Compliance Culture or Culture Change? The role of funders in improving data management and sharing practice amongst researchers

Promoting Data Sharing: The Moral Obligations of Public Funding Agencies

Sharing research data has great potential to benefit science and society. However, data sharing is still not common practice. Since public research funding agencies have a particular impact on research and researchers, the question arises: Are public funding agencies morally obligated to promote data sharing? We argue from a research ethics perspective that public funding agencies have several pro tanto obligations requiring them to promote data sharing. However, there are also pro tanto obligations that speak against promoting data sharing in general as well as with regard to particular instruments of such promotion. We examine and weigh these obligations and conclude that all things considered funders ought to promote the sharing of data. Even the instrument of mandatory data sharing policies can be justified under certain conditions.

Where Do Early Career Researchers Stand on Open Science Practices? A Survey Within the Max Planck Society

Open science (OS) is of paramount importance for the improvement of science worldwide and across research fields. Recent years have witnessed a transition toward open and transparent scientific practices, but there is still a long way to go. Early career researchers (ECRs) are of crucial relevance in the process of steering toward the standardization of OS practices, as they will become the future decision makers of the institutional change that necessarily accompanies this transition. Thus, it is imperative to gain insight into where ECRs stand on OS practices. Under this premise, the Open Science group of the Max Planck PhDnet designed and conducted an online survey to assess the stance toward OS practices of doctoral candidates from the Max Planck Society. As one of the leading scientific institutions for basic research worldwide, the Max Planck Society provides a considerable population of researchers from multiple scientific fields, englobed into three sections: biomedical sciences, chemistry, physics and technology, and human and social sciences. From an approximate total population of 5,100 doctoral candidates affiliated with the Max Planck Society, the survey collected responses from 568 doctoral candidates. The survey assessed self-reported knowledge, attitudes, and implementation of different OS practices, namely, open access publications, open data, preregistrations, registered reports, and replication studies. ECRs seemed to hold a generally positive view toward these different practices and to be interested in learning more about them. Furthermore, we found that ECRs' knowledge and positive attitudes predicted the extent to which they implemented these OS practices, although levels of implementation were rather low in the past. We observed differences and similarities between scientific sections. We discuss these differences in terms of need and feasibility to apply these OS practices in specific scientific fields, but additionally in relation to the incentive systems that shape scientific communities. Lastly, we discuss the implications that these results can have for the training and career advancement of ECRs, and ultimately, for the consolidation of OS practices.

Promoting data sharing among Indonesian scientists: A proposal of generic university-level Research Data Management Plan (RDMP)

Every researcher needs data in their working ecosystem, but despite of the resources (funding, time, and energy), that they have spent to get the data, only a few are putting more real attention to data management. This paper is mainly describing our recommendation of RDMP document at university level. This paper would be a form of our initiative to be developed at university or national level, which also in-line with current development in scientific practices mandating data sharing and data re-use.

Researchers can use this article as an assessment form to describe the setting of their research and data management. Researcher can also develop more detail RDMP to cater specific project's environment. In this Research Data Management Plan (RDMP), we propose three levels of storage: offline working storage, offline backup storage and online-cloud backup storage, located on a shared-repository. We also propose two kinds of cloud repository: a dynamic repository to store live data and a static repository to keep a copy of final data.

Hopefully, this RDMP could solve problems on data sharing and preservation, and additionally could increase researchers' awareness about data management to increase the value and impact of their researches.