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: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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-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 language	English
Title of host publication	Information Management and Big Data - 7th Annual International Conference, SIMBig 2020, Proceedings
Editors	Juan Antonio Lossio-Ventura, Jorge Carlos Valverde-Rebaza, Eduardo Díaz, Hugo Alatrista-Salas
Place of Publication	Cham
Pages	419-431
Number of pages	13
Volume	1410
DOIs	https://doi.org/10.1007/978-3-030-76228-5_30
State	Published - 12 May 2021
Event	International Conference on Information Management and Big Data - Lima, Peru Duration: 1 Oct 2020 → 3 Oct 2020 Conference number: 7 https://simbig.org/SIMBig2020/

Publication series

Name	Communications in Computer and Information Science
Volume	1410 CCIS
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	International Conference on Information Management and Big Data
Abbreviated title	SIMBig
Country/Territory	Peru
City	Lima
Period	1/10/20 → 3/10/20
Internet address	https://simbig.org/SIMBig2020/

Bibliographical note

Publisher Copyright:
© 2021, Springer Nature Switzerland AG.

Publisher Copyright:
© 2021, Springer Nature Switzerland AG.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 6 Clean Water and Sanitation
SDG 10 Reduced Inequalities
SDG 17 Partnerships for the Goals

Keywords

Big data
Data-driven decision
Public policy
Water management

Access to Document

10.1007/978-3-030-76228-5_30License: Unspecified

Cite this

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. In 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, Proceedings (Vol. 1410, pp. 419-431). (Communications in Computer and Information Science; Vol. 1410 CCIS).. https://doi.org/10.1007/978-3-030-76228-5_30

Barnuevo, Giuliana ; Galarza, Elsa ; Herrera, Maria Paz et al. / Data driven policy making : The Peruvian water resources observatory. Information Management and Big Data - 7th Annual International Conference, SIMBig 2020, Proceedings. editor / Juan Antonio Lossio-Ventura ; Jorge Carlos Valverde-Rebaza ; Eduardo Díaz ; Hugo Alatrista-Salas. Vol. 1410 Cham, 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. in JA Lossio-Ventura, JC Valverde-Rebaza, E Díaz & H Alatrista-Salas (eds), Information Management and Big Data - 7th Annual International Conference, SIMBig 2020, Proceedings. vol. 1410, Communications in Computer and Information Science, vol. 1410 CCIS, Cham, pp. 419-431, International Conference on Information Management and Big Data, Lima, Peru, 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 et al.
Information Management and Big Data - 7th Annual International Conference, SIMBig 2020, Proceedings. ed. / Juan Antonio Lossio-Ventura; Jorge Carlos Valverde-Rebaza; Eduardo Díaz; Hugo Alatrista-Salas. Vol. 1410 Cham, 2021. p. 419-431 (Communications in Computer and Information Science; Vol. 1410 CCIS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

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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VL - 1410

T3 - Communications in Computer and Information Science

SP - 419

EP - 431

BT - Information Management and Big Data - 7th Annual International Conference, SIMBig 2020, Proceedings

A2 - Lossio-Ventura, Juan Antonio

A2 - Valverde-Rebaza, Jorge Carlos

A2 - Díaz, Eduardo

A2 - Alatrista-Salas, Hugo

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. In Lossio-Ventura JA, Valverde-Rebaza JC, Díaz E, Alatrista-Salas H, editors, Information Management and Big Data - 7th Annual International Conference, SIMBig 2020, Proceedings. Vol. 1410. Cham. 2021. p. 419-431. (Communications in Computer and Information Science). doi: 10.1007/978-3-030-76228-5_30

Data driven policy making: The Peruvian water resources observatory

Abstract

Publication series

Conference

Bibliographical note

UN SDGs

Keywords

Access to Document

Other files and links

Fingerprint

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

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