Many published research results are false (Ioannidis, 2005), and controversy continues over the roles of replication and publication policy in improving the reliability of research. Addressing these problems is frustrated by the lack of a formal framework that jointly represents hypothesis formation, replication, publication bias, and variation in research quality. We develop a mathematical model of scientific discovery that combines all of these elements.
This model provides both a dynamic model of research as well as a formal framework for reasoning about the normative structure of science. We show that replication may serve as a ratchet that gradually separates true hypotheses from false, but the same factors that make initial findings unreliable also make replications unreliable. The most important factors in improving the reliability of research are the rate of false positives and the base rate of true hypotheses, and we offer suggestions for addressing each. Our results also bring clarity to verbal debates about the communication of research.
Surprisingly, publication bias is not always an obstacle, but instead may have positive impacts—suppression of negative novel findings is often beneficial. We also find that communication of negative replications may aid true discovery even when attempts to replicate have diminished power. The model speaks constructively to ongoing debates about the design and conduct of science, focusing analysis and discussion on precise, internally consistent models, as well as highlighting the importance of population dynamics.
URL : Replication, Communication, and the Population Dynamics of Scientific Discovery
DOI : 10.1371/journal.pone.0136088
29 août 2015
· 12 h 43 min
The research community needs reliable, standard ways to make the data produced by scientific research available to the community, while getting credit as data authors. As a result, a new form of scholarly publication is emerging: data publishing. Data pubishing – or making data long-term accessible, reusable and citable – is more involved than simply providing a link to a data file or posting the data to the researchers web site.
In this paper, we define what is needed for proper data publishing and describe how the open-source Dataverse software helps define, enable and enhance data publishing for all.
URL : http://scholar.harvard.edu/mercecrosas/publications/dataverse-4-defining-data-publishing
27 août 2015
· 20 h 45 min
Sharing individual-level data from clinical and public health research is increasingly being seen as a core requirement for effective and efficient biomedical research. This article discusses the results of a systematic review and multisite qualitative study of key stakeholders’ perspectives on best practices in ethical data sharing in low- and middle-income settings.
Our research suggests that for data sharing to be effective and sustainable, multiple social and ethical requirements need to be met. An effective model of data sharing will be one in which considered judgments will need to be made about how best to achieve scientific progress, minimize risks of harm, promote fairness and reciprocity, and build and sustain trust.
URL : Best Practices for Ethical Sharing of Individual-Level Health Research Data From Low- and Middle-Income Settings
Alternative location : http://m.jre.sagepub.com/content/10/3/302
27 août 2015
· 20 h 41 min
The abundance of South African clinical and public health research data has the potential to unlock important and valuable future advances in biomedical science. Amid increasing calls for more effective sharing of individual-level data, commitment to promote access to research data is evident within South Africa’s public research sector, but national guidance and regulation are absent.
This qualitative study examined the perceptions, experiences and concerns of 32 research stakeholders about data-sharing practices. There was consensus about the utility of data sharing in publicly funded health research. However, disparate views emerged about the possible harms and benefits of sharing data and how these should be weighed. The relative dearth of policies governing data-sharing practices needs to be addressed and a framework of support developed that incentivizes data-sharing practices for researchers that are both ethical and effective.
URL : Developing Ethical Practices for Public Health Research Data Sharing in South Africa
Alternative location : http://m.jre.sagepub.com/content/10/3/290
27 août 2015
· 20 h 36 min
The Thailand Major Overseas Programme coordinates large multi-center studies in tropical medicine and generates vast amounts of data. As the data sharing movement gains momentum, we wanted to understand attitudes and experiences of relevant stakeholders about what constitutes good data sharing practice. We conducted 15 interviews and three focus groups discussions involving 25 participants and found that they generally saw data sharing as something positive.
Data sharing was viewed as a means to contribute to scientific progress and lead to better quality analysis, better use of resources, greater accountability, and more outputs. However, there were also important reservations including potential harms to research participants, their communities, and the researchers themselves. Given these concerns, several areas for discussion were identified: data standardization, appropriate consent models, and governance.
URL : Journal of Empirical Research on Human Research Ethics-2015-Cheah-278-89
Alternative location : http://m.jre.sagepub.com/content/10/3/278
27 août 2015
· 20 h 32 min