Mapping citizen science contributions to the UN sustainable development goals
17 pages, 4 figures, supplementary material https://doi.org/10.1007/s11625-020-00833-7
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Format: | artículo biblioteca |
Language: | English |
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2020-11
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Subjects: | Sustainable Development Goals (SDGs), Citizen science, SDG indicators, Tier classification for SDG indicators, Crowdsourcing, Community-based monitoring, |
Online Access: | http://hdl.handle.net/10261/216096 http://dx.doi.org/10.13039/501100011859 http://dx.doi.org/10.13039/501100000780 http://dx.doi.org/10.13039/501100011033 |
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dig-icm-es-10261-2160962021-04-06T11:22:17Z Mapping citizen science contributions to the UN sustainable development goals Fraisl, Dilek Campbell, Jillian See, Linda Wehn, Uta Wardlaw, Jessica Gold, Margaret Moorthy, I. Arias, Rosa Piera, Jaume Oliver, Jessica L. Masó, Joan Penker, Marianne Fritz, Steffen International Institute for Applied Systems Analysis European Commission Agencia Estatal de Investigación (España) Sustainable Development Goals (SDGs) Citizen science SDG indicators Tier classification for SDG indicators Crowdsourcing Community-based monitoring 17 pages, 4 figures, supplementary material https://doi.org/10.1007/s11625-020-00833-7 The UN Sustainable Development Goals (SDGs) are a vision for achieving a sustainable future. Reliable, timely, comprehensive, and consistent data are critical for measuring progress towards, and ultimately achieving, the SDGs. Data from citizen science represent one new source of data that could be used for SDG reporting and monitoring. However, information is still lacking regarding the current and potential contributions of citizen science to the SDG indicator framework. Through a systematic review of the metadata and work plans of the 244 SDG indicators, as well as the identification of past and ongoing citizen science initiatives that could directly or indirectly provide data for these indicators, this paper presents an overview of where citizen science is already contributing and could contribute data to the SDG indicator framework. The results demonstrate that citizen science is “already contributing” to the monitoring of 5 SDG indicators, and that citizen science “could contribute” to 76 indicators, which, together, equates to around 33%. Our analysis also shows that the greatest inputs from citizen science to the SDG framework relate to SDG 15 Life on Land, SDG 11 Sustainable Cities and Communities, SDG 3 Good Health and Wellbeing, and SDG 6 Clean Water and Sanitation. Realizing the full potential of citizen science requires demonstrating its value in the global data ecosystem, building partnerships around citizen science data to accelerate SDG progress, and leveraging investments to enhance its use and impact Open access funding provided by International Institute for Applied Systems Analysis (IIASA). [...] This research received funding from the EU FP7 ERC CrowdLand project (No. 617754) and the EU Horizon 2020 research and innovation programme under the WeObserve project (No. 776740) With the funding support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), of the Spanish Research Agency (AEI) Peer reviewed 2020-07-07T09:07:33Z 2020-07-07T09:07:33Z 2020-11 artículo http://purl.org/coar/resource_type/c_6501 Sustainability Science 15(6): 1735-1751 (2020) 1862-4065 CEX2019-000928-S http://hdl.handle.net/10261/216096 10.1007/s11625-020-00833-7 1862-4057 http://dx.doi.org/10.13039/501100011859 http://dx.doi.org/10.13039/501100000780 http://dx.doi.org/10.13039/501100011033 en #PLACEHOLDER_PARENT_METADATA_VALUE# #PLACEHOLDER_PARENT_METADATA_VALUE# info:eu-repo/grantAgreement/EC/FP7/617754 info:eu-repo/grantAgreement/EC/H2020/776740 Postprint https://doi.org/10.1007/s11625-020-00833-7 Sí open |
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Sustainable Development Goals (SDGs) Citizen science SDG indicators Tier classification for SDG indicators Crowdsourcing Community-based monitoring Sustainable Development Goals (SDGs) Citizen science SDG indicators Tier classification for SDG indicators Crowdsourcing Community-based monitoring |
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Sustainable Development Goals (SDGs) Citizen science SDG indicators Tier classification for SDG indicators Crowdsourcing Community-based monitoring Sustainable Development Goals (SDGs) Citizen science SDG indicators Tier classification for SDG indicators Crowdsourcing Community-based monitoring Fraisl, Dilek Campbell, Jillian See, Linda Wehn, Uta Wardlaw, Jessica Gold, Margaret Moorthy, I. Arias, Rosa Piera, Jaume Oliver, Jessica L. Masó, Joan Penker, Marianne Fritz, Steffen Mapping citizen science contributions to the UN sustainable development goals |
description |
17 pages, 4 figures, supplementary material https://doi.org/10.1007/s11625-020-00833-7 |
author2 |
International Institute for Applied Systems Analysis |
author_facet |
International Institute for Applied Systems Analysis Fraisl, Dilek Campbell, Jillian See, Linda Wehn, Uta Wardlaw, Jessica Gold, Margaret Moorthy, I. Arias, Rosa Piera, Jaume Oliver, Jessica L. Masó, Joan Penker, Marianne Fritz, Steffen |
format |
artículo |
topic_facet |
Sustainable Development Goals (SDGs) Citizen science SDG indicators Tier classification for SDG indicators Crowdsourcing Community-based monitoring |
author |
Fraisl, Dilek Campbell, Jillian See, Linda Wehn, Uta Wardlaw, Jessica Gold, Margaret Moorthy, I. Arias, Rosa Piera, Jaume Oliver, Jessica L. Masó, Joan Penker, Marianne Fritz, Steffen |
author_sort |
Fraisl, Dilek |
title |
Mapping citizen science contributions to the UN sustainable development goals |
title_short |
Mapping citizen science contributions to the UN sustainable development goals |
title_full |
Mapping citizen science contributions to the UN sustainable development goals |
title_fullStr |
Mapping citizen science contributions to the UN sustainable development goals |
title_full_unstemmed |
Mapping citizen science contributions to the UN sustainable development goals |
title_sort |
mapping citizen science contributions to the un sustainable development goals |
publishDate |
2020-11 |
url |
http://hdl.handle.net/10261/216096 http://dx.doi.org/10.13039/501100011859 http://dx.doi.org/10.13039/501100000780 http://dx.doi.org/10.13039/501100011033 |
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