research-article

Environmental Big Data: a systematic mapping study

Authors:

Daniela Castelluccia,

Enrico G. Caldarola,

Nicola BoffoliAuthors Info & Claims

ACM SIGSOFT Software Engineering Notes, Volume 41, Issue 6

Pages 1 - 4

https://doi.org/10.1145/3011286.3011307

Published: 05 January 2017 Publication History

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Abstract

Big data sets and analytics are increasingly being used by government agencies, non-governmental organizations, and privatecompanies to forward environmental protection. Improving energy efficiency, promoting environmental justice, tracking climate change, and monitoring water quality are just a few of the objectives being furthered by the use of Big Data. The authors provide a more detailed analysis of the emerging evidence-based insights on Environmental Big Data (EBD), by applying the well-defined method of systematic mapping. The analysis of results throws light on the current open issues of Environmental Big Data. Moreover, different facets of the study can be combined nto answer more specific research questions. The report reveals the need for more empirical research able to provide new metrics measuring efficiency and effectiveness of the proposed analytics and new methods and tools supporting data processing workflow in EBD

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Kleisner KPokorný ŠČerný V(2023)Sexually dimorphic traits are associated with subsistence strategy in African faces from the Sahel/Savannah beltAmerican Journal of Human Biology10.1002/ajhb.2400836:4Online publication date: 28-Oct-2023
https://doi.org/10.1002/ajhb.24008
Camargo A LMedina D BGómez R J(2022)PROTOTIPO ELECTRÓNICO IoT PARA EL SEGUIMIENTO DE VARIABLES AMBIENTALESREVISTA AMBIENTAL AGUA, AIRE Y SUELO10.24054/raaas.v13i2.272313:2(1-9)Online publication date: 18-Nov-2022
https://doi.org/10.24054/raaas.v13i2.2723
Bastos ASguario Coelho De Andrade MYoshino RSantos M(2021)Industry 4.0 Readiness Assessment Method Based on RAMI 4.0 StandardsIEEE Access10.1109/ACCESS.2021.31054569(119778-119799)Online publication date: 2021
https://doi.org/10.1109/ACCESS.2021.3105456

Index Terms

Environmental Big Data: a systematic mapping study
1. General and reference
  1. Cross-computing tools and techniques
    1. Metrics
  2. Document types
    1. Surveys and overviews

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cover image ACM SIGSOFT Software Engineering Notes

ACM SIGSOFT Software Engineering Notes Volume 41, Issue 6

November 2016

110 pages

ISSN:0163-5948

DOI:10.1145/3011286

Editor:
John Georgas
Northern Arizona University, USA

Issue’s Table of Contents

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

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Published: 05 January 2017

Published in SIGSOFT Volume 41, Issue 6

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Kleisner KPokorný ŠČerný V(2023)Sexually dimorphic traits are associated with subsistence strategy in African faces from the Sahel/Savannah beltAmerican Journal of Human Biology10.1002/ajhb.2400836:4Online publication date: 28-Oct-2023
https://doi.org/10.1002/ajhb.24008
Camargo A LMedina D BGómez R J(2022)PROTOTIPO ELECTRÓNICO IoT PARA EL SEGUIMIENTO DE VARIABLES AMBIENTALESREVISTA AMBIENTAL AGUA, AIRE Y SUELO10.24054/raaas.v13i2.272313:2(1-9)Online publication date: 18-Nov-2022
https://doi.org/10.24054/raaas.v13i2.2723
Bastos ASguario Coelho De Andrade MYoshino RSantos M(2021)Industry 4.0 Readiness Assessment Method Based on RAMI 4.0 StandardsIEEE Access10.1109/ACCESS.2021.31054569(119778-119799)Online publication date: 2021
https://doi.org/10.1109/ACCESS.2021.3105456

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Analysis of Big Data technologies for use in agro-environmental science

A Brief Survey on Big Data in Healthcare

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