Saarnak, Christopher4; Utzinger, Jürg3; Kristensen, Thomas K.5
1 Parasitology and Aquatic Diseases, Department of Veterinary Disease Biology, Faculty of Health and Medical Sciences, Københavns Universitet2 Section of Parasitology, Health and Development, Department of Veterinary Disease Biology, Faculty of Life Sciences, Københavns Universitet3 Swiss Tropical and Public Health Institute4 Section of Parasitology, Health and Development, Department of Veterinary Disease Biology, Faculty of Life Sciences, Københavns Universitet5 Parasitology and Aquatic Diseases, Department of Veterinary Disease Biology, Faculty of Health and Medical Sciences, Københavns Universitet
the CONTRAST experience
The scientific community is charged with growing demands regarding the management of project data and outputs and the dissemination of key results to various stakeholders. We discuss experiences and lessons from CONTRAST, a multidisciplinary alliance that had been funded by the European Commission over a 4-year period, in order to optimize schistosomiasis control and transmission surveillance in sub-Saharan Africa. From the start, project partners from Europe and Africa set out an ambitious goal: to sample data following standard protocols at all field sites and then sharing the data in a way that would enable all project partners to have access through a password protected Internet-based data portal. This required anonymous agreement on several common standardised sample forms, ranging from the mundane but important issue of using the same units of measurement to more complex challenges, for instance agreeing on the same protocols for double-treatment of praziquantel in different settings. With the experiences gained by the CONTRAST project, this paper discusses issues of data management and sharing in research projects in the light of the current donor demand, and offers advice and specific suggestions for similar interdisciplinary research projects.
Acta Tropica, 2013, Vol 128, Issue 2, p. 407-411
The Faculty of Health and Medical Sciences; Data sampling; Africa; Data sharing; Database management; Data curation; Schistosomiasis; Standard protocols