There has considerable interest in bringing low/middle-income countries (LMIC) scientists into discussions on Open Data - both as contributors and users. The establishment of data sharing practices within LMIC research institutions is vital for the development of an Open Data landscape in the Global South. Nonetheless, many LMICs have significant challenges - resource provision, research support and extra-laboratory infrastructures. These low-resourced environments shape data sharing activities, but are rarely examined within Open Data discourse. In particular, little attention is given to how these research environments shape scientists' perceptions of data sharing (dis)incentives. This paper expands on these issues of incentivizing data sharing, using data from a quantitative survey disseminated to life scientists in 13 countries in sub-Saharan Africa. This interrogated not only perceptions of data sharing amongst LMIC scientists, but also how these are connected to the research environments and daily challenges experienced by them. The paper offers a series of analysis around commonly cited (dis)incentives such as data sharing as a means of improving research visibility; sharing and funding; and online connectivity. It identifies key areas that the Open Data community need to consider if true openness in research is to be established in the Global South.
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http://dx.doi.org/10.1080/11287462.2018.1441780 | DOI Listing |
NPJ Digit Med
January 2025
Biomedical Data Science Center, Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland.
The use of synthetic data is a promising solution to facilitate the sharing and reuse of health-related data beyond its initial collection while addressing privacy concerns. However, there is still no consensus on a standardized approach for systematically evaluating the privacy and utility of synthetic data, impeding its broader adoption. In this work, we present a comprehensive review and systematization of current methods for evaluating synthetic health-related data, focusing on both privacy and utility aspects.
View Article and Find Full Text PDFSci Data
January 2025
Department of Engineering Technology, University of Houston, Houston, TX, USA.
Functional near-infrared spectroscopy (fNIRS) is an increasingly popular neuroimaging technique that measures cortical hemodynamic activity in a non-invasive and portable fashion. Although the fNIRS community has been successful in disseminating open-source processing tools and a standard file format (SNIRF), reproducible research and sharing of fNIRS data amongst researchers has been hindered by a lack of standards and clarity over how study data should be organized and stored. This problem is not new in neuroimaging, and it became evident years ago with the proliferation of publicly available neuroimaging datasets.
View Article and Find Full Text PDFBMJ Open
January 2025
Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.
Introduction: The escalating resistance of microorganisms to antimicrobials poses a significant public health threat. Strategies that use biomarkers to guide antimicrobial therapy-most notably Procalcitonin (PCT) and C-reactive protein (CRP)-show promise in safely reducing patient antibiotic exposure. While CRP is less studied, it offers advantages such as lower cost and broader availability compared with PCT.
View Article and Find Full Text PDFClin Microbiol Infect
January 2025
Infectious Diseases and Microbiology Division, Hospital Universitario Virgen Macarena; Department of Medicine, University of Seville; Instituto de Biomedicina de Sevilla (IBiS)/Consejo Superior de Investigaciones Científicas (CSIC), Seville, Spain; CIBERINFEC, Instituto de Salud Carlos III, Madrid, Spain.
Background: Data sharing accelerates scientific progress and improves evidence quality. Even though journals and funding institutions require investigators to share data, only a small part of studies made their data publicly available upon publication. The procedures necessary to share retrospective data for re-use in secondary data analysis projects can be cumbersome.
View Article and Find Full Text PDFChaos
January 2025
Department of Applied Mathematics, College of Applied Sciences, Kyung Hee University, Yongin 17104, Republic of Korea.
Investment in resources is essential for facilitating information dissemination in real-world contexts, and comprehending the influence of resource allocation on information dissemination is, thus, crucial for the efficacy of collaborative networks. Nonetheless, current studies on information dissemination frequently fail to clarify the complex interplay between information distribution and resources in network contexts. In this work, we establish a resource-based information dissemination model to identify the complex interplay by examining the propagation threshold and equilibriums.
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