Public Repositories of Scientific Data: the case of FigShare
Author: Cassio Rafael C. dos Santos
FigShare: FigShare is an OpenScience online Platform, in which researchers, professors and students can access and share scientific papers with their respective Figures, Tables and, in some cases, raw data. Therefore, this platform works as a great scientific repository, allowing scientists to publicize the outcomes of their research, while allowing other researchers and students to replicate some surveys through accessing these data. Therefore, FigShare is an important tool to ensure the maximum publicity, transparency and reproducibility of Science in different areas, in a collaborative way between everyone.
Scientific Paper Description: In FigShare Platform, we used raw data from a paper entitled: "Agroforestry Practices Promote Biodiversity and Natural Resource Diversity in Atlantic Nicaragua". In this research, the authors assessed soil quality and diversity attributes, comparing agroforestry systems with secondary forest and pasture, in Nicaragua. To this end, they performed several samplings on many farms. In these farms, they observed four types of agroforestry systems (AFS): Cacao domint AFS, Coconut dominant AFS, Plantain dominant AFS and Mixed fruits AFS. To make the assessments simpler, the authors shrunk the data from the different AFS, turning them one single group to be compared to Forest and Pature. Some examples of the results obtained by this paper area presented below.
A Different Approach Proposal: Although they have found some interesting outcomes, we believe the raw data were underutilized, especially by shrinking the AFS groups into only one group. Therefore, we tried to propose an alternative assessment approach using the raw data of this paper, for the following soil variables: C and N concentration and stock, C/N ratio, soil bulk density and soil pH. By performing this new assessment, we found significant differences between the different AFS, denoting these systems need to be evaluated differently.
Raw Data and Code used
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