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Datasets for a multidimensional analysis connecting clean energy access and social development in sub-Saharan Africa
In this article we present datasets used for the construction of a composite indicator, the Social Clean Energy Access (Social CEA) Index, presented in detail in [1]. This article consists of comprehensive social development data related to electricity access, collected from several sources, and pro...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9969243/ https://www.ncbi.nlm.nih.gov/pubmed/36860406 http://dx.doi.org/10.1016/j.dib.2023.108948 |
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author | Casati, Paola Moner-Girona, Magda Shehu, Ibrahim Khaleel Szabó, Sandor Nhamo, Godwell |
author_facet | Casati, Paola Moner-Girona, Magda Shehu, Ibrahim Khaleel Szabó, Sandor Nhamo, Godwell |
author_sort | Casati, Paola |
collection | PubMed |
description | In this article we present datasets used for the construction of a composite indicator, the Social Clean Energy Access (Social CEA) Index, presented in detail in [1]. This article consists of comprehensive social development data related to electricity access, collected from several sources, and processed according to the methodology described in [1]. The new composite index includs 24 indicators capturing the status of the social dimensions related to electricity access for 35 SSA countries. The development of the Social CEA Index was supported by an extensive review of the literature about electricity access and social development which led to the selection of its indicators. The structure was evaluated for its soundness using correlational assessments and principal component analyses. The raw data provided allow stakeholders to focus on specific country indicators and to observe how scores on these indicators contributed to a country overall rank. The Social CEA Index also allows to understand the number of best performing countries (out of a total of 35) for each indicator. This allows different stakeholders to identify which the weakest dimensions are of social development and thus help in addressing priorities for action for funding towards specific electrification projects. The data can be used to assign weights according to stakeholders’ specific requirements. Finally, the dataset can be used for the case of Ghana to monitor the Social CEA Index progress over time through a dimension's breakdown approach. |
format | Online Article Text |
id | pubmed-9969243 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-99692432023-02-28 Datasets for a multidimensional analysis connecting clean energy access and social development in sub-Saharan Africa Casati, Paola Moner-Girona, Magda Shehu, Ibrahim Khaleel Szabó, Sandor Nhamo, Godwell Data Brief Data Article In this article we present datasets used for the construction of a composite indicator, the Social Clean Energy Access (Social CEA) Index, presented in detail in [1]. This article consists of comprehensive social development data related to electricity access, collected from several sources, and processed according to the methodology described in [1]. The new composite index includs 24 indicators capturing the status of the social dimensions related to electricity access for 35 SSA countries. The development of the Social CEA Index was supported by an extensive review of the literature about electricity access and social development which led to the selection of its indicators. The structure was evaluated for its soundness using correlational assessments and principal component analyses. The raw data provided allow stakeholders to focus on specific country indicators and to observe how scores on these indicators contributed to a country overall rank. The Social CEA Index also allows to understand the number of best performing countries (out of a total of 35) for each indicator. This allows different stakeholders to identify which the weakest dimensions are of social development and thus help in addressing priorities for action for funding towards specific electrification projects. The data can be used to assign weights according to stakeholders’ specific requirements. Finally, the dataset can be used for the case of Ghana to monitor the Social CEA Index progress over time through a dimension's breakdown approach. Elsevier 2023-02-07 /pmc/articles/PMC9969243/ /pubmed/36860406 http://dx.doi.org/10.1016/j.dib.2023.108948 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Casati, Paola Moner-Girona, Magda Shehu, Ibrahim Khaleel Szabó, Sandor Nhamo, Godwell Datasets for a multidimensional analysis connecting clean energy access and social development in sub-Saharan Africa |
title | Datasets for a multidimensional analysis connecting clean energy access and social development in sub-Saharan Africa |
title_full | Datasets for a multidimensional analysis connecting clean energy access and social development in sub-Saharan Africa |
title_fullStr | Datasets for a multidimensional analysis connecting clean energy access and social development in sub-Saharan Africa |
title_full_unstemmed | Datasets for a multidimensional analysis connecting clean energy access and social development in sub-Saharan Africa |
title_short | Datasets for a multidimensional analysis connecting clean energy access and social development in sub-Saharan Africa |
title_sort | datasets for a multidimensional analysis connecting clean energy access and social development in sub-saharan africa |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9969243/ https://www.ncbi.nlm.nih.gov/pubmed/36860406 http://dx.doi.org/10.1016/j.dib.2023.108948 |
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