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Earth Science Informatics

, Volume 8, Issue 1, pp 51–62 | Cite as

Formalizing the semantics of sea ice

  • Ruth E. Duerr
  • James McCusker
  • Mark A. Parsons
  • SiriJodha Singh Khalsa
  • Peter L. Pulsifer
  • Cassidy Thompson
  • Rui Yan
  • Deborah L. McGuinness
  • Peter Fox
Research Article

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.

Keywords

Sea ice Ontology Semantics Ice charts 

Notes

Acknowledgments

The authors gratefully acknowledge the support of National Science Foundation Award ACI 0956010 INTEROP: International Network of Arctic Knowledge that funded this work. We’d also like to thank the attendees of the several workshops held by this project, including members of the sea ice research, observations and modeling communities, ice operations specialists, and Indigenous sea ice experts from Barrow, Savoonga and the Lower Yukon region of Alaska for their participation in a series of lively and productive discussions leading to the results described here. Lastly, we’d like to thank the members of the JCOMM-ETSI for their review of the ontologies and willingness to maintain them going forward.

References

  1. ACIA (2005) Arctic Climate Impacts Assessment. Cambridge University Press, pp 1042Google Scholar
  2. Benedict JL, McGuinness DL, Fox PA (2006) A Semantic web-based methodology for building conceptual models of scientific information. In American Geophysical Union, Fall Meeting, San Francisco, Ca., December, 2007. Eos Trans. AGU 88(52), Fall Meet. Suppl., Abstract IN53A-0950Google Scholar
  3. Berrueta D, Polo L (2008) Measurement units ontology http://idi.fundacionctic.org/muo/muo-vocab.html
  4. Bushuyev AV (2011) Sea Ice Nomenclature, draft Version 1.0, http://www.aari.nw.ru/gdsidb/docs/wmo/nomenclature/WMO_Nomenclature_draft_version1-0.pdf (accessed 2011)
  5. Canadian Ice Service (2009) Canadian Ice Service Arctic Regional Sea Ice Charts in SIGRID-3 Format. National Snow and Ice Data Center, Boulder. doi: 10.7265/N51V5BW9 Google Scholar
  6. Clemente-Colón P (2010) Impacts of an ice-diminishing arctic on naval and maritime operations. In 2010 I.E. International Geoscience and Remote Sensing Symposium. Honolulu, Hi. TH4.L08.3Google Scholar
  7. Dumontier M, Baker CJO, Baran J, Callahan A, Chepelev L, Cruz-Toledo J, Del Rio NR et al (2014) The Semanticscience Integrated Ontology (SIO) for Biomedical Research and Knowledge Discovery. J Biomed Semant 5(1):14. doi: 10.1186/2041-1480-5-14 CrossRefGoogle Scholar
  8. Ford J, Gough B, Laidler G, MacDonald J, Qrunnnut J, Irngaut C (2009) Sea ice, climate change, and community vulnerability in northern Foxe Basin, Canada. Clim Res 38:138–154CrossRefGoogle Scholar
  9. Fox P, Raskin R, Bermudez L, Burrows H, Ramachandran R, Di L, Wilson B (2007) Datatype and service ontology. Federation of Earth Science Information Partners Wiki. http://wiki.esipfed.org/images/3/37/Semweb-001-datatype-service.pdf. Accessed 31 March, 2014
  10. Fox P, McGuinness DL, Cinquini L, West P, Garcia J, Benedict JL, Middleton D (2009) Ontology-supported scientific data frameworks: The virtual solar-terrestrial observatory experience. In Computers and Geosciences - Elsevier. Volume 35, Issue 4Google Scholar
  11. Interagency Arctic Research Policy Committee (IARPC) (2013) Arctic Research Plan: FY2013-2017, Office of Science and Technology Policy, http://www.whitehouse.gov/sites/default/files/microsites/ostp/2013_arctic_research_plan.pdf
  12. Lawrence DM, Slater AG, Tomas RA, Holland MM, Deser C (2008) Accelerated Arctic land warming and permafrost degradation during rapid sea ice loss. Geophys Res Lett 35(11)Google Scholar
  13. Lebo T, Sahoo S, McGuinness DL (2013) PROV-O: The PROV Ontology. World Wide Web Consortium (W3C) Recommendation. April 30, 2013. Available from http://www.w3.org/TR/prov-o/
  14. Maali F, Erickson J, Archer P (2014) Data Catalog Vocabulary (DCAT). W3C RecommendationGoogle Scholar
  15. McGuinness DL, Fox P, Cinquini L, West P, Garcia J, Benedict JL, Middleton D (2007) The virtual solar-terrestrial observatory: A deployed semantic web application case study for scientific research. In the Proceedings of the Nineteenth Conference on Innovative Applications of Artificial Intelligence (IAAI-07). Vancouver, British Columbia, Canada, July 22–26, 2007Google Scholar
  16. Meier WN, Gallaher D, Campbell GG (2013) New estimates of Arctic and Antarctic sea ice extent during September 1964 from recovered Nimbus I satellite imagery. Cryosphere Discuss 7(1):35–53CrossRefGoogle Scholar
  17. National Research Council (2012) Seasonal-to-decadal predictions of arctic sea ice: challenges and strategies. The National Academies Press, ISBN 9780309265263, http://www.nap.edu/openbook.php?record_id=13515
  18. Overpeck JT, Sturm M, Francis JA, Perovich DK, Serreze MC, Benner R, Carmack EC, Chapin FS, Gerlach SC, Hamilton LC, Hinzman LD, Holland M, Huntington HP, Key JR, Lloyd AH, MacDonald GM, McFadden J, Noone D, Prowse TD, Schlosser P, Vörösmarty C (2005) Arctic system on trajectory to new, seasonally ice-free state. Eos Trans Am Geophys Union 86(34):309–313Google Scholar
  19. Raskin RG, Pan MJ (2005) Knowledge representation in the semantic web for Earth and environmental terminology (SWEET). Comput Geosci 31(9):1119–1125CrossRefGoogle Scholar
  20. Rubel-Shuart B (2000) Glossary of Terms for the EOSDIS Core System (ECS) Project, Technical Paper 152-TP-003-003. http://edhs1.gsfc.nasa.gov/waisdata/docsw/pdf/tp1520303.pdf
  21. SPARQL Query Language for RDF, Seaborne A, Prud’hommeaux E, Editors, W3C Recommendation, 15 January 2008, http://www.w3.org/TR/2008/REC-rdf-sparql-query-20080115/ . Latest version available at http://www.w3.org/TR/rdf-sparql-query/
  22. Serreze MC, Holland MM, Stroeve J (2007) Perspectives on the Arctic’s shrinking sea ice cover. Science 315:1533–1536CrossRefGoogle Scholar
  23. Star SL, Griesemer JR (1989) Institutional Ecology, ‘Translations’ and Boundary Objects: Amateurs and Professionals in Berkeley’s Museum of Vertebrate Zoology, 1907–39. Soc Stud Sci 19(3):387–420. doi: 10.1177/030631289019003001 CrossRefGoogle Scholar
  24. Stirling I, Parkinson CL (2006) Possible Effects of Climate Warming on Selected Populations of Polar Bears (Ursus maritimus) in the Canadian Arctic. Arctic 59:261–275Google Scholar
  25. Stroeve J, Serreze M, Drobot S, Gearheard S, Holland M, Maslanik J, Meier W, Scambos T (2008) Arctic Sea Ice Extent Plummets in 2007, Eos Trans. AGU 89(2):13–14. doi: 10.1029/2008EO020001
  26. Vaughan DG, Comiso JC, Allison I, Carrasco J, Kaser G, Kwok R, Mote P, Murray T, Paul F, Ren J, Rignot E, Solomina O, Steffen K, Zhang T (2013) Observations: Cryosphere. In: Stocker TF, Qin D, Plattner G-K, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM (eds) Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, CambridgeGoogle Scholar
  27. Wang M, Overland JE (2009) A sea ice free summer Arctic within 30 years? Geophys Res Lett 36, L07502. doi: 10.1029/2009GL037820 Google Scholar
  28. World Meteorological Organization (WMO) (1970) WMO sea-ice nomenclature. WMO/OMM/BMO No 259.TP.145, GenevaGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Ruth E. Duerr
    • 1
  • James McCusker
    • 2
  • Mark A. Parsons
    • 3
  • SiriJodha Singh Khalsa
    • 1
  • Peter L. Pulsifer
    • 1
  • Cassidy Thompson
    • 1
  • Rui Yan
    • 2
  • Deborah L. McGuinness
    • 2
  • Peter Fox
    • 2
  1. 1.National Snow and Ice Data CenterUniversity of Colorado at BoulderBoulderUSA
  2. 2.Tetherless World ConstellationRensselaer Polytechnic InstituteTroyUSA
  3. 3.Institute for Data Exploration and ApplicationsRensselaer Polytechnic InstituteTroyUSA

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