see Ali-Khan et al., 2015 for the full report). We note that in this manuscript we may indicate the proportion or number of our interviewees who held the described opinions. Two limitations to this approach should be considered. First, our sample, while broadly representative of the units, demographics and responsibilities at the MNI, is not random. Further, we note that in the course of semi-structured interviews, respondents will answer according to their specific interests and knowledge (Patton, 2002; Ritchie and Spencer, 2002). Therefore, the content of individual interviews is not always directly comparable. Subject to this caution, we believe that the inclusion of proportions enhances the informativeness of our findings (Maxwell, 2010). Finally, we note that we took a reflexive standpoint on our data, critically considering them within the broader context of the academic and policy literature and our professional knowledge and experience in this domain.

References

  1. 1
  2. 2
  3. 3
    Open access to scientific publications: an analysis of the barriers to change?
    1. B-C Bjork
    (2004)
    Information Research 9:2.
  4. 4
    Big Data, Little Data, No Data: Scholarship in the Networked World
    1. CL Borgman
    (2015)
    Cambridge: MIT Press.
  5. 5
  6. 6
  7. 7
  8. 8
  9. 9
  10. 10
  11. 11
  12. 12
  13. 13
    Open science: one term, five schools of thought
    1. B Fecher
    2. S Friesike
    (2014)
    In: S Bartling, S Friesike, editors. Opening Science. Heidelberg: Springer. pp. 17–47.
  14. 14
  15. 15
  16. 16
  17. 17
  18. 18
    Open science: A new “Trust technology”?
    1. C Grand
    2. K Wilkinson
    3. AFW Bultitude
    (2012)
    Science Communication 34:679–689.
  19. 19
  20. 20
  21. 21
  22. 22
  23. 23
  24. 24
  25. 25
  26. 26
  27. 27
  28. 28
  29. 29
  30. 30
    Data sharing
    1. DL Longo
    2. JM Drazen
    (2016)
    New England Journal of Medicine 374:276–277.
    https://doi.org/10.1056/NEJMe1516564
  31. 31
  32. 32
    Open Science
    1. MNI
    (2017)
    Accessed 2017.
  33. 33
  34. 34
  35. 35
  36. 36
  37. 37
  38. 38
  39. 39
  40. 40
    Strategies for dissemination of university knowledge
    1. D Nicol
    (2008)
    Health Law Journal 16:207–235.
  41. 41
    Data Access Overview
    1. NKI-RS
    (2017)
    Accessed 2017.
  42. 42
    Making Open Science a Reality
    1. OECD
    (2015)
    Accessed 2017.
  43. 43
    Research Data Infrastructures in the UK
    1. Open Research Data Task Force
    (2017)
    London: Universities UK.
  44. 44
  45. 45
  46. 46
    Qualitative Research & Evaluation Methods
    1. MQ Patton
    (2002)
    237–238, Purposeful Sampling, Qualitative Research & Evaluation Methods.
  47. 47
  48. 48
  49. 49
  50. 50
  51. 51
    NVivo
    1. QSR International
    (2016)
    Accessed 2017.
  52. 52
    Qualitative data analysis for applied policy research
    1. J Ritchie
    2. L Spencer
    (2002)
    The Qualitative Researcher’s Companion 573:305–329.
  53. 53
  54. 54
  55. 55
  56. 56
  57. 57
  58. 58
  59. 59
  60. 60
  61. 61
    The Metric Tide
    1. J Wilsdon
    (2015)
    Accessed 2017.
  62. 62
  63. 63

Decision letter

  1. Peter A Rodgers
    Reviewing Editor; eLife, United Kingdom

In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.

Thank you for submitting your article "Motivating Participation in Open Science by Examining Researcher Incentives" to eLife for consideration as a Feature Article. Your article has been reviewed by three peer reviewers, and the evaluation has been overseen by the eLife Features Editor (Peter Rodgers).

The reviewers and the Features Editor have agreed on the revisions that are needed to make the article suitable for publication in eLife (see list below).

The following individuals involved in review of your submission have agreed to reveal their identity: Cameron Neylon (Reviewer #2); Juan Pablo Alperin (Reviewer #3).

Summary:

This is a valuable contribution to the discussion on the implementation of Open Science approaches reporting on an important and large-scale experiment in this space. The study tackles an important issue facing the research community today: while most researchers agree with the principles of Open Science, there continue to be barriers to adopting OS practices that are deeply rooted in the academic culture. Exploring and understanding the motivations for adopting or resisting OS practices is therefore an important part of making changes. Neuro's OS framework does appear to offer an interesting case study to explore these issues. The methods are presented well, and I have no concerns about the way the data collection and data analysis are described. The choice of semi-structured interviews is justified convincingly.

Essential revisions:

1) The authors should discuss all ten of the themes they identify. There is substantial value to my mind in reporting the full set, as this will allow greater integration with the other literature in this space.

2) The issue of researchers' trust: The authors mention the role of incentives in publishing, and the significance of career outcomes for researchers. Publishing novel research can make researcher careers, while being 'scooped' may well break their careers. The concerns of scientists participating in open science initiatives often relate to the lack of trust in the system to safeguard their priority in publishing novel findings. I feel that the authors of this paper have somewhat ignored the issue of trust/distrust in science.

3) The authors need to do more to cite existing literature in the field and to place their own work in the context of previous work. Here are some specific examples:

3a) One very recent study which is conspicuously absent from the reference list, and which may inform the analysis, is: Open Research Data Taskforce (2017) Research Data Infrastructures in the UK: www.universitiesuk.ac.uk/policy-and-analysis/research-policy/open-science/Documents/ORDTF%20report%20nr%201%20final%2030%2006%202017.pdf

This is a comprehensive review of Open Science (preservation and sharing of data, the responsibilities of researchers, institutions and funders) in various countries, including Canada. Very helpfully, the report summarizes the problems the policy causes for researchers/scientists (though these were not based on interviews with scientists). Perhaps it would be useful for the authors to compare their findings with what the authors of the UK report found. Some points made here resonate with the UK study, but others stand in contrast to it. Is this because of the specific context of the country, or perhaps the context of this particular institution that appears to be head of the game in the implementation of Open Science policies?

3b) I think the paper could be substantially strengthened and made more generally applicable through reference to existing frameworks and similar efforts. I am thinking particularly of the work of Fecher and Friesikie (a number of articles including the important "Open Science: One term, five schools of thought" but also recent work on barriers to data sharing in Germany). Christine Borgman's work on data sharing (Big Data, Little Data…) and more broadly dissections of incentives (European Commission Expert Group report on role of research evaluation in progress to Open Science, Metric Tide report) and potentially the literature around choices to public Open Access as well could be valuable. At the moment I feel that the article reinforces what we have seen in other cases, which is valuable. I think it would be stronger and more valuable if these issues were developed in those broader contexts.

3c) (From Cameron Neylon). Something from my own recent work that I feel would be worth exploring is the extent to which group level dynamics help or hinder adoption. What is unique about the effort at the Neuro is the way it operates at a departmental level. Does being part of a group shift the dynamics of issues? Does identity of being in the department vs identity of being part of external communities contribute to engagement, or hinder it?

Note: This may be out of scope for this article, but I feel it could offer a productive line of inquiry that builds on the important and unique aspects of this program.

3d) The article would benefit from a more thorough literature review that looks at barriers to the adoption of open practices. While some aspects of Open Science are not as well studied, Open Access (OA) has been written about extensively in the literature, including studies about opinions and attitudes, and some explicitly about barriers to change. There have also been efforts to document barriers to adoption of Open Data. A few references are below; a number of publishers have also conducted surveys of researchers' awareness of and attitudes towards both open access and open data.

However, more important from my perspective would be to relate this other work to what has already been written in the Discussion section. For example, researcher's misgivings based on a lack of awareness and understanding of openness has been previously documented. Similarly, the endless studies on the OA Citation Advantage speaks to the author's point that the OS community has attempted to find evidence of the benefits to researchers.

Björk, B.-C. (2004). Open access to scientific publications-an analysis of the barriers to change? Retrieved from https://helda.helsinki.fi/handle/10227/647

Harley, D. (2013). Scholarly communication: Cultural contexts, evolving models. Science, 342(6154), 80-82.

Harley, D., Acord, S. K., Earl-Novell, S., Lawrence, S., & King, C. J. (2010). Assessing the Future Landscape of Scholarly Communication: An Exploration of Faculty Values and Needs in Seven Disciplines. Center for Studies in Higher Education. Retrieved from http://escholarship.org/uc/item/15x7385g

Peekhaus, W., & Proferes, N. (2015). How library and information science faculty perceive and engage with open access. Journal of Information Science, 41(5), 640-661. https://doi.org/10.1177/0165551515587855

Peekhaus, W., & Proferes, N. (2016). An examination of North American Library and Information Studies faculty perceptions of and experience with open-access scholarly publishing. Library & Information Science Research, 38(1), 18-29. https://doi.org/10.1016/j.lisr.2016.01.003

Xia, J. (2010). A longitudinal study of scholars attitudes and behaviors toward open-access journal publishing. Journal of the American Society for Information Science & Technology, 61(3), 615- 624. https://doi.org/10.1002/asi.21283

https://doi.org/10.7554/eLife.29319.004

Author response

Essential revisions:

1) The authors should discuss all ten of the themes they identify. There is substantial value to my mind in reporting the full set, as this will allow greater integration with the other literature in this space.

We have added data on all themes identified to the manuscript. These number nine not ten, as we combined some of them (notably on intellectual property and industry partners) to improve the flow of the text. Please see: Results section; Themes: “Current state of sharing”, “Attribution and publication”, “Infrastructure and resources” and “Research ethics”.

We also lightly edited parts of the existing themes to add to their comprehensiveness. Please see: “Open Science Needs to be Stakeholder Driven”, “Researchers: Motivated by ethics, but also career advancement” and “On patients”.

2) The issue of researchers' trust: The authors mention the role of incentives in publishing, and the significance of career outcomes for researchers. Publishing novel research can make researcher careers, while being 'scooped' may well break their careers. The concerns of scientists participating in open science initiatives often relate to the lack of trust in the system to safeguard their priority in publishing novel findings. I feel that the authors of this paper have somewhat ignored the issue of trust/distrust in science.

We have added data that are relevant to the issues of researchers’ trust to the Results and Discussion.

Specifically, please see:

- “Open Science Needs to be Stakeholder”: we report on the need for stakeholder consultation in open science policy design and for such policy to respect researchers’ academic freedom

- “Current state of sharing”: we note researchers’ agreement that they should be allowed to publish before releasing data

- “Researchers: Motivated by ethics, but also career advancement”: we note researchers’ fear of ‘scooping’ and misuse, and of the MNI policy going beyond cultural norms and thus disadvantaging them.

- Discussion: we discuss the issue of trust and how the MNI is starting to address this.

We hope that these additions properly address your point about trust.

3) The authors need to do more to cite existing literature in the field and to place their own work in the context of previous work. Here are some specific examples:

3a) One very recent study which is conspicuously absent from the reference list, and which may inform the analysis, is: Open Research Data Taskforce (2017) Research Data Infrastructures in the UK: www.universitiesuk.ac.uk/policy-and-analysis/research-policy/open-science/Documents/ORDTF%20report%20nr%201%20final%2030%2006%202017.pdf

This is a comprehensive review of Open Science (preservation and sharing of data, the responsibilities of researchers, institutions and funders) in various countries, including Canada. Very helpfully, the report summarizes the problems the policy causes for researchers/scientists (though these were not based on interviews with scientists). Perhaps it would be useful for the authors to compare their findings with what the authors of the UK report found. Some points made here resonate with the UK study, but others stand in contrast to it. Is this because of the specific context of the country, or perhaps the context of this particular institution that appears to be head of the game in the implementation of Open Science policies?

Thank you for these helpful references. We have added citations to this report throughout the Results and Discussion. We felt that the issues it notes were largely consistent with our findings, but we have highlighted one or our findings that diverges from Fecher, Friesike and Hebings’ 2015 work and from the recent Wouters and Haak 2017 CWTS, University Leiden and Elsevier study.

3b) I think the paper could be substantially strengthened and made more generally applicable through reference to existing frameworks and similar efforts. I am thinking particularly of the work of Fecher and Friesikie (a number of articles including the important "Open Science: One term, five schools of thought" but also recent work on barriers to data sharing in Germany). Christine Borgman's work on data sharing (Big Data, Little Data…) and more broadly dissections of incentives (European Commission Expert Group report on role of research evaluation in progress to Open Science, Metric Tide report) and potentially the literature around choices to public Open Access as well could be valuable. At the moment I feel that the article reinforces what we have seen in other cases, which is valuable. I think it would be stronger and more valuable if these issues were developed in those broader contexts.

As noted directly above, we have added reference to Fecher, Freisike and Hebing, 2015 throughout the Results and Discussion, and to European Commission report, Wilsdon et al., 2017, and Borgman, 2015, to the Discussion. We do feel that our results are largely consistent with those reported by others. In the discussion however, we highlight the unique context of the MNI’s open science initiative, and reflect on how this may influence some of our findings.

3c) (From Cameron Neylon). Something from my own recent work that I feel would be worth exploring is the extent to which group level dynamics help or hinder adoption. What is unique about the effort at the Neuro is the way it operates at a departmental level. Does being part of a group shift the dynamics of issues? Does identity of being in the department vs identity of being part of external communities contribute to engagement, or hinder it?

Note: This may be out of scope for this article, but I feel it could offer a productive line of inquiry that builds on the important and unique aspects of this program.

Thank you for this comment. Yes, we attempted to address this in the Discussion.

3d) The article would benefit from a more thorough literature review that looks at barriers to the adoption of open practices. While some aspects of Open Science are not as well studied, Open Access (OA) has been written about extensively in the literature, including studies about opinions and attitudes, and some explicitly about barriers to change. There have also been efforts to document barriers to adoption of Open Data. A few references are below; a number of publishers have also conducted surveys of researchers' awareness of and attitudes towards both open access and open data.

However, more important from my perspective would be to relate this other work to what has already been written in the Discussion section. For example, researcher's misgivings based on a lack of awareness and understanding of openness has been previously documented. Similarly, the endless studies on the OA Citation Advantage speaks to the author's point that the OS community has attempted to find evidence of the benefits to researchers.

Björk, B.-C. (2004). Open access to scientific publications-an analysis of the barriers to change? Retrieved from https://helda.helsinki.fi/handle/10227/647

Harley, D. (2013). Scholarly communication: Cultural contexts, evolving models. Science, 342(6154), 80-82.

Harley, D., Acord, S. K., Earl-Novell, S., Lawrence, S., & King, C. J. (2010). Assessing the Future Landscape of Scholarly Communication: An Exploration of Faculty Values and Needs in Seven Disciplines. Center for Studies in Higher Education. Retrieved from http://escholarship.org/uc/item/15x7385g

Peekhaus, W., & Proferes, N. (2015). How library and information science faculty perceive and engage with open access. Journal of Information Science, 41(5), 640-661. https://doi.org/10.1177/0165551515587855

Peekhaus, W., & Proferes, N. (2016). An examination of North American Library and Information Studies faculty perceptions of and experience with open-access scholarly publishing. Library & Information Science Research, 38(1), 18-29. https://doi.org/10.1016/j.lisr.2016.01.003

Xia, J. (2010). A longitudinal study of scholars attitudes and behaviors toward open-access journal publishing. Journal of the American Society for Information Science & Technology, 61(3), 615- 624. https://doi.org/10.1002/asi.21283

Thank you for these references. We have added reference to several of them.

https://doi.org/10.7554/eLife.29319.005

Article and author information

Author details

  1. Sarah E Ali-Khan

    Sarah E Ali-Khan is in the Centre for Intellectual Property Policy, Faculty of Law, McGill University, Montreal, Canada

    Contribution
    Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing—original draft, Project administration
    Competing interests
    No competing interests declared
    ORCID icon 0000-0002-9453-5086
  2. Liam W Harris

    Liam W Harris is in the Centre for Intellectual Property Policy, Faculty of Law, McGill University, Montreal, Canada

    Contribution
    Investigation, Writing—original draft
    Competing interests
    No competing interests declared
  3. E Richard Gold

    E Richard Gold is in the Centre for Intellectual Property Policy, Faculty of Law, and the Department of Human Genetics, McGill University, Montreal, Canada

    Contribution
    Conceptualization, Formal analysis, Supervision, Project administration, Writing—review and editing
    For correspondence
    richard.gold2@mcgill.ca
    Competing interests
    This study was funded under the PACEOMICS project, supported by Genome Canada, Genome Quebec, Genome Alberta and the Canadian Institutes for Health Research, and by the Montreal Neurological Institute and Hospital (the MNI), which is part of McGill University, with which the authors are affiliated. The MNI identified the need for this study and approached one of the authors (ERG) to conceive, design and actualize the research. The MNI did not have access to the study data and played no further role in the study other than to supply a list of staff members.
    ORCID icon 0000-0002-3789-9238

Funding

Genome Canada (PACEOMICS)

  • E Richard Gold

Canadian Institutes of Health Research (PACEOMICS)

  • E Richard Gold

Genome Quebec (PACEOMICS)

  • E Richard Gold

Montreal Neurological Institute

  • E Richard Gold

Genome Alberta (PACEOMICS)

  • E Richard Gold

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

We thank Kendra Levasseur for her excellent research assistance on this project.

Ethics

Human subjects: This study was approved by the Research Ethics Board of McGill University. All interviewees provided written informed consent.

Reviewing Editor

  1. Peter A Rodgers, Reviewing Editor, eLife, United Kingdom

Publication history

  1. Received: June 6, 2017
  2. Accepted: October 20, 2017
  3. Version of Record published: October 30, 2017 (version 1)

Copyright

© 2017, Ali-Khan et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 871
    Page views
  • 73
    Downloads
  • 0
    Citations

Article citation count generated by polling the highest count across the following sources: PubMed Central, Scopus, Crossref.

Comments

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Download citations (links to download the citations from this article in formats compatible with various reference manager tools)

Open citations (links to open the citations from this article in various online reference manager services)