Research and Design of Hydrological Big-data Sharing Platform

10 pages•Published: September 20, 2018

Abstract

In this paper, the methodology of hydrological big-data standardization is discussed upon analyzing on the characteristics of hydrological data. Three main standards of hydrological data in China are considered in the standardization, which are respectively "Structure and identifier for real-time hydrological information database", "standard for structure and identifier in fundamental hydrological database" and "Structure and identifier for water quality database". Solutions on data pre-processing, data indexing and highly efficient data reading and writing are also introduced. The mass storage capacity and high speed computing capability of Hadoop are utilized for designing and implementing hydrological big-data sharing platform. Then a prototype of the hydrological big-data sharing platform is introduced in this article. Accordingly, the platform can be the technical support for information sharing and space integration between water conservancy industries and other industries, as well as the interdisciplinary sustainable development.

Keyphrases: big data, hbase, hdfs, hydrological data sharing

In: Goffredo La Loggia, Gabriele Freni, Valeria Puleo and Mauro De Marchis (editors). HIC 2018. 13th International Conference on Hydroinformatics, vol 3, pages 2383-2392.

Links:	https://easychair.org/publications/paper/G98V
	https://doi.org/10.29007/c6pg

BibTeX entry

@inproceedings{HIC2018:Research_Design_Hydrological_Big,
  author    = {Jian Xu and Hua Chen},
  title     = {Research and Design of Hydrological Big-data Sharing Platform},
  booktitle = {HIC 2018. 13th International Conference on Hydroinformatics},
  editor    = {Goffredo La Loggia and Gabriele Freni and Valeria Puleo and Mauro De Marchis},
  series    = {EPiC Series in Engineering},
  volume    = {3},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2516-2330},
  url       = {/publications/paper/G98V},
  doi       = {10.29007/c6pg},
  pages     = {2383-2392},
  year      = {2018}}

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