Abstract
Analysis based on primary biodiversity data is essential to understand the climate changes impact on biodiversity. Two challenges are involved in the use of such data. The first challenge is the identification of essential aspect of occurrences, such as, localization, institution responsible, which is important to measure the suitability of such data to the analysis which will be carried on using such data. In this sense, we propose a framework to perform data mining analysis in order to obtain such information without previous knowledge about the database, which can be integrated with different data portals using web services. We performed an evaluation with a subset of primary data available at GBIF Data Portal, which showed trends in information about occurrence location and the institution which is responsible for the occurrence.
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Fontes, S.G., Stanzani, S.L., Correa, P.L.P. (2015). A Data Mining Framework for Primary Biodiversity Data Analysis. In: Rocha, A., Correia, A., Costanzo, S., Reis, L. (eds) New Contributions in Information Systems and Technologies. Advances in Intelligent Systems and Computing, vol 353. Springer, Cham. https://doi.org/10.1007/978-3-319-16486-1_81
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DOI: https://doi.org/10.1007/978-3-319-16486-1_81
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-16485-4
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