Informational, Educational, and Scientific Values of Environmental Data Interactive Visualizations

• Autorzy: Karol Król , Krzysztof Gawroński

Warianty tytułu

Informacyjna, edukacyjna i naukowa wartość interaktywnych wizualizacji danych środowiskowych

• Języki publikacji: EN

Abstrakty

EN

Various programmatic techniques and tools are more and more frequently being used for the interactive visualization of data, especially environmental data. Their prevalence and domain of their use in environmental management as well as the promotion and popularization of scientific survey results have increased successively. Chosen examples of applications of environmental data interactive visualizations were presented in the paper, their advantages and disadvantages were discussed, and some of the most-popular techniques and tools used in their creation were listed. In conclusion, it was pointed out that data visualizations are being applied more and more in the natural and technical sciences. Moreover, it was noticed that environmental data visualizations can influence the efficiency of environmental management, and the repeatedly reiterated and multi-sourced transmission of data can publicize environmental problems as well as affect the ecological awareness of individuals or social groups. (original abstract)

Różnorakie techniki i narzędzia programistyczne są coraz częściej stosowane do interaktywnej wizualizacji danych, w szczególności środowiskowych. Sukcesywnie zwiększa się powszechność i obszar ich zastosowań w zarządzaniu środowiskiem oraz w upowszechnianiu i popularyzacji wyników badań naukowych. W pracy przedstawiono wybrane przykłady zastosowań wizualizacji danych środowiskowych, omówiono ich wady i zalety, wymieniono także jedne z najpopularniejszych technik i narzędzi umożliwiających ich tworzenie. W konkluzji zwrócono uwagę, że wizualizacje danych znajdują coraz częściej zastosowanie w naukach przyrodniczych i technicznych. Ponadto zauważono, że wizualizacje danych środowiskowych mogą wpływać na efektywność zarządzania środowiskiem, a wielokrotnie ponawiany i wieloźródłowy przekaz informacji może nagłośnić problemy środowiskowe oraz wpłynąć na świadomość ekologiczną jednostek lub grup społecznych. (abstrakt oryginalny)

Słowa kluczowe

EN

Cartography; Environmental management; Data visualisation

PL

Kartografia; Zarządzanie środowiskiem; Wizualizacja danych

• Czasopismo: Geomatics and Environmental Engineering
• Rocznik: 2018
• Numer: nr 12/2
• Strony: 51--62

Twórcy

autor

Karol Król

• University of Agriculture in Kraków, Poland

autor

Krzysztof Gawroński

• University of Agriculture in Kraków, Poland

Bibliografia

• Ames D.P., Horsburgh J.S., Cao Y., Kadlec J., Whiteaker T., Valentine D.: HydroDesktop: Web services-based software for hydrologic data discovery, download, visualization, and analysis. Environmental Modelling & Software, no. 37, 2012, pp. 146-156.
• Andrienko G., Andrienko N., Dykes J., Kraak M.J., Robinson A., Schumann H.: GeoVisual analytics: interactivity, dynamics, and scale. Cartography and Geographic Information Science, vol. 43, no. 1, 2016, pp. 1-2. DOI: 10.1080/15230406.2016.1095006.
• Avouris N.M., Page B. (eds.): Environmental informatics: Methodology and applications of environmental information processing. Springer Science & Business Media, 2013. DOI: 10.1007/978-94-017-1443-3.
• Benkler Y.: Coase's Penguin, or, Linux and the Nature of the Firm. Yale Law Journal, vol. 112, no. 3, 2002, pp. 369-446.
• Benslimane D., Dustdar S., Sheth A.: Services mashups: The new generation of web applications. IEEE Internet Computing, vol. 12, no. 5, 2008, pp. 13-15. DOI: 10.1109/MIC.2008.110.
• Bostock M., Ogievetsky V., Heer J.: D³ data-driven documents. IEEE Transactions on Visualization and Computer Graphics, vol. 17, no. 12, 2011, pp. 2301-2309. DOI: 10.1109/TVCG.2011.185.
• Bowie G.D., Millward A.A., Bhagat N.N.: Interactive mapping of urban tree benefits using Google Fusion Tables and API technologies. Urban Forestry & Urban Greening, vol. 13, no. 4, 2014, pp. 742-755. DOI: 10.1016/j.ufug.2014.06.002.
• Bruns A.: Produsage: Towards a Broader Framework for User-Led Content Creation. [in:] Proceedings of the 6th ACM SIGCHI Conference on Creativity & Cognition, ACM, New York 2007, pp. 99-106. DOI: 10.1145/1254960.1254975.
• Bryan B.A.: Physical environmental modeling, visualization and query for supporting landscape planning decisions. Landscape and Urban Planning, vol. 65, no. 4, 2003, pp. 237-259. DOI: 10.1016/S0169-2046(03)00059-8.
• Bryant N., Wildfire J.: Webcharts - A Web-based Charting Library for Custom Interactive Data Visualization. Journal of Open Research Software, vol. 4, no. 1, 2016, p. 29. DOI: 10.5334/jors.127.
• Carswell C.M., Wickens C.D.: Information integration and the object display an interaction of task demands and display superiority. Ergonomics, vol. 30, no. 3, 1987, pp. 511-527. DOI: 10.1080/00140138708969741.
• Daniel T.C.: Data visualization for decision support in environmental management. Landscape and Urban Planning, vol. 21, no. 4, 1992, pp. 261-263. DOI: 10.1016/0169-2046(92)90036-Y.
• De Paor D.G., Whitmeyer S.J., Marks M. Bailey J.E.: Geoscience applications of client/server scripts, Google Fusion Tables, and dynamic KML. [in:] Whitmeyer S.J. (ed.), Google Earth and Virtual Visualizations in Geoscience Education and Research, Geological Society of America Special Papers, no. 492, Geological Society of America, 2012, pp. 77-104. DOI: 10.1130/2012.2492(06).
• Devarakonda S., Sevusu P., Liu H., Liu R., Iftode L., Nath B.: Real-time air quality monitoring through mobile sensing in metropolitan areas. [in:] Proceedings of the 2nd ACM SIGKDD International Workshop on Urban Computing. ACM 2013. ACM, New York, pp. 15:1-15:8. DOI: 10.1145/2505821.2505834.
• Doshi J., Goradia A.I., Mistry D.: A Review of Google Data Visualization Tools. International Journal of Current Engineering and Technology, vol. 4, no. 5, 2014, pp. 3134-3138.
• ElTayeby O., John D., Patel P., Simmerman S.: Comparative case study between D3 & Highcharts on Lustre metadata visualization. [in:] 2013 IEEE Symposium on Large-Scale Data Analysis and Visualization (LDAV). DOI: 10.1109/LDAV.2013.6675172.
• Fox P., Hendler J.: Changing the equation on scientific data visualization. Science, vol. 331, no. 6018, 2011, pp. 705-708. DOI: 10.1126/science.1197654.
• Friendly M.: A brief history of data visualization. [in:] Handbook of Data Visualization, Springer, Berlin - Heidelberg 2008, pp. 15-56. DOI: 10.1007/978-3-540-33037-0_2.
• Gonzalez H., Halevy A.Y., Jensen C.S., Langen A., Madhavan J., Shapley R., Shen W, Goldberg-Kidon J.: Google fusion tables: web-centered data management and collaboration. [in:] Proceedings of the 2010 ACM SIGMOD International Conference on Management of Data, ACM, New York 2010. DOI: 10.1145/1807167.1807286.
• Goodchild M.F.: Citizens as sensors: the world of volunteered geography. Geo-Journal, vol. 69, no. 4, 2007, pp. 211-221. DOI: 10.1007/s10708-007-9111-y.
• He M., Tang X., Huang Y.: To visualize spatial data using thematic maps combined with infographics. Geoinformatics, IEEE 2011, pp. 1-5. DOI: 10.1109/GeoInformatics.2011.5980880.
• Kralikova R., Rovnak M., Kralik M.: Visualization of environmental data. SGEM Scientific GeoConference, no. 2, 2008, pp. 577-584.
• Krauss J.: Infographics: More than Words Can Say. Learning & Leading with Technology, vol. 39, no. 5, 2012, pp. 10-14.
• Król K.: Data presentation on the map in Google Charts and jQuery JavaScript technologies. Geomatics, Landmanagement and Landscape, no. 2, 2016, pp. 91-106. DOI: 10.15576/GLL/2016.2.91.
• Król K., Prus B.: The comparative analysis of selected interactive data presentation techniques on the example of the land use structure in the commune of Tomice. Polish Cartographical Review, vol. 48, no. 3, 2016, pp. 1-13. DOI: https://doi.org/10.1515/pcr-2016-0009.
• Kulawiak M., Prospathopoulos A., Perivoliotis L., Kioroglou S., Stepnowski A.: Interactive visualization of marine pollution monitoring and forecasting data via a Web-based GIS. Computers & Geosciences, vol. 36, no. 8, 2010, pp. 1069-1080. DOI: 10.1016/j.cageo.2010.02.008.
• Lee M.G., Yu K.M. Chien S.T.: Visualize Field Data in Fusion Tables-Take Chung Hua University Plant Map as Example. [in:] 2014 7th International Conference on Ubi-Media Computing and Workshops (UMedia 2014): Ulaanbaatar, Mongolia, 12-14 July 2014. IEEE, 2014, pp. 261-265. DOI: 10.1109/U-MEDIA.2014.71.
• Lindquist M., Lange E., Kang J.: From 3D landscape visualization to environmental simulation: The contribution of sound to the perception of virtual environments. Landscape and Urban Planning, no. 148, 2016, pp. 216-231. DOI: 10.1016/j.landurbplan.2015.12.017.
• Liu X., Hui Y., Sun W., Liang H.: Towards service composition based on mashup.[in:] 2007 IEEE Congress on Services: (SERVICES 2007): Proceedings: Salt Lake City, Utah, USA, IEEE Computer Society, 2007, pp. 332-339. DOI: 10.1109/SERVICES.2007.67.
• Manovich L.: The Language of New Media. MIT Press, Cambridge 2001.
• Meitner M.J., Sheppard S.R., Cavens D., Gandy R., Picard P., Harshaw H., Harrison D.: The multiple roles of environmental data visualization in evaluating alternative forest management strategies. Computers and Electronics in Agriculture, vol. 49, no. 1, 2005, pp. 192-205. DOI: 10.1016/j.compag. 2005.03.002.
• Nair L.R., Shetty S.D., Shetty S.D.: Interactive visual analytics on Big Data: Tableau vs D3. js. Journal of e-Learning and Knowledge Society, vol. 12, no. 4, 2016, p. 139-150.
• Orland B.: Data visualization techniques in environmental management: a workshop. Landscape and Urban Planning, vol. 21, no. 4, 1992, pp. 237-239.
• Paar P.: Landscape visualizations: Applications and requirements of 3D visualization software for environmental planning. Computers, Environment and Urban Systems, vol. 30, no. 6, 2006, pp. 815-839. DOI: 10.1016/j.compenvurbsys.2005.07.002.
• Roth R.E., MacEachren A.M.: Geovisual analytics and the science of interaction: an empirical interaction study. Cartography and Geographic Information Science, vol. 43, no. 1, 2016, pp. 30-54. DOI: 10.1080/15230406.2015.1021714.
• Schnettler B.: Auf dem Weg zu einer Soziologie visuellen Wissens. Sozialer Sinn, vol. 8, no. 2, pp. 189-211.
• Sheppard S.R., Cizek P.: The ethics of Google Earth: Crossing thresholds from spatial data to landscape visualisation. Journal of Environmental Management, vol. 90, no. 6, 2009, pp. 2102-2117. DOI: 10.1016/j.jenvman.2007.09.012.
• Velasco V., Gogu R., Vázquez-Suñè E., Garriga A., Ramos E., Riera J., Alcaraz M.: The use of GIS-based 3D geological tools to improve hydrogeological models of sedimentary media in an urban environment. Environmental Earth Sciences, vol. 68, no. 8, 2013, pp. 2145-2162. DOI: 10.1007/s12665-012-1898-2.
• Xu Z., Coors V.: Combining system dynamics model, GIS and 3D visualization in sustainability assessment of urban residential development. Building and Environment, no. 47, 2012, pp. 272-287. DOI: 10.1016/j.buildenv.2011.07.012.
• Yu J., Benatallah B., Casati F., Daniel F.: Understanding mashup development. Internet Computing, vol. 12, no. 5, 2008, pp. 44-52. DOI: 10.1109/MIC.2008.114.
• Yue P., Jiang L., Hu L.: Google fusion tables for managing soil moisture sensor observations. Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 7, no. 11, 2014, pp. 4414-4421. DOI: 10.1109/JSTARS.2014.2353621.

Identyfikatory

DOI

/10.7494/geom.2018.12.2.51