Data driven policy making: The Peruvian water resources observatory

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

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

Data driven policy making: The Peruvian water resources observatory

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

Universidad del Pacífico

Resultado de la investigación: Capítulo del libro/informe/acta de congreso › Capítulo de libro › revisión exhaustiva

Resumen

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.

Idioma original	Inglés
Título de la publicación alojada	Information management and big data
Subtítulo de la publicación alojada	7th Annual International Conference, SIMBig 2020, Lima, Peru, October 1–3, 2020, Proceedings
Editores	Juan Antonio Lossio-Ventura, Jorge Carlos Valverde-Rebaza, Eduardo Díaz, Hugo Alatrista-Salas
Lugar de publicación	Cham
Editorial	Springer
Páginas	419-431
Número de páginas	13
ISBN (versión digital)	978-3-030-76228-5
ISBN (versión impresa)	978-3-030-76227-8
DOI	https://doi.org/10.1007/978-3-030-76228-5_30
Estado	Publicada - 12 may 2021
Evento	International Conference on Information Management and Big Data - Lima, Perú Duración: 1 oct 2020 → 3 oct 2020 Número de conferencia: 7 https://simbig.org/SIMBig2020/

Serie de la publicación

Nombre	Communications in Computer and Information Science
Volumen	1410
ISSN (versión impresa)	1865-0929
ISSN (versión digital)	1865-0937

Conferencia

Conferencia	International Conference on Information Management and Big Data
Título abreviado	SIMBig
País/Territorio	Perú
Ciudad	Lima
Período	1/10/20 → 3/10/20
Dirección de internet	https://simbig.org/SIMBig2020/

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Contribución a la conferencia

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https://doi.org/10.1007/978-3-030-76228-5_30Licencia: Sin especificar

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Information management and big data: 7th Annual International Conference, SIMBig 2020, Lima, Peru, October 1–3, 2020, Proceedings
Lossio-Ventura, J. A., Valverde-Rebaza, J. C. (ed.), Díaz, E. (ed.) & Alatrista-Salas, H. (ed.), 2021, Cham: Springer. 554 p. (Communications in Computer and Information Science; vol. 1410 CCIS)
Resultado de la investigación: Informe/libro › Libro › revisión exhaustiva

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Barnuevo, G., Galarza, E., Herrera, M. P., Lazo Lazo, J. G., & Nunez-del-Prado, M. (2021). Data driven policy making: The Peruvian water resources observatory. En J. A. Lossio-Ventura, J. C. Valverde-Rebaza, E. Díaz, & H. Alatrista-Salas (Eds.), Information management and big data: 7th Annual International Conference, SIMBig 2020, Lima, Peru, October 1–3, 2020, Proceedings (pp. 419-431). ( Communications in Computer and Information Science; Vol. 1410). Springer. https://doi.org/10.1007/978-3-030-76228-5_30

Barnuevo, Giuliana ; Galarza, Elsa ; Herrera, Maria Paz ; Lazo Lazo, Juan G. ; Nunez-del-Prado, Miguel. / Data driven policy making : The Peruvian water resources observatory. Information management and big data: 7th Annual International Conference, SIMBig 2020, Lima, Peru, October 1–3, 2020, Proceedings. editor / Juan Antonio Lossio-Ventura ; Jorge Carlos Valverde-Rebaza ; Eduardo Díaz ; Hugo Alatrista-Salas. Cham : Springer, 2021. pp. 419-431 ( Communications in Computer and Information Science).

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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 Pac{\'i}fico. 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{\textquoteright}s periphery.",

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Barnuevo, G, Galarza, E, Herrera, MP, Lazo Lazo, JG & Nunez-del-Prado, M 2021, Data driven policy making: The Peruvian water resources observatory. En JA Lossio-Ventura, JC Valverde-Rebaza, E Díaz & H Alatrista-Salas (eds.), Information management and big data: 7th Annual International Conference, SIMBig 2020, Lima, Peru, October 1–3, 2020, Proceedings. Communications in Computer and Information Science, vol. 1410, Springer, Cham, pp. 419-431, International Conference on Information Management and Big Data, Lima, Perú, 1/10/20. https://doi.org/10.1007/978-3-030-76228-5_30

Data driven policy making : The Peruvian water resources observatory. / Barnuevo, Giuliana; Galarza, Elsa; Herrera, Maria Paz; Lazo Lazo, Juan G.; Nunez-del-Prado, Miguel.

Information management and big data: 7th Annual International Conference, SIMBig 2020, Lima, Peru, October 1–3, 2020, Proceedings. ed. / Juan Antonio Lossio-Ventura; Jorge Carlos Valverde-Rebaza; Eduardo Díaz; Hugo Alatrista-Salas. Cham : Springer, 2021. p. 419-431 ( Communications in Computer and Information Science; Vol. 1410).

Resultado de la investigación: Capítulo del libro/informe/acta de congreso › Capítulo de libro › revisión exhaustiva

TY - CHAP

T1 - Data driven policy making

T2 - International Conference on Information Management and Big Data

AU - Barnuevo, Giuliana

AU - Galarza, Elsa

AU - Herrera, Maria Paz

AU - Lazo Lazo, Juan G.

AU - Nunez-del-Prado, Miguel

N1 - Conference code: 7

PY - 2021/5/12

Y1 - 2021/5/12

N2 - 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.

AB - 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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BT - Information management and big data

A2 - Lossio-Ventura, Juan Antonio

A2 - Valverde-Rebaza, Jorge Carlos

A2 - Díaz, Eduardo

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PB - Springer

CY - Cham

Y2 - 1 October 2020 through 3 October 2020

ER -

Barnuevo G, Galarza E, Herrera MP, Lazo Lazo JG, Nunez-del-Prado M. Data driven policy making: The Peruvian water resources observatory. En Lossio-Ventura JA, Valverde-Rebaza JC, Díaz E, Alatrista-Salas H, editores, Information management and big data: 7th Annual International Conference, SIMBig 2020, Lima, Peru, October 1–3, 2020, Proceedings. Cham: Springer. 2021. p. 419-431. ( Communications in Computer and Information Science). https://doi.org/10.1007/978-3-030-76228-5_30

Data driven policy making: The Peruvian water resources observatory

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Resultados de investigaciones

Information management and big data: 7th Annual International Conference, SIMBig 2020, Lima, Peru, October 1–3, 2020, Proceedings

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