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Developing a vocabulary and ontology for modeling insect natural history data: example data, use cases, and competency questions

Abstract. Insects are possibly the most taxonomically and ecologically diverse class of multicellular organisms on Earth. Consequently, they provide nearly unlimited opportunities to develop and test ecological and evolutionary hypotheses. Currently, however, large-scale studies of insect ecology, b...

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Detalles Bibliográficos
Autores principales: Stucky, Brian J., Balhoff, James P., Barve, Narayani, Barve, Vijay, Brenskelle, Laura, Brush, Matthew H., Dahlem, Gregory A, Gilbert, James D. J., Kawahara, Akito Y., Keller, Oliver, Lucky, Andrea, Mayhew, Peter J., Plotkin, David, Seltmann, Katja C., Talamas, Elijah, Vaidya, Gaurav, Walls, Ramona, Yoder, Matt, Zhang, Guanyang, Guralnick, Rob
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Pensoft Publishers 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6426826/
https://www.ncbi.nlm.nih.gov/pubmed/30918448
http://dx.doi.org/10.3897/BDJ.7.e33303
Descripción
Sumario:Abstract. Insects are possibly the most taxonomically and ecologically diverse class of multicellular organisms on Earth. Consequently, they provide nearly unlimited opportunities to develop and test ecological and evolutionary hypotheses. Currently, however, large-scale studies of insect ecology, behavior, and trait evolution are impeded by the difficulty in obtaining and analyzing data derived from natural history observations of insects. These data are typically highly heterogeneous and widely scattered among many sources, which makes developing robust information systems to aggregate and disseminate them a significant challenge. As a step towards this goal, we report initial results of a new effort to develop a standardized vocabulary and ontology for insect natural history data. In particular, we describe a new database of representative insect natural history data derived from multiple sources (but focused on data from specimens in biological collections), an analysis of the abstract conceptual areas required for a comprehensive ontology of insect natural history data, and a database of use cases and competency questions to guide the development of data systems for insect natural history data. We also discuss data modeling and technology-related challenges that must be overcome to implement robust integration of insect natural history data.