ETHAN: the Evolutionary Trees and Natural History Ontology

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Large-scale ecological modeling and evolutionary studies often rely on scoring taxon-level characteristics of a wide variety of organisms. Compiling such data is laborious and may involve finding and reformatting data tables in original literature or personally exchanging spreadsheets or ASCII files with researchers. Compiled taxon-level data is beginning to be shared digitally, and efforts to support wide data sharing in ecology and evolution should make even more compiled data available in forms useful to scientists. However, retrieval, integration, transformation, and validation of shared data in traditional archives remain difficult and largely manual processes. Discovery of new insights from such data is therefore delayed if it is even possible. Our interest in natural history information stems from our work on a suite of tools to support invasive species biologists. Though food web structure has been recognized to play a role in the success or failure of potential species invasions and their impacts, few ecosystems have been the subjects of empirical food web studies. Thus response teams are typically unable to get quick answers to questions like "what are likely prey and predator species of the invader in the new environment?" We have developed a food web constructor that currently uses an algorithm relying on taxonomic or phylogenetic relationships to model ecological interactions. Future algorithmic developments will use similarities in life history, natural history, or behavior to inform link predictions.

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ecoinformatics, food web, ontology, semantic web


University of Maryland, Baltimore County

Computer Science and Electrical Engineering

technical report

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UMBC ebiquity