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

Brian J. Stucky; James P. Balhoff; Narayani Barve; Vijay Barve; Laura Brenskelle; Matthew H. Brush; Gregory A. Dahlem; James D.J. Gilbert; Akito Y. Kawahara; Oliver Keller; Andrea Lucky; Peter J. Mayhew; David Plotkin; Katja C. Seltmann; Elijah Talamas; Gaurav Vaidya; Ramona Walls; Matt Yoder; Guanyang Zhang; Rob Guralnick

doi:10.3897/BDJ.7.e33303

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

Brian J. Stucky, James P. Balhoff, Narayani Barve, Vijay Barve, Laura Brenskelle, Matthew H. Brush, Gregory A. Dahlem, James D.J. Gilbert, Akito Y. Kawahara, Oliver Keller, Andrea Lucky, Peter J. Mayhew, David Plotkin, Katja C. Seltmann, Elijah Talamas, Gaurav Vaidya, Ramona Walls, Matt Yoder, Guanyang Zhang, Rob Guralnick

Oregon Clinical and Translational Research Institute

Research output: Contribution to journal › Article › peer-review

3 Scopus citations

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.

Original language	English (US)
Article number	e33303
Journal	Biodiversity Data Journal
Volume	7
DOIs	https://doi.org/10.3897/BDJ.7.e33303
State	Published - 2019

Keywords

Biodiversity informatics
Data modeling
Insects
Natural history
Ontology

ASJC Scopus subject areas

Insect Science
Ecology, Evolution, Behavior and Systematics
Animal Science and Zoology
Agricultural and Biological Sciences (miscellaneous)
Plant Science
Ecology

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Stucky, B. J., Balhoff, J. P., Barve, N., Barve, V., Brenskelle, L., Brush, M. H., Dahlem, G. A., Gilbert, J. D. J., Kawahara, A. Y., Keller, O., Lucky, A., Mayhew, P. J., Plotkin, D., Seltmann, K. C., Talamas, E., Vaidya, G., Walls, R., Yoder, M., Zhang, G., & Guralnick, R. (2019). Developing a vocabulary and ontology for modeling insect natural history data: Example data, use cases, and competency questions. Biodiversity Data Journal, 7, Article e33303. https://doi.org/10.3897/BDJ.7.e33303

Stucky, BJ, Balhoff, JP, Barve, N, Barve, V, Brenskelle, L, Brush, MH, Dahlem, GA, Gilbert, JDJ, Kawahara, AY, Keller, O, Lucky, A, Mayhew, PJ, Plotkin, D, Seltmann, KC, Talamas, E, Vaidya, G, Walls, R, Yoder, M, Zhang, G & Guralnick, R 2019, 'Developing a vocabulary and ontology for modeling insect natural history data: Example data, use cases, and competency questions', Biodiversity Data Journal, vol. 7, e33303. https://doi.org/10.3897/BDJ.7.e33303

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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.",

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AU - Stucky, Brian J.

AU - Balhoff, James P.

AU - Barve, Narayani

AU - Barve, Vijay

AU - Brenskelle, Laura

AU - Brush, Matthew H.

AU - Dahlem, Gregory A.

AU - Gilbert, James D.J.

AU - Kawahara, Akito Y.

AU - Keller, Oliver

AU - Lucky, Andrea

AU - Mayhew, Peter J.

AU - Plotkin, David

AU - Seltmann, Katja C.

AU - Talamas, Elijah

AU - Vaidya, Gaurav

AU - Walls, Ramona

AU - Yoder, Matt

AU - Zhang, Guanyang

AU - Guralnick, Rob

PY - 2019

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N2 - 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.

AB - 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.

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KW - Data modeling

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KW - Ontology

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

Abstract

Keywords

ASJC Scopus subject areas

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