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Based on a communication-centered approach, this article examines how researchers approach societal impact, that is, what they think about societal impact in research governance, what their societal goals are, and how they use communication formats. Hence, this study offers empirical evidence on a group that has received remarkably little attention in the scholarly discourse on the societal impact of research—academic researchers. Our analysis is based on an empirical survey among 499 researchers in Germany conducted from April to June 2020. We show that most researchers regard societal engagement as part of their job and are generally in favor of impact evaluation. However, few think that societal impact is a priority at their institution, and even fewer think that institutional communication departments reach relevant stakeholders in society. Moreover, we show that researchers’ societal goals and use of communication formats differ greatly between their disciplines and the types of organization that they work at. Our results add to the ongoing metascientific discourse on the relationship between science and society and offer empirical support for the hypothesis that assessment needs to be sensitive to disciplinary and organizational context factors.

It is widely acknowledged that data sharing has great potential for scientific progress. However, so far making data available has little impact on a researcher’s reputation. Thus, data sharing can be conceptualized as a social dilemma. In the presented study we investigated the influence of the researcher's personality within the social dilemma of data sharing. The theoretical background was the appropriateness framework. We conducted a survey among 1564 researchers about data sharing, which also included standardized questions on selected personality factors, namely the so-called Big Five, Machiavellianism and social desirability. Using regression analysis, we investigated how these personality domains relate to four groups of dependent variables: attitudes towards data sharing, the importance of factors that might foster or hinder data sharing, the willingness to share data, and actual data sharing. Our analyses showed the predictive value of personality for all four groups of dependent variables. However, there was not a global consistent pattern of influence, but rather different compositions of effects. Our results indicate that the implications of data sharing are dependent on age, gender, and personality. In order to foster data sharing, it seems advantageous to provide more personal incentives and to address the researchers’ individual responsibility.

Open access to research data has been described as a driver of innovation and a potential cure for the reproducibility crisis in many academic fields. Against this backdrop, policy makers are increasingly advocating for making research data and supporting material openly available online. Despite its potential to further scientific progress, widespread data sharing in small science is still an ideal practised in moderation. In this article, we explore the question of what drives open access to research data using a survey among 1564 mainly German researchers across all disciplines. We show that, regardless of their disciplinary background, researchers recognize the benefits of open access to research data for both their own research and scientific progress as a whole. Nonetheless, most researchers share their data only selectively. We show that individual reward considerations conflict with widespread data sharing. Based on our results, we present policy implications that are in line with both individual reward considerations and scientific progress.

The acceptance and adoption of a standard like DDI highly depends on the availability of software tools to use it. The DDI Developers Community is a part of the DDI Alliance where software developers from around the world can meet and swap ideas on working with DDI in various programming environments and languages. In this session we like to give you an introduction to our work and present you a selection of available tools. This Session will give you an overview of tools available from the community. Most of the presenters will be available during the subsequent poster session for detailed questions or further demonstrations of their tools.

Academic data sharing is a way for researchers to collaborate and thereby meet the needs of an increasingly complex research landscape. It enables researchers to verify results and to pursuit new research questions with “old” data. It is therefore not surprising that data sharing is advocated by funding agencies, journals, and researchers alike. We surveyed 2661 individual academic researchers across all disciplines on their dealings with data, their publication practices, and motives for sharing or withholding research data. The results for 1564 valid responses show that researchers across disciplines recognise the benefit of secondary research data for their own work and for scientific progress as a whole — still they only practice it in moderation. An explanation for this evidence could be an academic system that is not driven by monetary incentives, nor the desire for scientific progress, but by individual reputation — expressed in (high ranked journal) publications. We label this system a Reputation Economy. This special economy explains our findings that show that researchers have a nuanced idea how to provide adequate formal recognition for making data available to others — namely data citations. We conclude that data sharing will only be widely adopted among research professionals if sharing pays in form of reputation. Thus, policy measures that intend to foster research collaboration need to understand academia as a reputation economy. Successful measures must value intermediate products, such as research data, more highly than it is the case now.