Name
Abstract | ||
|---|---|---|
We have initiated a project aimed at enhancing interdisciplinary understanding and usability of polar data by diverse communities. We have produced computer- and human-understandable models of sea ice that can be used to support the interoperability of a wide range of sea ice data. This has the potential to improve scientific predictive analyses and increase usage of the data by scientists, modelers, and forecasters as well as residents of communities that rely on sea ice. We have developed a family of ontologies, leveraging existing best in class models, including one module describing physical characteristics of sea ice, another describing sea ice charts, and a third modeling “egg codes” - an internationally accepted standard for symbolically representing sea ice within geographic regions. We used a semantic Web methodology to rapidly gather and refine requirements, design and iterate over the ontologies, and to evaluate the ontologies with respect to the use cases. We gathered requirements from a wide range of potential stakeholders reflecting the interests of operational ice centers, ice researchers, and indigenous people. We introduce the driving use case and provide an overview of the resulting open source ontologies. We also introduce some key technical considerations including the prominent role of provenance, terms of use, and credit in the model. We describe how the ontologies are being employed and highlight their compatibility with a wide range of existing standards previously developed by many of the stakeholder communities. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/s12145-014-0177-z | Earth Science Informatics |
Keywords | Field | DocType |
Sea ice, Ontology, Semantics, Ice charts | Ontology (information science),Data mining,Ontology,Sea ice,Use case,Computer science,Interoperability,Usability,Semantic Web,Semantics | Journal |
Volume | Issue | ISSN |
8 | 1 | 1865-0481 |
Citations | PageRank | References |
1 | 0.39 | 5 |
Authors | ||
9 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ruth E. Duerr | 1 | 91 | 12.97 |
| James P. McCusker | 2 | 1 | 0.39 |
| Mark A. Parsons | 3 | 66 | 9.52 |
| Siri Jodha Singh Khalsa | 4 | 1 | 0.39 |
| Peter Pulsifer | 5 | 2 | 1.13 |
| Cassidy Thompson | 6 | 1 | 0.39 |
| Rui Yan | 7 | 88 | 5.22 |
| Deborah L. McGuinness | 8 | 7144 | 833.99 |
| Peter Fox | 9 | 238 | 33.49 |