An ontology for landscapes |
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| Affiliation: | 1. Department of Forest Ecology and Management, University of Wisconsin-Madison, Madison, WI 53706, USA;2. Biology Department, York University, 4700 Keele St., Toronto, ON, 3J 1P3 Canada;3. Department of Botany/Microbiology, Ohio Wesleyan University, Delaware, OH 43015, USA;1. Department of Informatics – Catarinense Federal Institute, Araquari, SC, Brazil;2. NR2 – Department of Informatics – Federal University of Paraná, Curitiba, PR, Brazil;1. Genomic Medicine Program, Houston Methodist Research Institute, Houston, TX 77030, USA;2. Center for Nuclear Receptors and Cell Signaling, University of Houston, Houston, TX 77024, USA;1. Dipartimento di Fisica e Astronomia, Università di Bologna, via Irnerio 46, 40126 Bologna, Italy;2. I.N.F.N., Sezione di Bologna, viale Berti Pichat 6/2, 40127 Bologna, Italy;3. Institute of Space Science, Bucharest, P.O. Box MG-23, RO-077125 Bucharest-Magurele, Romania;4. Dipartimento di Matematica, Politecnico di Milano, Piazza L. da Vinci 32, 20133 Milano, Italy;5. Yukawa Institute for Theoretical Physics, Kyoto University, Kyoto 606-8502, Japan;1. “Gheorghe Mihoc-Caius Iacob” Institute of Statistical Mathematics and Applied Mathematics, Romanian Academy, Calea 13 Septembrie No. 13, Bucharest 050711, Romania;2. University of Bucharest, Research Center for Ecological Services, Romania;1. Dipartimento di Fisica e Astronomia, Alma Mater Università di Bologna, via Irnerio 46, 40126 Bologna, Italy;2. I.N.F.N., Sezione di Bologna, viale Berti Pichat 6/2, 40127 Bologna, Italy;3. Institute of Space Science, Bucharest, P.O. Box MG-23, RO-077125 Bucharest-Magurele, Romania;4. HEPCOS, Department of Physics, SUNY at Buffalo, Buffalo, NY 14260-1500, United States |
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| Abstract: | ![]()
As ecological data increases in breadth, depth, and complexity, the discipline of ecology is increasingly influenced by information science. While this influence provides many opportunities for ecologists, it also necessitates a change in how we manage and share data, and perhaps more fundamentally, define concepts in ecology. Specifically, the information technology process of automated data integration entirely depends upon consistent concept definition. A common tool used in computer science and engineering to specify meanings, which is both novel and offers significant potential to ecology, is an ontology. An ontology is a formal representation of knowledge in which concepts are described by their meaning and their relationship to each other. Ontologies are a tool that can be used to ‘explicitly specify a concept’ (Gruber, 1993) and this approach is uncommon in ecology. In this paper, we develop an ontology for the concept of ‘landscape’ that captures the most general definitions and usages of this term. We selected the concept of landscape because it is often used in very different ways by investigators and hence generates linguistic uncertainty. A graphic theoretic (i.e., visual) model is provided which describes the set of structuring rules we used to define the relationships between ‘landscape’ and appropriately related terms. Based upon these rules, a landscape necessarily contains a spatial component (i.e., area), structure and function (i.e., ecosystems), and is scale independent. This approach provides the set of necessary conditions for landscape studies to reduce linguistic uncertainty, and facilitate interoperability of data, i.e., in a manner that promotes data linkages and quantitative synthesis particularly by automatic data synthesis programs that are likely to become an important part of ecology in the future. Simply put, we use an ontology, a technique novel to ecology but not other disciplines, to define ‘landscape,’ thereby clearly delineating one subset of its potential general usage. As such this ontology can serve as both a checklist for landscape studies and a blueprint for additional ecological ontologies. |
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