Abstract
Introduction
Institutional, national, and international policies increasingly oblige or encourage research data sharing (Bishop & Kuula-Luumi, 2017; European Commission, 2019; Kurata et al., 2017) as openly sharing research data has enormous potential (Cho, 2019; Terras, 2015). It has been stated that open research data is critical for the duplication, corroboration, and extension of empirical findings (Andreoli-Versbach & Mueller-Langer, 2014). Open research data enables the creation of new data combinations (Jaeger & Bertot, 2010; Krotoski, 2012; Uhlir & Schröder, 2007), novel discoveries (Grechkin et al., 2017), better replication of research, and the avoidance of the unnecessary repetition of research (Campbell, 2015; Rouder, 2016; Von St. Vieth et al., 2017). Open research data also potentially contributes to transparent and verifiable research (Enke et al., 2012), and enables scientists to better inform society of the outcomes derived from their—often publicly funded—research (Arza & Fressoli, 2018; Enke et al., 2012).
Whether researchers are willing and able to share their research data openly depends on a complex combination of factors (Tenopir et al., 2011). Examples of factors that influence researchers’ open data sharing behavior include the existence of a demand for specific data (Zuiderwijk & Spiers, 2019), the availability of an appropriate infrastructure for data sharing (Arzberger et al., 2004; Joo et al., 2017; Wallis et al., 2013), the organizational support provided for sharing research data openly (Joo et al., 2017; Kim & Yoon, 2017; Sayogo & Pardo, 2013), and consequently how much effort it requires to openly publish the data (Heise & Pearce, 2020). Some factors also relate to the data itself, such as the privacy sensitivity of the data (da Costa & Lima Leite, 2019; Haeusermann et al., 2017; Kim & Adler, 2015) and its quality (Fecher et al., 2015; Yoon, 2017). When researchers’ environment changes, the factors influencing researchers’ willingness and ability to share their data openly may also alternate.
The outbreak of the Coronavirus SARS-CoV-2, causing the disease COVID-19, was a significant modification in the environment of many researchers worldwide. In March 2020, the World Health Organization (WHO) officially characterized COVID-19 as a pandemic (World Health Organization, 2020). At the time of writing, many countries worldwide have found a way to manage COVID-19 and claim that the number of cases is under control. Still, the pandemic provides an interesting perspective to learn from. The COVID-19 pandemic may have impacted some factors that determine whether researchers share their research data openly. Consequently, the pandemic may have led researchers to either change their open data sharing behavior or not. On the one hand, researchers’ willingness and ability to openly share their research data may have increased due to the COVID-19 pandemic. For example, the demand or urgent need for specific datasets and collaboration on data has grown, especially for real-time data derived from COVID-19-related research (Curioso & Carrasco-Escobar, 2020). On the other hand, several studies report that open data availability remains restricted compared to the many articles published since the COVID-19 pandemic started (Gkiouras et al., 2020). Various types of critical datasets on COVID-19 are not publicly available (Baker et al., 2020; Curioso & Carrasco-Escobar, 2020).
While several relevant studies concerning the influence of the COVID-19 pandemic on researchers’ behavior to share their research data openly exist, these mainly provide indications or suggestions rather than empirical research in this area (e.g., Cheifet, 2020; Curioso & Carrasco-Escobar, 2020; Cutcher-Gershenfeld et al., 2020; Gardner et al., 2021). Of the few empirical studies, some focus on the reuse of open research data rather than its provision (Baynes & Hahnel, 2020) or on the number of COVID-19-related articles for which the underlying datasets are shared openly (Gkiouras et al., 2020; Lucas-Dominguez et al., 2021). Research that empirically investigates how COVID-19 pandemic-related factors influenced researchers’ behavior to share their research data openly is scarce. To fill this knowledge gap, this study aims to investigate the influence of COVID-19 pandemic-related factors on researchers’ willingness and ability to share their research data openly.
This study contributes scientifically by going beyond conceptual studies as it provides empirically-funded insights concerning the influence of COVID-19 pandemic-related factors on researchers’ willingness and ability to openly share their data. As a novel scientific contribution, it demonstrates and discusses which COVID-19 pandemic-related factors may have changed researchers’ willingness and ability to share their research data openly and why some other factors appeared not to have any influence on researchers’ open data sharing behavior. As a practical contribution, this research provides recommendations that policymakers can use to sustainably support open research data sharing in post-COVID-19 times. Gaining more insight into the factors that influence the decision of researchers to openly share their research data is critical. Practically, such insight offers the possibility to better understand how policymakers can positively influence open research data sharing, with the ultimate goal of realizing more societal, operational, and economic value.
Research Background
Many definitions of research data and data sharing exist (Kurata et al., 2017). In this study, we define open research data as the structured, machine-readable data underpinning scientific research results that researchers actively publish on the internet for public reuse, and that is freely accessible, usable, modifiable, and sharable by other researchers (European Commission, n.d.; Geiger & Von Lucke, 2012; Open Knowledge Foundation, 2015; The Concordat Working Group, 2016). Open research data includes primary (i.e., raw) data and data derived from primary data or existing sources held by others (The Concordat Working Group, 2016), encompassing both qualitative and quantitative data.
Some studies have already been conducted on the topic of open research data in relation to the COVID-19 pandemic. Part of this previous research focuses on using and exploiting open research data, including COVID-19 data, to gain further insight into the development of the COVID-19 pandemic and related issues (e.g., Furtado, 2020; Kang et al., 2020; Leung et al., 2020; López & Čukić, 2021; Seo et al., 2020; Sousa & Barata, 2021; Xiong et al., 2020). Other studies concentrate on improving the findability of COVID-19-related data (Alamo et al., 2020; Ferrer-Sapena et al., 2020; Head, 2020; Onami et al., 2020; Todd et al., 2020) and the challenges specifically for interpreting and using COVID-19 data (El Emam et al., 2020; Temiz & Gurdur Broo, 2020). Yet other studies concern governmental policies on sharing COVID-19 data openly or not (Gonzalvez-Gallego & Nieto-Torrejon, 2020; Yuan et al., 2020) and the publication of COVID-19 pandemic articles in relation to providing open access to the underlying research data (Gkiouras et al., 2020; Teixeira da Silva et al., 2020). Only few studies examined how the COVID-19 pandemic influenced researchers’ behavior to share their research data openly. For example, some studies suggest an increase in researchers’ willingness and ability to openly share their data due to the COVID-19 pandemic (e.g., Baynes & Hahnel, 2020; Cheifet, 2020). Others indicate no or only very minor effects (e.g., Curioso & Carrasco-Escobar, 2020; Cutcher-Gershenfeld et al., 2020; Gkiouras et al., 2020; Lucas-Dominguez et al., 2021), or provide arguments for both an increase and decrease in open data sharing behavior during the pandemic (Gardner et al., 2021).
Various factors could potentially increase researchers’ willingness and ability to openly share their research data due to the COVID-19 pandemic. First, the demand or urgent need for specific datasets and collaboration on data has grown, especially for real-time data derived from COVID-19-related research (Curioso & Carrasco-Escobar, 2020). The COVID-19 pandemic requires “the collection, reporting and sharing of data within and between research communities, public health practitioners, clinicians and policymakers” (RDA COVID-19 Working Group, 2020, p. 7), which helps to comprehend the spread of the virus (Temiz & Gurdur Broo, 2020). During the COVID-19 pandemic, governmental policymakers urgently needed to assess the severity, dispersion, and effects of COVID-19, make informed decisions and rapidly implement efficient and effective response strategies based on timely and accurate data (RDA COVID-19 Working Group, 2020). These response strategies have an enormous impact on safety, security, and the economy. The COVID-19 pandemic proofs the significance of having access to open research data relevant for emergency response strategies (Jung & Novikova, 2020), just like preceding health emergencies did (World Health Organization, 2015).
Furthermore, the infrastructure for openly sharing research data may have been improved due to the need for open COVID-19 data. For example, data sharing support services worldwide made various efforts to establish infrastructure for real-time data publication (Gardner et al., 2021). Support services improved existing systems to meet additional “expectations for timely open data at an actionable level of spatial resolution” (Gardner et al., 2021, p. e80). Improved infrastructure may have made it easier for researchers to openly share their data and possibly increased their ability and willingness to share data openly. Researchers have started to appreciate accurate and reliable open data more during the COVID-19 pandemic (Digital Science, 2021) and COVID-19 may have transformed how researchers collaborate (Kipnis, 2021). Furthermore, seeing apparent successes of the result of openly sharing research data, including the speedy sequencing of the SARS-CoV-2 Coronavirus genome, may stimulate researchers to follow this example (Cheifet, 2020; Cutcher-Gershenfeld et al., 2020).
On the other hand, there may also be various factors that have led to a descrease or no changes in researchers openly sharing research data due to the COVID-19 pandemic. Different studies report that open data availability remains restricted compared to the many articles published since the COVID-19 pandemic started (Gkiouras et al., 2020). Various types of critical datasets on COVID-19 are not publicly available (Baker et al., 2020; Curioso & Carrasco-Escobar, 2020). Besides, Gardner et al. (2021) report that even though data sharing infrastructures improved during the COVID-19 pandemic, they still have severe limitations. Constraints of data-sharing infrastructures include the lack of agreed standards for collecting, documenting, and sharing the data (Ferrer-Sapena et al., 2020; Gardner et al., 2021; RDA COVID-19 Working Group, 2020), the lack of granularity of the data’s spatial and temporal scale (Gardner et al., 2021), and the lack of a machine-readable format (Gardner et al., 2021). Mechanisms to coordinate data sharing across research disciplines are inadequate, and motivation structures are lacking (Shmagun et al., 2021). These shortcomings make the data less useful for planning and modeling purposes (Gardner et al., 2021) and may reduce researchers’ willingness and ability to openly share their research data. Previous research also found that early-career researchers are negatively affected by the ongoing pandemic (Herman et al., 2021), which may reduce their willingness and ability to openly share their research data.
In addition to the factors that can be considered COVID-19 pandemic-specific, also during the COVID-19 pandemic researchers still struggled with obstacles to openly sharing data that already existed before the pandemic. Examples include the commercialization of research findings (Fecher et al., 2015), the fear of the misinterpretation of open data (Harper & Kim, 2018; Schmidt et al., 2016), the fear of receiving no credit or recognition for sharing the data (Arzberger et al., 2004; Schmidt et al., 2016), the fear of data scooping (Sayogo & Pardo, 2013; Zuiderwijk & Spiers, 2019), trust issues (Corti & Fielding, 2016), and missing out on future publication opportunities (Harper & Kim, 2018; Mooney & Newton, 2012). Due to these factors, the impact of COVID-19 pandemic-related factors on researchers’ willingness and ability to openly share their research data may be small or even non-existent. And even if researchers openly share their data more often due to the COVID-19 pandemic, this behavior may not sustain in the long term (Shmagun et al., 2021). The increase in data sharing may be temporary because researchers often share their data in the absence of formal contracts and other long-lasting institutional arrangements (Cutcher-Gershenfeld et al., 2020).
In sum, previous research provides both factors that potentially increase and factors that potentially decrease open research data sharing rates due to the COVID-19 pandemic. Furthermore, there are factors that appear not to be affected by the COVID-19 pandemic but still influencing open data sharing behavior or do not result in any changes. Finally, there may be differences between research fields in “accelerating preexisting patterns of collaboration and open sharing of data, models, and resources in response to the crisis” (Cutcher-Gershenfeld et al., 2020, p. 499). The lack of insight into how COVID-19 pandemic-related factors and other factors influenced the open data sharing behavior of researchers is my main driver for conducting a questionnaire on this topic, as discussed in the next section.
Research Design
Approach
This study’s target group consists of researchers who have at least a general understanding of the term “open research data.” We collected data through a questionnaire promoted among both academic and non-academic researchers since both groups can openly share research data. This study’s questionnaire can be classified as an online, cross-section, self-completion survey. We used a non-random purposive sampling approach to promote the questionnaire. As explained by Hibberts et al. (2012, p. 67), “purposive sampling involves seeking out specific individuals meeting specific criteria to participate in a research study.” The specific criteria in this study included that participants (1) were researchers collecting or producing research data, (2) had a basic understanding of the meaning of openly sharing research data, (3) covered a variety of research disciplines, including those that might potentially be COVID-19 pandemic-related. These criteria were directly derived from this study’s main objective (i.e., to investigate the influence of COVID-19 pandemic-related factors on researchers’ willingness and ability to share their research data openly). Moreover, this study had to be conducted within a time frame where researchers could still clearly remember the influence of the COVID-19 pandemic on their data sharing behavior. This criterion was met by collecting data at a moment when the COVID-19 pandemic was still ongoing in many countries worldwide. Due to this constraint, questionnaire responses had to be collected within a relatively small time frame. Questionnaire responses were collected between May 2020 and August 2020, using the Qualtrics software (https://www.qualtrics.com/), which is compliant with the European General Data Protection Regulation. The non-random purposive sampling approach was necessary to establish a sample of researchers who met the above-mentioned criteria and to conduct this study within the limited time frame.
We used two main approaches to promote the questionnaire. First, we requested participants of the Massive Open Online Course (MOOC) “Open Science: Sharing Your Research with the World” to complete the questionnaire. This course is taught by Delft University of Technology. The reason for selecting the MOOC participants is because these participants met the three above-mentioned criteria to be included in this study. First, since the MOOC was aimed at researchers (particularly PhD candidates, postdocs, and assistant, associate, and full professors) there was a high chance that they collected and/or produced research data, thereby meeting our first criterion. Second, the MOOC participants represented a research community that understands what research data is and what the benefits and barriers for openly sharing research data are, since these are topics taught in this online course. An understanding of open research data is essential for researchers to participate in our study in order to obtain valid responses to our questionnaire. Third, based on registration data from the MOOC, we knew that the MOOC participants represented a variety of researchers from different research disciplines, which enabled us to investigate differences in researchers’ willingness and ability to openly share research data between research disciplines.
Furthermore, since the number of active MOOC participants was limited to approximately 100 researchers, we decided to promote the questionnaire beyond the MOOC. To reach researchers from a large diversity of research disciplines, we sent many invitations to e-mail lists for specific research disciplines, in this way ensuring that the first and third inclusion criteria would be met (i.e., involving researchers collecting or producing research data and covering a variety of research disciplines). We also sent more than 1,000 personalized e-mails to researchers identified through institutional websites, including those from Leiden University, MIT, University of Oslo, University of Groningen, and the Medicine University of Toronto. We purposefully selected specific research groups from particular countries to ensure diversity in our sample’s represented countries and research disciplines. Finally, we advertised the questionnaire through specific social media channels on Twitter and LinkedIn and during conference presentations that addressed researchers from particular research disciplines.
A total of 255 respondents completely or partly filled out the questionnaire. From the sample of 255, we removed the data of respondents for whom responses to essential questions were missing and data of respondents who indicated they were not involved in research. When data about non-essential questions was missing, we still kept the response and did not remove it from our sample. After eliminating the incomplete responses and the answers of respondents who did not identify themselves as researchers (thus not meeting inclusion criterion one), 135 useful responses remained for the analysis.
All 135 respondents in our sample provided written informed consent to voluntarily participate in the study. They confirmed that they understood that they could refuse to answer certain questions and that they could withdraw from the study at any time, without having to give a reason. All respondents also confirmed that the information they provided might be used for scientific publications and presentations and that they agreed that the anonymized research data would be shared openly through the 4TU.Research Data repository. The final dataset as well as the used questionnaire are publicly available (Digital Object Identifier (DOI): https://doi.org/10.4121/1a8dffa5-0452-48fc-aaf1-2c2d7f10c886.v1). The study setup was approved by the Human Research Ethics Committee of Delft University of Technology under committee approval number 1968.
For our analysis, we examined descriptive statistics and Chi-Square tests using IBM SPSS Statistics version 26. Since our data appeared not to meet several assumptions for alternative, more advanced tests (e.g., Principle Component Analysis or multiple regression), we did not conduct additional tests (also see the section Research Limitations).
Sample
Table 1 provides demographic and background information about the respondents participating in the questionnaire. The percentages refer to the ratio of a particular characteristic in relation to the complete sample. The table depicts that most respondents are in the age group of 31 to 40 (37%), while also many respondents were 30 or younger (25.9%) or 41 to 50 years old (23.7%). The distribution of males and females was nearly equal. The respondents came from various countries, most of them belonging to the Germanic Europe cluster (43%) (see Dorfman et al., 2004; House et al., 2004). Most respondents have a PhD degree (57%) or a Master’s degree (38.5%). For those who only have a Master’s degree, most of them participated in education on open data and open science. Moreover, these respondents could very well be PhD-candidates that have gained experience with open data sharing but that have not yet completed their PhD, as indicated by the data collected through our MOOC (e.g., this was visible in assignments that the MOOC participants had to complete as part of the MOOC). The large majority of the respondents are academic researchers (85.9%), including Ph.D. candidates (31.1%), Assistant Professors (14.1%), Associate Professors (12.6%), and Full Professors (13.3%). In total, 89.6% reported at least a certain level of expertise concerning sharing research data openly. About 45.2% reported above-average or considerable expertise.
Respondents’ Demographics and Background.
Measures
Table 2 depicts the measures used in this study (see Appendix A for the questionnaire used in this study). First, we asked the respondents for their experience with openly sharing research data in the past and how relevant it would be to share their research data openly. Then we asked the respondents to estimate how other people would feel about them sharing their research data and how they felt about other researchers (not) openly sharing research data. Subsequently, we presented several statements about the potential advantages of openly sharing research data, also in relation to the COVID-19 pandemic. Thereafter, we asked how much support researchers received for openly sharing their data and the potential disadvantages of openly sharing their data. Finally, we questioned researchers about their attitude toward future open data sharing behavior. We presented our definition of open research data to our respondents at the beginning of the survey since open research data can be defined in various ways. We also provided definitions of other key concepts in the questionnaire and repeated them where needed.
Variables Surveyed in the Questionnaire.
Before sending out the questionnaire, we tested the way we operationalized research data sharing and other measures. We first involved three persons, including an expert in questionnaires and statistics, in testing the questionnaire items for understandability, upon which the questions were made more evident and non-ambiguous. Subsequently, we ran a pre-test involving five persons. No more changes were made to the questionnaire after the pre-test since the testers did not have any further comments.
Results
This section reports the results of our study. It first discusses the findings concerning researchers’ open data sharing behavior in general, followed by the findings concerning researchers’ willingness to openly share their research data in times of the COVID-19 pandemic in particular. We then compare researchers’ perceived contributions of their COVID-19-related research data to those of their non-COVID-19-related research data. Finally, we describe the influence of various factors on researchers’ willingness and ability to openly share their research data. The data underlying these results can be found in Appendix B and online through the previously shared DOI.
Open research data sharing in general
As depicted in Figure 1, most researchers in this study have openly shared (non-sensitive) research data at least once in the past (74.1%), while nearly one quarter has never done so (24.4%). The majority of all researchers who have ever shared their data openly are, on average, sharing their data yearly or a few times per year (53.3% of all researchers in the sample). In proportion to the total amount of non-sensitive data generated by researchers, most researchers (46.7%) shared between 0% and 20% of their data on average. When we exclude researchers who have never openly shared research data in the past from this number, most researchers still shared only between 0% and 20% of their research data. Of all researchers in our sample, 16.3% openly shared more than 60% of their non-sensitive research data in the past.

The frequency of researchers openly sharing their (non-sensitive) research data in the past (in percentages).
Of the researchers in our sample, 85.2% consider it likely that they will openly share research data in the future. Only 5.2% consider it unlikely to share research data openly in the future. While most researchers in our sample have shared no more than 20% of their non-sensitive research data in the past, most are more optimistic about data sharing in the future. The opinions of researchers on the proportion of research data they will openly share in the future are more divided. Nearly a quarter of the respondents (23.7%) expects to openly share 41% to 60% of all the data they will collect in the future, while 22.2% expects to openly share 61% to 80%.
Researchers’ Willingness to Openly Share Their Research Data in Times of the COVID-19 Pandemic
The percentage of researchers that has ever openly shared research data themselves (74.1%, see Results section) corresponds to the percentage of researchers that expects other researchers to openly share their research data. Nearly three-quarters (74%) of the researchers in our sample agree to some extent that they expect other researchers to openly share their reseach data whenever possible (see Figure 2, where “V” refers to the variable in Table 2). Interestingly, this number increases to 91.8% when it comes to researchers’ expectation of openly sharing COVID-19-related research by other researchers. Only 3.1% disagrees with the statement that other researchers should openly share COVID-19-related research data they have collected, opposed to 13.5% of the researchers disagreeing with this statement for research data in general. Apparently, researchers expect a higher willingness of their peers to openly share COVID-19-related research data than for other types of research data. However, when asked if other researchers openly share their research data, opinions are relatively divided: 42.2% disagrees, 17% neither disagrees nor agrees, and 40.8% agrees. Thus, researchers perceive their fellow researchers to less often share their data openly than they would find reasonable.

Researchers’ expectations of other researchers to openly share their research data (COVID-19-related or in general).
Respondents were also asked directly whether the COVID-19 pandemic changed their willingness to share their research data openly. More than half of the respondents (59.3%) stated that the COVID-19 pandemic did not influence their willingness to openly share research data, while slightly more than one-third (37.8%) believed it did (see Table 3). Out of the group with an increased willingness to share research data openly, most respondents experienced a moderate or large increase in their willingness to share their data (49.0% and 33.3%, respectively). Some researchers reported a small increase in their willingness to share their data openly (17.6%).
The Self-Reported Influence of Researchers to Openly Share Their Research Data Due to the COVID-19 Pandemic.
Researchers’ Perceived Contributions of Their COVID-19-Related and Non-COVID-19-Related Research Data
This section discusses our findings on the contributions (i.e., positive impacts) that researchers perceive their research data could have, making a distinction between both COVID-19-related research data and non-COVID-19-related research data. In general, most researchers in our sample agree that if they would openly share their research data, this would increase the pool of information available to scientists and society (94.7%) (see Figure 3). In our sample, 95.5% of the respondents agree that them openly sharing their research data will encourage the validation, verification, and falsification of research results and 75.1% agrees that this would provide decision-makers with facts to address complex, often transnational problems. When applied specifically to the situation of the COVID-19 pandemic, these numbers are lower, namely 28.7%, 26.5%, and 26.5% respectively, meaning that about one quarter of the respondents in our study believes that their data is useful for investigating the COVID-19 pandemic and for providing decision-makers with facts to address COVID-19-related problems.

Respondents’ perceived contributions of openly sharing their research data to research in general and COVID-19 research in particular.
Factors Influencing Researchers’ Willingness and Ability to Openly Share Their Research Data
Finally, we investigated the potential influence of various factors on researchers’ willingness and ability to openly share research data in relation to the COVID-19 pandemic, including disciplinary and social influences, institutional support, and the fear for potential negative consequences.
Disciplinary Influences on Openly Sharing Research Data
We examined whether the fact that a researcher’s research discipline was COVID-19-related (independent variable) was associated with the change in the researchers’ willingness to openly share research data (dependent variable) (see Table 4). We found a significant association between the COVID-19-relatedness of researchers’ research discipline and whether or not the COVID-19 pandemic led to a change in their willingness to share their research data openly:
Researchers’ Self-Reported Increase in Willingness to Openly Share Their Research Data Due to the COVID-19 Pandemic Cross-Tabulated With Whether a Researchers’ Research Discipline is COVID-19-Related.
Four responses missing.
The results also show that when multiple respondents came from the same research discipline, they sometimes had different opinions on whether their research discipline was COVID-19 related. For example, four respondents considered Economics to be COVID-19-related, while two did not. This difference may have to do with the sub-disciplines within this discipline. Some researchers in Economics may be investigating the effects of the COVID-19 pandemic on the economy, while others may be addressing other areas within Economics. The respondents mentioned various COVID-19-related fields, such as Medicine, Computer Science, Business Administration, Economics, and Public Administration and Political Science. At least one respondent stated that this research discipline was not related to the COVID-19 pandemic for all of these disciplines. This finding supports the hypothesis that it depends on the sub-discipline whether a respondent is conducting either COVID-19 or non-COVID-19-related research. In the sample, the respondents from other fields, such as Language and Literature, Psychology, Sociology, History, and Archeology, did not assess their discipline to be COVID-19-related. However, even within these disciplines, there may be sub-disciplines addressing the COVID-19 topics, such as how employment is changing through the pandemic (Sociology) or how societies dealt with pandemics in the past (History). This may have been the topic of investigation of researchers outside this study.
Social Influence on Openly Sharing Research Data
Additionally, social factors may influence openly sharing research data, including the social influence of supervisors and colleagues. More than three quarters of the respondents (76.3%) believes that most people who are important to them would approve it if they (would) openly share their research data in their current position (see Figure 4). However, most respondents in our sample are not encouraged that much to openly share their research data by their supervisor(s) (25.1%) or their colleagues (31.9%). These numbers are nearly similar for researchers who conduct COVID-19 pandemic-related research compared to those who do not conduct this type of research. Our findings suggest that there may be an important role for supervisors and colleagues in encouraging open data sharing (see the Discussion section).

The influence of various social factors on whether researchers openly share their research data.
Institutional Support for Openly Sharing Research Data
Institutions may support researchers in their efforts to openly share research data in various ways. We examined the influence of institutional support in the form of infrastructures, repositories, research data management, and institutional policies (see Figure 5). Approximately one-third of the respondents in our sample states that their institution provides sufficient support for openly sharing research data (31.2%), including a useful infrastructure (33.3%) and a useful repository (31.9%), with negligible differences for researchers working in a COVID-19-related research discipline compared to researchers who do not work in such a discipline. A slightly larger group of respondents agrees that their institution provides sufficient support for research data management (35.6%) and 37.8% is familiar with their institution’s open data sharing policy. Here, we also find nearly similar results for researchers working in COVID-19-related research disciplines and non-COVID-19-related research disciplines. In sum, a relatively large proportion of the respondents in our sample do not receive sufficient support for openly sharing research data. Improving these facilitating conditions might be an important factor to stimulate open data sharing behavior.

The influence of various institutional factors on whether researchers openly share their research data.
Potential Negative Consequences of Openly Sharing Research Data
Various potential negative consequences of openly sharing research data may inhibit researchers from sharing their data. We investigated the influence of potential negative consequences, including researchers’ fear of the misinterpretation and misuse of their research data, researchers’ concerns about losing an advantage, and researchers’ fear of other researchers’ findings errors in the data (see Figure 6). The researchers in our sample seem to be most concerned about the possible misinterpretation of their research data (44.5% states this is a concern) and the (intentional) misuse of their data (44.5% states this is a concern). The respondents are slightly less concerned that others will find errors in their data, although our findings still suggest that these concerns influence the data sharing behavior of 26.7% of the researchers in our sample. Our findings show that various factors related to potential negative consequences of openly sharing research data and these should be considered when developing incentives and policies that intend to stimulate openly sharing research data. We did not identify significantly different results for researchers who conduct COVID-19-related research compared to researchers who do not carry out such type of research.

The influence of various potential negative consequences on whether researchers openly share their research data.
Discussion
This section provides a brief summary of this study’s results, its theoretical implications, its practical implications, and the limitations and avenues for future research.
Discussion of Study Results
Using a questionnaire (
We examined various factors that may potentially influence researchers’ willingness and ability to openly share research data in relation to the COVID-19 pandemic, including research discipline, social influences, institutional support, and the fear for potential negative consequences. Out of these factors, we only identified a clear difference in data sharing behavior between the respondents who stated that their research was COVID-19-related compared to the respondents who stated that their research was not COVID-19-related for the research discipline-related factors. For the factors related to social influences, institutional support, and the fear of negative consequences, the findings are nearly similar for researchers who conduct COVID-19 pandemic-related research compared to those who do not conduct this type of research. This means that social influences, institutional support, and the fear of negative consequences were nearly similar for researchers working on COVID-19-related research compared to researchers working on other types of research.
In this study, more than half of the respondents (59.3%) stated that the COVID-19 pandemic did not influence their willingness to openly share their research data, while slightly more than one-third (37.8%) believed it did. At the same time, the odds of a researcher openly sharing research data were 2.58 times higher if they worked in a COVID-19-related research discipline than if they worked in a non-COVID-19-related research discipline. However, the increased chances of openly sharing research data for researchers who work in a COVID-19-related research discipline do not necessarily need to be caused by the COVID-19 pandemic itself as other factors that we did not include in this study may also play a role, requiring caution in the findings’ interpretation. One other factor that may play a role and that we did not investigate concerns the country that the researcher is living in and how much it has been affected by the COVID-19 pandemic. For example, measures to reduce the impact of COVID-19 have been quite diverse across countries and the feeling of urgency to openly share research data in different countries may have influenced researchers in different degrees.
Theoretical Implications
Previous research already shows how various factors influence researchers’ decisions to openly share their research data (e.g., Haeusermann et al., 2017; Piwowar et al., 2007; Savage & Vickers, 2009). Tenopir et al. (2011, p. e21101) find that “scientists do not make their data electronically available to others for various reasons, including insufficient time and lack of funding.”Sayogo and Pardo (2013) identify data management skills and organization support as well as the acknowledgment of the data set’s originator in terms of appreciation and legal and policy requirements as the major determinants affecting researchers’ willingness to openly share their research data. Moreover, some studies have focused specifically on factors influencing researchers’ willingness to openly share their research data in the context of epidemics and pandemics, including Zika, Ebola, and COVID-19 (Lucas-Dominguez et al., 2021). For example, the urgent need to combat the COVID-19 pandemic may have shown the demand for COVID-19-related research data by research communities, public health practitioners, and policymakers, which may have led to an increase in openly sharing such datasets (see Curioso & Carrasco-Escobar, 2020; RDA COVID-19 Working Group, 2020; Temiz & Gurdur Broo, 2020).
Our study complements existing studies concerning the influence of the COVID-19 pandemic on researchers’ willingness and ability to openly share their research data. Rather than discussing the
Inspired by the Unified Theory of Acceptance and Use of Technology (UTAUT) (Venkatesh et al., 2003), we examined whether some specific factors from this model explained open research data sharing behavior between COVID-19 researchers and non-COVID-19 researchers. However, our empirical data does not identify clear differences in social influences, institutional support (including facilitating conditions and effort expectancy), or the fear of negative consequences of openly sharing research data (including performance-related and trust-related factors) for researchers conducting COVID-19-related research compared to researchers conducting other types of research. While previous research shows that various efforts have been made to establish infrastructure for the real-time data publication of COVID-19 data (Gardner et al., 2021), this research shows that institutional repositories still insufficiently support researchers in their data sharing activities.
A central assumption of this study is that an increase in researchers’ willingness and ability to openly share their research data will lead to more researchers who actually openly share their research data, and subsequently to increased numbers of openly shared research datasets. It may be theorized from the Theory of Planned Behavior (Ajzen, 1985, 1991) that attitudes, subjective norms, and behavioral control lead to intentions, which subsequently lead to actual behavior. However, while we did cover attitudes and norms in our questionnaire and we did question researchers about their
This study complements the research carried out by Lucas-Dominguez et al. (2021) and Gkiouras et al. (2020) who examined how many datasets underlying scientific publications concerning COVID-19 research have been shared openly. Lucas-Dominguez et al. (2021) found that while the number of articles published on COVID-19 research increased enormously, in their sample of 5,905 records only 13.6% were accompanied by the underlying open research data, and only 1.2% was accompanied by reusable data. Gkiouras et al. (2020) examined a sample of 140 articles, of which only one article (0.7%) offered complete open data. Lucas-Dominguez et al. (2021) warn that while health emergencies such as COVID-19 lead to an increase in the number of articles published open access, they neither lead to a proportional increase in open research datasets, nor to an improvement of the data’s quality and reusability.
Practical Implications
This study identified the perceived influence of various factors on researchers’ willingness and ability to openly share research data in relation to the COVID-19 pandemic, including disciplinary and social influences, institutional support, and the fear of potential negative consequences of open data sharing. In this section, we discuss three practical recommendations that we derived from these findings for policymakers responsible for open research data policies.
First, our study shows that there may be a key role for supervisors and colleagues in encouraging open data sharing. At the moment, it appears that many supervisors and colleagues do not encourage their fellow researchers to openly share their research data. Various theories, such as Innovation Diffusion Theory (Rogers, 1962) and the Unified Theory of Technology Acceptance (Venkatesh et al., 2003), suggest that social factors can influence human behavior. We hypothesize that such social factors could also include the behavior of researchers’ peers, colleagues, supervisors, and the norms of the social system or research disciplinary cultures. Based on our findings, we recommend policymakers to develop programs that actively reward and compensate (academic and non-academic) researchers to openly share their research data. Such rewards can be both monetary and non-monetary and can be based on competition, peer pressure, or collaboration. For instance, a supervisor of a university’s research team could evaluate the proportion of datasets shared by the team and assign a reward (e.g., an additional conference allowed to be visited, a bonus, a mention in the university’s newsletter, or an award) for the team member who shared the largest proportion of the non-sensitive research data he or she collected that year. Such programs that stimulate openly sharing research data should be adapted to the environment they are implemented in and should comply with the standards and rules that are common in that environment. For instance, assigning a reward that is not valued in a certain research department is likely not to have any influence on the research data sharing behavior of the researchers in that department. Equity Theory (Adams, 1963; Walster et al., 1973, 1976) may be used as a basis to develop reward and compensation programs for openly sharing research data.
Second, our study shows that a relatively large proportion of the researchers in this study do not receive sufficient institutional support for openly sharing research data. We particularly studied institutional support in the form of institutional infrastructures, repositories, research data management support, and institutions’ open data sharing policies, while also considering institutional support in general. Based on our findings, we recommend policymakers who are responsible for institutional open research data policies (e.g., within a university or research institution) to ensure that supportive open research data infrastructures, repositories, and management processes are being co-created by (1) the researchers within their institution who should be using them, (2) experienced ICT developers, (3) research data managers and librarians, and (4) open data and open science policymakers. The infrastructures, repositories, and management processes to be developed should take as much work out of the hands of the researchers as possible. The co-creation by different stakeholders should ensure that all of their interests are being considered. This recommendation is consistent with previous research that states that research data infrastructures should be sustainable and robust for long-term usage (Arzberger et al., 2004) and data repositories should foster a culture of both data sharing and reuse (Joo et al., 2017). Previous research also found that organizational support for data management can support data sharing and reduce the effort to share data (Sayogo & Pardo, 2013), just like using software, equipment and data repositories can reduce the effort required from researchers in openly sharing their data (da Costa & Lima Leite, 2019).
Third, this study examined various factors related to potential negative consequences of openly sharing research data, including the misuse and misinterpretation of open research data by other researchers, the fear of losing an advantage when openly sharing research data, and the fear that other researchers will find errors in the data. Such factors may lead to reluctance among researchers to openly share their research data and, therefore, we recommend open data policymakers who develop incentives and policies that intend to stimulate openly sharing research data to not only consider the potential benefits of openly sharing research data, but also the potential negative consequences. In scientific publishing, it is already common to criticize or point at the limitations of the research conducted by fellow researchers. Using existing standards for article referencing (e.g., those of the APA), it is also common for scientists to refer to the existing research articles written by their peers that they build upon in their own scientific publications. Furthermore, more and more scientific articles are being made accessible to anyone (i.e., open access). This existing scientific publishing system contrasts the current “research data sharing system.” For instance, building upon, reusing, and referring to datasets created and archived in data repositories by other researchers (i.e., data citation) is less common in many research disciplines (Robinson-García et al., 2016), which contributes to researchers’ fear of losing an advantage when openly sharing their data. Moreover, our study shows that many researchers still fear that other researchers will spot errors in their open research datasets, while spotting errors could also be viewed as a learning opportunity and a way to further develop scientific insights in collaboration with peers. Some relevant steps have already been taken to develop toward a research data sharing system that considers the potential negative consequences of openly sharing research data, including the development of data citations standards (Parsons et al., 2019), while more work is to be done in this area (e.g., see Buneman et al., 2020; Parsons et al., 2019).
Research Limitations and Avenues for Future Research
This study has a number of limitations. First, we left the decision of whether the researcher’s research discipline is COVID-19-related up to the respondent. For most research disciplines, this is difficult to assess as an outsider. In addition, we found that respondents within the same research discipline often had a different opinion on whether their research was COVID-19-related or not. Therefore, the increased odds for a researcher to openly share data when their research was COVID-19-related perhaps cannot be attributed to differences in research disciplinary practices. For example, differences in standards used per discipline (see Nelson, 2009) or in preferences to conduct research based on second-hand data than in some fields (see Curty et al., 2017) do not explain the increased odds on openly sharing research data in our study. Instead, our study suggests that factors such as the urgent demand for COVID-19-related data and personal motivations might play a more critical role. A recommendation for future research would be to consider degrees of relatedness, where some research disciplines are more related to COVID-19 than others. We did not consider such degrees in our analysis. Furthermore, a researcher may work in a research discipline that is COVID-19-related but may not carry out COVID-19-related research himself or herself. Further research should address this issue and use a more fine-grained assessment of a researcher’s level of involvement in COVID-19-related research.
This quantitative study investigates correlations between research disciplines and data sharing behavior, yet the questionnaire does not allow us to conclude causality. As a consequence, this study does not yield the exact reasons for some researchers’ changed attitude toward data sharing. In this study, we focused on the value of open research data for gaining new insights useful in the battle against COVID-19. However, researchers may also openly share their data during a pandemic for another reason. Many researchers cannot collect data themselves due to COVID-19 restrictions and happily use the data collected and openly shared by others (Baynes & Hahnel, 2020). We recommend future research to study openly sharing research data from this perspective, as it may complement the findings from this research. Qualitative research could complement this study by examining the different factors leading to open data sharing behavior, including relevant control factors such as journal policies, funding requirements, community norms, the availability of metadata standards and data repositories, and others. Moreover, it should be examined whether the hypothesized relationship between the increased willingness and ability to openly share research data and the number of datasets shared indeed leads to more datasets being shared openly. Future research should dig deeper into the underlying relationships, for instance, through interviews, focus groups and case studies.
Another topic of consideration here is the sustainability of open data sharing behavior. Various scholars raised questions about how enduring an increase in open data sharing would be after the COVID-19 pandemic (Cutcher-Gershenfeld et al., 2020; Shmagun et al., 2021). The long-term effects are questionable because of lacking formal contracts and other long-lasting institutional arrangements that stimulate enduring open data sharing (Cutcher-Gershenfeld et al., 2020). After the COVID-19 pandemic, the demand for data may become less obvious to researchers. In addition, most researchers then still struggle with obstacles for openly sharing research data that already existed before the pandemic. Unfortunately, our data does not allow for investigating whether a relationship between the COVID-19 relatedness of a researchers’ field on the one hand and researchers’ intentions for openly sharing research data in the future on the other hand. We recommend future research to investigate the long-lasting effects of increased open data sharing for both COVID-19 and non-COVID-19-related research.
Finally, the analyses of our data have mainly been descriptive since some of the assumptions of other, more advanced tests are not met by the dataset. Obtaining more questionnaire responses could have made it possible to conduct more advanced data analysis. Furthermore, collecting additional responses would allow us to enhance the representativeness of our sample regarding different research disciplines and countries. Moreover, data sharing practices may differ between academic and non-academic researchers, but those differences could not be examined due to the study’s relatively small sample size.
Conclusions
This study aims to investigate the influence of COVID-19 pandemic-related factors on researchers’ willingness and ability to share their research data openly. A total of 135 researchers completed a global survey on this topic. Nearly three-quarters of these researchers have openly shared their research data at least once in the past, and 44% have shared research data in the 6 months preceding the study. Our data suggests that researchers expect a higher willingness of their peers to openly share COVID-19-related research data than for other types of research data. Fifty-one respondents (37.8%) stated that COVID-19 pandemic-related factors made them share their research data openly more, while 80 (59.3%) reported that pandemic-related factors did not influence their open data sharing behavior. As one of the influencing factors, we found a significant association between the COVID-19-relatedness of researchers’ research discipline and whether or not the COVID-19 pandemic led to a change in their willingness and ability to share their research data openly:
The scientific contributions of this study are as follows. First, this study goes beyond conceptual studies concerning the influence of COVID-19 pandemic-related factors on researchers’ willingness and ability to openly share their data, as it provides empirically-funded insights on this topic. As a novel scientific contribution, it demonstrates and discusses which COVID-19 pandemic-related factors may have changed researchers’ willingness and ability to share their research data openly and why some other factors appeared not to have any influence on researchers’ open data sharing behavior. Moreover, this study complements existing research concerning the proportion of datasets underlying scientific COVID-19 publications that have been shared openly (e.g., Gkiouras et al., 2020; Lucas-Dominguez et al., 2021). While these existing studies take the perspective of the
Gaining more insight into the COVID-19 pandemic-related factors that influenced the decision of researchers to openly share their research data is critical since these insights can be translated to recommendations stimulating researchers to openly share their research data after the pandemic. As a practical contribution, this study provides recommendations that open research data policymakers can use to support and encourage open research data sharing in post-COVID-19 times. Based on our findings, we first recommend policymakers to develop programs that actively reward (academic and non-academic) researchers to openly share their research data. Second, policymakers who are responsible for institutional open research data policies (e.g., within a university or research institution) are advised to ensure that supportive open research data infrastructures, repositories, and management processes are being co-created by (1) the researchers within their institution who should be using them, (2) experienced ICT developers, (3) research data managers and librarians, and (4) the institution’s open data and open science policymakers. Third, we recommend open data policymakers who develop incentives and policies that intend to stimulate openly sharing research data to not only consider the potential benefits of openly sharing research data, but also the potential negative consequences that may hinder researchers at the individual level. These recommendations allow policymakers to positively influence open research data sharing behavior, with the ultimate goal of creating more societal, operational, and economic value.
Supplemental Material
sj-docx-1-sgo-10.1177_21582440241234985 – Supplemental material for Researchers’ Willingness and Ability to Openly Share Their Research Data: A Survey of COVID-19 Pandemic-Related Factors
Supplemental material, sj-docx-1-sgo-10.1177_21582440241234985 for Researchers’ Willingness and Ability to Openly Share Their Research Data: A Survey of COVID-19 Pandemic-Related Factors by Anneke Zuiderwijk in SAGE Open
Footnotes
Declaration of Conflicting Interests
Funding
Ethics Statement
Supplemental Material
References
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
