Abstract
To manage raw data from Neuroscience experiments we have to cope with the heterogeneity of data formats and the complexity of additional metadata, such as its provenance information, that need to be collected and stored. Although some progress has already been made toward the elaboration of a common description for Neuroscience experimental data, to the best of our knowledge, there is still no widely adopted standard model to describe this kind of data. In order to foster neurocientists to find and to use a structured and comprehensive model with a robust tracking of data provenance, we present a brief evaluation of guidelines and models for representation of raw data from Neuroscience experiments, focusing on how they support provenance tracking.
This work was produced at FAPESP Research, Innovation and Dissemination Center for Neuromathematics (grant 2013/07699-0, S. Paulo Research Foundation).
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Ruiz-Olazar, M., Rocha, E.S., Rabaça, S.S., Ribas, C.E., Nascimento, A.S., Braghetto, K.R. (2016). A Review of Guidelines and Models for Representation of Provenance Information from Neuroscience Experiments. In: Mattoso, M., Glavic, B. (eds) Provenance and Annotation of Data and Processes. IPAW 2016. Lecture Notes in Computer Science(), vol 9672. Springer, Cham. https://doi.org/10.1007/978-3-319-40593-3_26
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DOI: https://doi.org/10.1007/978-3-319-40593-3_26
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