Accounting for biogeographical ignorance within biodiversity modelling

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Researchers have developed the first Maps of Biogeographical Ignorance (MoBIs) that account for uncertainty in big-data biodiversity analysis, allowing for better informed decision making for conservation purposes

Biodiversity data can be analysed to predict species distribution at various scales of time and space. However, survey completeness and temporal decay in data quality introduce uncertainty into biodiversity models. Researchers Joaquín Hortal, Juliana Stropp (National Museum of Natural Sciences, Spain), Richard Ladle (University of Porto, Portugal), and Geiziane Tessarolo (State University of Goiás, Brazil), among others, are constructing the […]

Value Added Data systems: An architecture for end-user informed data preparation

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As the myriad of data sources continues to grow, so does the need for cost-effective, scalable and principled techniques for integrating and cleaning big data in order to optimise the data quality and thus increase its value. Dr Norman Paton, Professor of Computer Science and Dr Nikolaos Konstantinou, a Research Fellow with the Department of Computer Science, both from the […]