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A Design of Building Inventory for Risk Analysis Using Open Data

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Current Trends in Web Engineering (ICWE 2019)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11609))

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Abstract

This study introduces a design of building inventory for risk analysis using open data in Korea. Recently, disasters of various sizes and types are occurring globally. Risk analysis tools are used to estimate the losses due to disasters. However, there is a limitation in the application of disaster statistical data in Korea because these data are based on the country where the tool is produced. To improve the accuracy of loss assessment, it is necessary to utilize data in consideration of each country’s environment. However, the data opened at the national level are distributed among various organizations. Thus, considerable time is required to build infrastructure. Therefore, we collect the open data distributed among various institutions and ensure data compatibility and interoperability through the standardization of the data in various formats. In addition to a disaster analysis system, a design method for a database system that can support various analysis systems through the data is proposed considering scalability.

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References

  1. Chai, S.-S., Shin, S., Suh, D.: A study on the development of korean inventory for the multi-hazard risk assessment. J. Dig. Contents Soc. 18(6), 1127–1134 (2017)

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  3. ERGO, http://ergo.ncsa.illinois.edu/?page_id=44. Accessed 29 Apr 2019

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Acknowledgement

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2018R1C1B5084507).

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Correspondence to Dongjun Suh .

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Chai, SS., Suh, D. (2020). A Design of Building Inventory for Risk Analysis Using Open Data. In: Brambilla, M., Cappiello, C., Ow, S. (eds) Current Trends in Web Engineering. ICWE 2019. Lecture Notes in Computer Science(), vol 11609. Springer, Cham. https://doi.org/10.1007/978-3-030-51253-8_1

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  • DOI: https://doi.org/10.1007/978-3-030-51253-8_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-51252-1

  • Online ISBN: 978-3-030-51253-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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