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Data Driven Policy Making: The Peruvian Water Resources Observatory

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Information Management and Big Data (SIMBig 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1410))

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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.

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Notes

  1. 1.

    Python: https://www.python.org.

  2. 2.

    QGIS: https://www.qgis.org/es/site/.

  3. 3.

    Logstash: https://www.elastic.co.

  4. 4.

    Elasticsearch: https://www.elastic.co/logstash.

  5. 5.

    Kibana: https://www.elastic.co/kibana.

  6. 6.

    GEOIDEP: https://www.geoidep.gob.pe/.

  7. 7.

    ANA: https://www.ana.gob.pe/.

  8. 8.

    MINSA: https://www.gob.pe/minsa/.

  9. 9.

    SUNASS: https://www.sunass.gob.pe/websunass/.

  10. 10.

    Waze Route Calculator: https://github.com/kovacsbalu/WazeRouteCalculator.

  11. 11.

    SCIP: www.scipopt.org/.

  12. 12.

    PySCIPOpt: https://github.com/SCIP-Interfaces/PySCIPOpt.

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Author information

Authors and Affiliations

  1. Universidad Del Pacifico, Lima, Peru

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

Authors
  1. Giuliana Barnuevo
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  2. Elsa Galarza
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  3. Maria Paz Herrera
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  4. Juan G. Lazo Lazo
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  5. Miguel Nunez-del-Prado
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  6. José Luis Ruiz
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Corresponding author

Correspondence to Miguel Nunez-del-Prado .

Editor information

Editors and Affiliations

  1. Stanford University, Stanford, CA, USA

    Juan Antonio Lossio-Ventura

  2. Visibilia, São Paulo, Brazil

    Jorge Carlos Valverde-Rebaza

  3. University of Valencia, Valencia, Spain

    Eduardo Díaz

  4. Universidad del Pacífico, Lima, Peru

    Hugo Alatrista-Salas

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Barnuevo, G., Galarza, E., Herrera, M.P., Lazo, J.G.L., Nunez-del-Prado, M., Ruiz, J.L. (2021). Data Driven Policy Making: The Peruvian Water Resources Observatory. In: Lossio-Ventura, J.A., Valverde-Rebaza, J.C., Díaz, E., Alatrista-Salas, H. (eds) Information Management and Big Data. SIMBig 2020. Communications in Computer and Information Science, vol 1410. Springer, Cham. https://doi.org/10.1007/978-3-030-76228-5_30

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  • DOI: https://doi.org/10.1007/978-3-030-76228-5_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-76227-8

  • Online ISBN: 978-3-030-76228-5

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