Junior research group: Open science

Increasingly, researchers are expected to make their research data openly available. However, scientific fields differ in their research practices and norms for sharing research data. We provide quantitative evidence of differences in data practices and the public sharing of research data at a granularity of field-specificity that is rarely reported in open data surveys. Based on a survey of 8,822 researchers at German Universities, we find considerable variation, within and across disciplines, of data practices and rates of open data sharing. Our findings underline that in order to evaluate rates of public data sharing, a better understanding of the embedding of public data sharing into field-specific research practices is needed.

Often, bibliometric mapping studies remain at a very abstract level when assessing the validity or accuracy of the generated maps. In this case study of citation-based mappings of a research specialty, we dig deeper into the topical structures generated by the chosen mapping approaches and examine their correspondence to a sociologically informed understanding of the research specialty in question. Our analysis highlights the variety of types of topical relatedness and epistemic interdependency that citations can stand for. Unless we assume that invasion biology is unique, our analysis suggests that global algorithmic field classification approaches that use citation links indiscriminately may struggle to reconstruct research specialties.

The use of citations as indicators of topical relatedness of publications is common in the algorithmic mapping of the structure of science. References to source documents, however, may serve a variety of epistemic functions, and hence represent rather different dimensions of topical relatedness, such as the research methods used, the empirical objects studied, the theoretical resources build on, the research questions pursued, or the external motivation for and relevance of the work. In this case study, we explore the diversity in topical dimensions along which publications are linked in citation networks, by coding the epistemic function of in-text citations. [...]

This contribution discusses what it means to understand the sharing of research data not only as a social practice, but as an integral part of research practices. It reviews recent literature, assesses progress made and remaining gaps, and outlines a re-conceptualization of data sharing that results from taking the content of research seriously.

In our research, we examine the role of sharing of epistemic resources, such as research data, code, samples, or method know-how, for knowledge production in scientific fields. Our focus is on resources that are created in the process of research and shared with researchers or research groups outside of the original context of creation of the resource. Based on a field-comparative ethnographic study of research specialties in the sciences that differ in their epistemic practices, we examine the causal link between epistemic conditions of research on the one hand, and reoccurring patterns of sharing on the other. In our contribution we discuss challenges encountered when deriving causal explanations of field differences in sharing.

Increasingly, researchers are expected to make their research data openly available. However, scientific fields differ in their research practices and norms for sharing research data. We provide quantitative evidence of differences in data practices and the public sharing of research data at a granularity of field-specificity that is rarely reported in open data surveys. Based on a survey of 8,822 researchers at German Universities, we find considerable variation, within and across disciplines, of data practices and rates of open data sharing. Our findings underline that in order to evaluate rates of public data sharing, a better understanding of the embedding of public data sharing into field-specific research practices is needed.

Increasingly, researchers are expected to make their research data openly available. In this keynote, I provide an overview of the state-of-the-art in research on the sharing of research data with a particular emphasis on understanding field-specific motivations of researchers to share or not to share.

For a long time the scientific production process has been known as resting on the "shoulders of giants" (Merton 1965). But how do scientists know that these giants are actually giants and not dwarfs on stilts? Where do they get their firm footing in science from? How do they know they won't hit hard ground? They do trust in the giants. [...] This paper aims to draw a systematic picture of the role of scientific trust within research specialties. By its field comparative approach it offers a concept of trust for science studies which can be discussed, expanded and modified to apply to further research specialties, disciplines and areas of scientific work.

The use of citations as indicators of topical relatedness of publications is common in the algorithmic mapping of the structure of science. References to source documents, however, may serve a variety of epistemic functions, and hence represent rather different dimensions of topical relatedness. They may pertain to the research methods used, the empirical objects studied, the theoretical resources build on, the research questions pursued, or the external motivation for and relevance of the work. In this qualitative case study, we explore the diversity in topical dimensions along which publications are linked in citation networks.

Open science advocates and an increasing number of political stakeholders and research funding agencies encourage researchers to publicly share the various instantiations of scientific knowledge that are generated during the research process, in particular research data, but also computer code, method protocols, or material specimens. Critical for the success of this vision is the readiness of research groups to share those tools and resources that they have created. The study I will present seeks to contribute to a theory of field-specific forms of sharing by looking specifically at the question how sharing decisions are influenced by the epistemic conditions for research in a field.