Data driven policy making: The Peruvian water resources observatory

Giuliana Barnuevo, Elsa Galarza, Maria Paz Herrera, Juan G. Lazo Lazo, Miguel Nunez-del-Prado

Research output: Contribution to journalArticle in a journalpeer-review

Abstract

Nowadays, Big Data holds vast potential for improving decision-making in public policy due to the different methodologies for working with complex heterogeneous big data, which allows proposing policies based on real and measurable key performance indicators. This article aims to describe the water resource observatory of the Public Management School of Universidad del Pacífico. The idea behind the observatory is to handle data extracted from non-traditional sources to enhance efficient and responsive government solutions through evidence-based public policies for water regulation. We used Elastic Search stack to centralize and visualize data from different sources, which was standardized using river basins as basic units. Finally, we show a use case of the data gathered to optimize the water supply in new urban zones in Lima’s periphery.
Original languageEnglish
Pages (from-to)419-431
Number of pages13
Journal Communications in Computer and Information Science
Volume1410
DOIs
StatePublished - 12 May 2021
EventInternational Conference on Information Management and Big Data - Lima, Peru
Duration: 1 Oct 20203 Oct 2020
Conference number: 7
https://simbig.org/SIMBig2020/

Bibliographical note

Publisher Copyright:
© 2021, Springer Nature Switzerland AG.

Publisher Copyright:
© 2021, Springer Nature Switzerland AG.

Keywords

  • Big data
  • Data-driven decision
  • Public policy
  • Water management

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