JOURNAL BROWSE
Search
Advanced SearchSearch Tips
A Review on the Management of Water Resources Information based on Big Data and Cloud Computing
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
  • Journal title : Journal of Wetlands Research
  • Volume 18, Issue 1,  2016, pp.100-112
  • Publisher : Korean Wetlands Society
  • DOI : 10.17663/JWR.2016.18.1.100
 Title & Authors
A Review on the Management of Water Resources Information based on Big Data and Cloud Computing
Kim, Yonsoo; Kang, Narae; Jung, Jaewon; Kim, Hung Soo;
  PDF(new window)
 Abstract
In recent, the direction of water resources policy is changing from the typical plan for water use and flood control to the sustainable water resources management to improve the quality of life. This change makes the information related to water resources such as data collection, management, and supply is becoming an important concern for decision making of water resources policy. We had analyzed the structured data according to the purpose of providing information on water resources. However, the recent trend is big data and cloud computing which can create new values by linking unstructured data with structured data. Therefore, the trend for the management of water resources information is also changing. According to the paradigm change of information management, this study tried to suggest an application of big data and cloud computing in water resources field for efficient management and use of water. We examined the current state and direction of policy related to water resources information in Korea and an other country. Then we connected volume, velocity and variety which are the three basic components of big data with veracity and value which are additionally mentioned recently. And we discussed the rapid and flexible countermeasures about changes of consumer and increasing big data related to water resources via cloud computing. In the future, the management of water resources information should go to the direction which can enhance the value(Value) of water resources information by big data and cloud computing based on the amount of data(Volume), the speed of data processing(Velocity), the number of types of data(Variety). Also it should enhance the value(Value) of water resources information by the fusion of water and other areas and by the production of accurate information(Veracity) required for water management and prevention of disaster and for protection of life and property.
 Keywords
Water Resources Information;Big Data;Cloud Computing;
 Language
Korean
 Cited by
 References
1.
Bae, IS. (2006). Weather Dominates, Planet Media. [Korean Literature]

2.
BDT Insights. (2014). Cutting edge Environment Protector 'Big Data'. http://www.bdtinsights.com/kr/

3.
IBM (2012), Analysis: The real advantage of Big Data, IBM IBM Institute for Business Value [Korean Literature]

4.
IDC Digital Universe Study: extracting value from chaos, http://www.emc.com/collateral/demos/microsites/emc-digital-universe-2011/index.htm

5.
Kang, TG., Lee, Y., Hong, YS., Jung, SW. (2012). Analysis of River Environment Management in China and Cooperation Method between Korea and China. Korea Institute for International Economic Policy and Korea Environment Institute. [Korean Literature]

6.
Kim, DP. and Lee, NH. (2010). The Hydrological Characteristics Analysis on the Seolma-Cheon Experimental Catchment. Proceedings of the Korean Environmental Sciences Society Conference. [Korean Literature]

7.
Kim, HK. (2012). Social Issues and Big Data Strategy of Korea. The 3rd National Strategy Forum of Big Data, National Information Society Agency, pp. 7-19. [Korean Literature]

8.
Kim, JH. (2004). Water Resources Policy of Japan. Magazine of Korea Water Resources Association, 37(6), pp. 55-69. [Korean Literature] crossref(new window)

9.
Kim, JW. (2015). Analysis of relationship between inundation depth of flow duration and plant habitat -A case study on Binae wetland-. Thesis for Master' Degree, Inha University. [Korean Literature]

10.
Kim, SJ. (2011). Impact of Climate Change on Water Resources and Ecological Habitat in A River Basin. Ph.D. dissertation, Inha University. [Korean Literature]

11.
Korea Meteorological Administration. (2013). Meteorological Technology & Policy, 6(2). [Korean Literature]

12.
KT Economic Management Institute (2012) Big Data Recent global trends and issues. [Korean Literature]

13.
Lee, JS. and Kim, JW. (2013). Creative Economy and Water Industry. Korea Institute of Science & Technology Evaluation and Planning. [Korean Literature]

14.
Lee, KH. (2011). Estimation of Expected Flood Damage considering Uncertainty and Under Climate Change. Ph.D. dissertation, Inha University. [Korean Literature]

15.
National Information Society Agency (2013). Data analysis for a better future: Global Best Practices of Big Data II. [Korean Literature]

16.
National Institute of Environmental Research. (2012). Research of Development for Automatic Water Quality Monitoring Network Data Open System and Real-Time Monitoring Method, Ministry of Environment. [Korean Literature]

17.
Park, MJ. (2006). Flood Forecast System of America. Magazine of Korea Water Resources Association, 39(7), pp. 47-54. [Korean Literature] crossref(new window)

18.
Park, SJ. (2011). International Water Policy Trends and Implications. Water Journal. [Korean Literature]

19.
Shim, MP. (2006). Survival Conditions in 21st Century. Magazine of Korea Water Resources Association, 39(6), pp. 61-63. [Korean Literature]

20.
TDWI Reserach (2011). Big data analytics Report [Korean Literature]

21.
Water Resources Management Office. (2007). Case of Integrated Watershed Management in Korea. K-Water. [Korean Literature]

22.
Wikipedia, http://ko.wikipedia.org/wiki/

23.
Yoo, Grace. (2013). The role of the Researcher in Big Data Era. TNS Consult.