Oceanography The Official Magazine of
The Oceanography Society
Volume 27 Issue 03

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Volume 27, No. 3
Pages 138 - 147

OpenAccess

Operational Oceanography, End Users, and Social Network Sites: An Exploratory Analysis

Pablo Otero Manuel Ruiz-VillarrealGonzalo González-NuevoJose Manuel Cabanas
Article Abstract

Many oceanographic products are currently being disseminated in a systematic and routine manner to end users. In recent years, data producers have gained insight into the specific requirements of the scientific community. However, there is still a lack of perception of the interests of the broader and non-expert public. This study analyzes the interests and needs of potential end users of operational oceanography by mining Web search engine and social media data. Results show an increasing number of people searching for operational oceanography-related products, with seasonality in these searches depending on the kind of variable. Information on currents is searched more during winter, waves during spring, and tides and temperature during summer. Moreover, the ranking of specific interests of the general public differs from the requirements of the fisheries and applied environmental scientists reported by the International Council for the Exploration of the Sea Working Group on Operational Oceanographic Products for Fisheries and Environment. The general public is more interested in temperature, wave conditions, and sea ice, whereas the highest priority of a group of scientists was temperature, currents, and salinity. An understanding of the terminology used by non-expert clients and their priorities will help institutions involved in curating and disseminating oceanographic data sets to better design their Web portals and applications.

Citation

Otero, P., M. Ruiz-Villarreal, G. González-Nuevo, and J.M. Cabanas. 2014. Operational oceanography, end users, and social network sites: An exploratory analysis. Oceanography 27(3):138–147, https://doi.org/10.5670/oceanog.2014.63.

References

Askitas, N., and K.F. Zimmermann. 2009. Google econometrics and unemployment forecasting. Applied Economics Quarterly 55:107–120, https://doi.org/10.3790/aeq.55.2.107.

Baker, S., and A. Fradkin. 2011. What drives job search? Evidence from Google search data. Technical report, Stanford University, http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1811247.

Berx, B., M. Dickey-Collas, M.D. Skogen, Y-H. De Roeck, H. Klein, R. Barciela, R.M. Forster, E. Dombrowsky, M. Huret, M. Payne, and others. 2011. Does operational oceanography address the needs of fisheries and applied environmental scientists? Oceanography 24(1):166–171, https://doi.org/10.5670/oceanog.2011.14.

Brownstein, J.S., C.C. Freifeld, and L.C. Madoff. 2009. Digital disease detection: Harnessing the Web for public health surveillance. New England Journal of Medicine 360:2,153–2,157, https://doi.org/10.1056/NEJMp0900702.

Burton, S.H., K.W. Tanner, C.G. Giraud-Carrier, J.H. West, and M.D. Barnes. 2012. “Right time, right place” health communication on Twitter: Value and accuracy of location information. Journal of Medical Internet Research 14(6), e156, https://doi.org/10.2196/jmir.2121.

Ethnologue. 2013. Ethnologue: Languages of the World, 17th ed. Published by SIL International, http://www.ethnologue.com.

Facebook, Inc. 2012. Form 10-K Annual Report 2012. Retrieved from Securities and Exchange Commission EDGAR (Electronic Data Gathering, Analysis, and Retrieval system) database website: http://www.sec.gov/edgar.shtml.

Ginsberg, J., M.H. Mohebbi, R.S. Patel, L. Brammer, M.S. Smolinski, and L. Brilliant. 2009. Detecting influenza epidemics using search engine query data. Nature 457:1,012–1,014, https://doi.org/10.1038/nature07634.

Goel, S., J.M. Hofman, S. Lahaie, D.M. Pennock, and D.J. Watts. 2010. Predicting consumer behavior with Web search. Proceedings of the National Academy of Sciences of the United States of America 7:17,486–17,490, https://doi.org/10.1073/pnas.1005962107.

Hulth, A., G. Rydevik, and A. Linde. 2009. Web queries as a source for syndromic surveillance. PLoS ONE 4(2):e4378, https://doi.org/10.1371/journal.pone.0004378.

IPCC (Intergovernmental Panel on Climate Change). 2013. Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, T.F. Stocker, D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex, and P.M. Midgley, eds, Cambridge University Press, Cambridge, United Kingdom, and New York, NY, USA, 1,535 pp.

Otero, P., M. Ruiz-Villarreal, L. Garcia-Garcia, M. Marta-Almeida, M. Cobas, G. González-Nuevo, and J.M. Cabanas. 2011. Walking on the sea side: Modeling and observational efforts of the Iberian Margin Ocean Observatory (RAIA). OCEANS, 2011 IEEE – Spain, June 6–9, 2011, https://doi.org/10.1109/Oceans-Spain.2011.6003564.

Paul, J.M., and M. Dredze. 2013. Drug extraction from the Web: Summarizing drug experiences with multi-dimensional topic models. Pp. 168–178 in Proceedings of NAACL-HLT 2013. Atlanta, Georgia, 9–14 June 2013, N13-1017, Association for Computational Linguistics, http://aclweb.org/anthology//N/N13.

Polfeldt, T. 2006. Making environment statistics useful: A Third World perspective. Environmetrics 17:219–226, https://doi.org/10.1002/env.747.

Preis, T., D. Reith, and H.E. Stanley. 2010. Complex dynamics of our economic life on different scales: Insights from search engine query data. Philosophical Transactions of the Royal Society A 368:5,707–5,719, https://doi.org/10.1098/rsta.2010.0284.

Preis, T., H.S. Moat, H.E. Stanley, and S.R. Bishop. 2012. Quantifying the advantage of looking forward. Scientific Reports 2:350, http://dx.doi.org/10.1038/srep00350.

Myslín, M., S.H. Zhu, W. Chapman, and M. Conway. 2013. Using Twitter to examine smoking behavior and perceptions of emerging tobacco products. Journal of Medical Internet Research 15(8), e174, https://doi.org/10.2196/jmir.2534.

Ruhl, H.A., M. André, L. Beranzoli, M.N. Çağatay, A. Colaço, M. Cannat, J.J. Dañobeitia, P. Favali, L. Géli, M. Gillooly, and others. 2011. Societal need for improved understanding of climate change, anthropogenic impacts, and geo-hazard warning drive development of ocean observatories in European Seas. Progress in Oceanography 91:1–33, https://doi.org/10.1016/j.pocean.2011.05.001.

Sakaki, T., M. Okazaki, and Y. Matsuo. 2010. Earthquake shakes Twitter users: Real-time event detection by social sensors. Pp. 851–860 in WWW’10: Proceedings of the 19th International Conference on World Wide Web. ACM, New York, USA, https://doi.org/10.1145/1772690.1772777.

Signorini, A., A.M. Segre, and P.M. Polgreen. 2011. The use of Twitter to track levels of disease activity and public concern in the US during the influenza A H1N1 pandemic. PLoS ONE 6(5):e19467, https://doi.org/10.1371/journal.pone.0019467.

Wilson, R.E., S.D. Gosling, and L.T. Graham. 2012. A review of Facebook research in the social sciences. Perspectives on Psychological Science 7:203, https://doi.org/10.1177/1745691612442904.

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