Cargando…

Leveraging Big Data and Analytics to Improve Food, Energy, and Water System Sustainability

With the world population projected to grow significantly over the next few decades, and in the presence of additional stress caused by climate change and urbanization, securing the essential resources of food, energy, and water is one of the most pressing challenges that the world faces today. Ther...

Descripción completa

Detalles Bibliográficos
Autores principales: Pitts, Joshua, Gopal, Sucharita, Ma, Yaxiong, Koch, Magaly, Boumans, Roelof M., Kaufman, Les
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7931953/
https://www.ncbi.nlm.nih.gov/pubmed/33693388
http://dx.doi.org/10.3389/fdata.2020.00013
_version_ 1783660390651002880
author Pitts, Joshua
Gopal, Sucharita
Ma, Yaxiong
Koch, Magaly
Boumans, Roelof M.
Kaufman, Les
author_facet Pitts, Joshua
Gopal, Sucharita
Ma, Yaxiong
Koch, Magaly
Boumans, Roelof M.
Kaufman, Les
author_sort Pitts, Joshua
collection PubMed
description With the world population projected to grow significantly over the next few decades, and in the presence of additional stress caused by climate change and urbanization, securing the essential resources of food, energy, and water is one of the most pressing challenges that the world faces today. There is an increasing priority placed by the United Nations (UN) and US federal agencies on efforts to ensure the security of these critical resources, understand their interactions, and address common underlying challenges. At the heart of the technological challenge is data science applied to environmental data. The aim of this special publication is the focus on big data science for food, energy, and water systems (FEWSs). We describe a research methodology to frame in the FEWS context, including decision tools to aid policy makers and non-governmental organizations (NGOs) to tackle specific UN Sustainable Development Goals (SDGs). Through this exercise, we aim to improve the “supply chain” of FEWS research, from gathering and analyzing data to decision tools supporting policy makers in addressing FEWS issues in specific contexts. We discuss prior research in each of the segments to highlight shortcomings as well as future research directions.
format Online
Article
Text
id pubmed-7931953
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-79319532021-03-09 Leveraging Big Data and Analytics to Improve Food, Energy, and Water System Sustainability Pitts, Joshua Gopal, Sucharita Ma, Yaxiong Koch, Magaly Boumans, Roelof M. Kaufman, Les Front Big Data Big Data With the world population projected to grow significantly over the next few decades, and in the presence of additional stress caused by climate change and urbanization, securing the essential resources of food, energy, and water is one of the most pressing challenges that the world faces today. There is an increasing priority placed by the United Nations (UN) and US federal agencies on efforts to ensure the security of these critical resources, understand their interactions, and address common underlying challenges. At the heart of the technological challenge is data science applied to environmental data. The aim of this special publication is the focus on big data science for food, energy, and water systems (FEWSs). We describe a research methodology to frame in the FEWS context, including decision tools to aid policy makers and non-governmental organizations (NGOs) to tackle specific UN Sustainable Development Goals (SDGs). Through this exercise, we aim to improve the “supply chain” of FEWS research, from gathering and analyzing data to decision tools supporting policy makers in addressing FEWS issues in specific contexts. We discuss prior research in each of the segments to highlight shortcomings as well as future research directions. Frontiers Media S.A. 2020-04-28 /pmc/articles/PMC7931953/ /pubmed/33693388 http://dx.doi.org/10.3389/fdata.2020.00013 Text en Copyright © 2020 Pitts, Gopal, Ma, Koch, Boumans and Kaufman. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Big Data
Pitts, Joshua
Gopal, Sucharita
Ma, Yaxiong
Koch, Magaly
Boumans, Roelof M.
Kaufman, Les
Leveraging Big Data and Analytics to Improve Food, Energy, and Water System Sustainability
title Leveraging Big Data and Analytics to Improve Food, Energy, and Water System Sustainability
title_full Leveraging Big Data and Analytics to Improve Food, Energy, and Water System Sustainability
title_fullStr Leveraging Big Data and Analytics to Improve Food, Energy, and Water System Sustainability
title_full_unstemmed Leveraging Big Data and Analytics to Improve Food, Energy, and Water System Sustainability
title_short Leveraging Big Data and Analytics to Improve Food, Energy, and Water System Sustainability
title_sort leveraging big data and analytics to improve food, energy, and water system sustainability
topic Big Data
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7931953/
https://www.ncbi.nlm.nih.gov/pubmed/33693388
http://dx.doi.org/10.3389/fdata.2020.00013
work_keys_str_mv AT pittsjoshua leveragingbigdataandanalyticstoimprovefoodenergyandwatersystemsustainability
AT gopalsucharita leveragingbigdataandanalyticstoimprovefoodenergyandwatersystemsustainability
AT mayaxiong leveragingbigdataandanalyticstoimprovefoodenergyandwatersystemsustainability
AT kochmagaly leveragingbigdataandanalyticstoimprovefoodenergyandwatersystemsustainability
AT boumansroelofm leveragingbigdataandanalyticstoimprovefoodenergyandwatersystemsustainability
AT kaufmanles leveragingbigdataandanalyticstoimprovefoodenergyandwatersystemsustainability