Analysing data quality frameworks and evaluating the statistical output of United Nations Sustainable Development Goals’ reports
This paper evaluates the quality of the United Nations Sustainable Development Goals’ report for 2020, and devises a new data quality assessment framework based on analysing many data quality frameworks. Data in this paper is collected from the official UN SDG official website, and the national stat...
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Format: | Article |
Language: | English |
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EDP Sciences
2022-01-01
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Series: | Renewable Energy and Environmental Sustainability |
Subjects: | |
Online Access: | https://www.rees-journal.org/articles/rees/full_html/2022/01/rees210081/rees210081.html |
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author | Al-Salim Wajdi Darwish Abdul Salam K. Farrell Peter |
author_facet | Al-Salim Wajdi Darwish Abdul Salam K. Farrell Peter |
author_sort | Al-Salim Wajdi |
collection | DOAJ |
description | This paper evaluates the quality of the United Nations Sustainable Development Goals’ report for 2020, and devises a new data quality assessment framework based on analysing many data quality frameworks. Data in this paper is collected from the official UN SDG official website, and the national statistics offices of the UN countries. A weighted-score sum module is also being utilized to find the best data quality dimension. These dimensions are then used to create a new data quality framework. It is found that the UN SDGs used a data quality framework that is based on statistical output factors and ignores other quality factors and therefore the score for assessing this report is 56%. The perceived identified gaps include: countries are using different quality and assessment frameworks which cause inconsistency in data quality; data is outdated and incomplete; data is not available for many indicators and countries; cost and efficiency are not part of the UN SDG data quality framework; therefore weak data management is found. Areas for improvement include creating one comprehensive data quality framework for all countries will ensure the highest data quality. |
first_indexed | 2024-04-13T15:51:21Z |
format | Article |
id | doaj.art-c3d6f691fd52470fa87e5e93c2f51dc2 |
institution | Directory Open Access Journal |
issn | 2493-9439 |
language | English |
last_indexed | 2024-04-13T15:51:21Z |
publishDate | 2022-01-01 |
publisher | EDP Sciences |
record_format | Article |
series | Renewable Energy and Environmental Sustainability |
spelling | doaj.art-c3d6f691fd52470fa87e5e93c2f51dc22022-12-22T02:40:50ZengEDP SciencesRenewable Energy and Environmental Sustainability2493-94392022-01-0171710.1051/rees/2022003rees210081Analysing data quality frameworks and evaluating the statistical output of United Nations Sustainable Development Goals’ reportsAl-Salim Wajdi0https://orcid.org/0000-0002-2787-8812Darwish Abdul Salam K.1Farrell Peter2University of BoltonUniversity of BoltonUniversity of BoltonThis paper evaluates the quality of the United Nations Sustainable Development Goals’ report for 2020, and devises a new data quality assessment framework based on analysing many data quality frameworks. Data in this paper is collected from the official UN SDG official website, and the national statistics offices of the UN countries. A weighted-score sum module is also being utilized to find the best data quality dimension. These dimensions are then used to create a new data quality framework. It is found that the UN SDGs used a data quality framework that is based on statistical output factors and ignores other quality factors and therefore the score for assessing this report is 56%. The perceived identified gaps include: countries are using different quality and assessment frameworks which cause inconsistency in data quality; data is outdated and incomplete; data is not available for many indicators and countries; cost and efficiency are not part of the UN SDG data quality framework; therefore weak data management is found. Areas for improvement include creating one comprehensive data quality framework for all countries will ensure the highest data quality.https://www.rees-journal.org/articles/rees/full_html/2022/01/rees210081/rees210081.htmldata quality assessment frameworkfactors of data qualitydimensions of data quality indicatorsdata quality managementdata governanceun sdgs |
spellingShingle | Al-Salim Wajdi Darwish Abdul Salam K. Farrell Peter Analysing data quality frameworks and evaluating the statistical output of United Nations Sustainable Development Goals’ reports Renewable Energy and Environmental Sustainability data quality assessment framework factors of data quality dimensions of data quality indicators data quality management data governance un sdgs |
title | Analysing data quality frameworks and evaluating the statistical output of United Nations Sustainable Development Goals’ reports |
title_full | Analysing data quality frameworks and evaluating the statistical output of United Nations Sustainable Development Goals’ reports |
title_fullStr | Analysing data quality frameworks and evaluating the statistical output of United Nations Sustainable Development Goals’ reports |
title_full_unstemmed | Analysing data quality frameworks and evaluating the statistical output of United Nations Sustainable Development Goals’ reports |
title_short | Analysing data quality frameworks and evaluating the statistical output of United Nations Sustainable Development Goals’ reports |
title_sort | analysing data quality frameworks and evaluating the statistical output of united nations sustainable development goals reports |
topic | data quality assessment framework factors of data quality dimensions of data quality indicators data quality management data governance un sdgs |
url | https://www.rees-journal.org/articles/rees/full_html/2022/01/rees210081/rees210081.html |
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