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The SDGs reflect a data-driven and society-oriented framework that requires a collaborative action from all levels of society to achieve the future we want while leaving no one behind. Crucial to the success of this framework is timely, reliable and comprehensive data that are difficult to gather using traditional sources of data alone. Coupled with the traditional methods and other new sources of data such as Earth Observation (EO), citizen science has a great potential to address the data gaps and needs in the SDG framework. A recent study by Fraisl et al shows that citizen science data have the potential to contribute data to 33% of the SDG indicators. This session aims to introduce Citizen Science to the official statistics community and demonstrate the value of citizen science for monitoring the SDGs, drawing upon concrete examples that outline the use of citizen science data by NSOs and UN agencies. The challenges and barriers for the uptake of citizen science data for feeding into SDG monitoring processes will be discussed, and how we can bring it into the scope of official statistics through recognition by governments, national statistical offices (NSOs), the UN system, and other data producers and users, from the perspective of the representatives of all these stakeholders.

The SDGs reflect a data-driven and society-oriented framework that requires a collaborative action from all levels of society to achieve the future we want while leaving no one behind. Crucial to the success of this framework is timely, reliable and comprehensive data that are difficult to gather using traditional sources of data alone. Coupled with the traditional methods and other new sources of data such as Earth Observation (EO), citizen science has a great potential to address the data gaps and needs in the SDG framework. A recent study by Fraisl et al shows that citizen science data have the potential to contribute data to 33% of the SDG indicators. This session aims to introduce Citizen Science to the official statistics community and demonstrate the value of citizen science for monitoring the SDGs, drawing upon concrete examples that outline the use of citizen science data by NSOs and UN agencies. The challenges and barriers for the uptake of citizen science data for feeding into SDG monitoring processes will be discussed, and how we can bring it into the scope of official statistics through recognition by governments, national statistical offices (NSOs), the UN system, and other data producers and users, from the perspective of the representatives of all these stakeholders.

The SDGs are a universal agenda to address the world's most pressing societal, environmental and economic challenges. The supply of timely, relevant and reliable data is essential in guiding policies and decisions for successful implementation of the SDGs. Yet official statistics cannot provide all of the data needed to populate the SDG indicator framework. Citizen science offers a novel solution and an untapped opportunity to complement traditional sources of data, such as household surveys, for monitoring progress towards the SDGs, while at the same time mobilizing action and raising awareness for their achievement. This paper presents the potential offered by one specific citizen science tool, Picture Pile, to complement and enhance official statistics to monitor several SDGs and targets. Designed to be a generic and flexible tool, Picture Pile is a web-based and mobile application for ingesting imagery from satellites, orthophotos, unmanned aerial vehicles or geotagged photographs that can then be rapidly classified by volunteers. The results show that Picture Pile could contribute to the monitoring of fifteen SDG indicators under goals 1, 2, 11, 13, 14 and 15 based on the Picture Pile campaigns undertaken to date. Picture Pile could also be modified to support other SDGs and indicators in the areas of ecosystem health, eutrophication and built-up areas, among others. In order to leverage this particular tool for SDG monitoring, its potential must be showcased through the development of use cases in collaboration with governments, NSOs and relevant custodian agencies. Additionally, mutual trust needs to be built among key stakeholders to agree on common goals that would facilitate the use of Picture Pile or other citizen science tools and data for SDG monitoring and impact.

The SDGs are a universal agenda to address the world's most pressing societal, environmental and economic challenges. The supply of timely, relevant and reliable data is essential in guiding policies and decisions for successful implementation of the SDGs. Yet official statistics cannot provide all of the data needed to populate the SDG indicator framework. Citizen science offers a novel solution and an untapped opportunity to complement traditional sources of data, such as household surveys, for monitoring progress towards the SDGs, while at the same time mobilizing action and raising awareness for their achievement. This paper presents the potential offered by one specific citizen science tool, Picture Pile, to complement and enhance official statistics to monitor several SDGs and targets. Designed to be a generic and flexible tool, Picture Pile is a web-based and mobile application for ingesting imagery from satellites, orthophotos, unmanned aerial vehicles or geotagged photographs that can then be rapidly classified by volunteers. The results show that Picture Pile could contribute to the monitoring of fifteen SDG indicators under goals 1, 2, 11, 13, 14 and 15 based on the Picture Pile campaigns undertaken to date. Picture Pile could also be modified to support other SDGs and indicators in the areas of ecosystem health, eutrophication and built-up areas, among others. In order to leverage this particular tool for SDG monitoring, its potential must be showcased through the development of use cases in collaboration with governments, NSOs and relevant custodian agencies. Additionally, mutual trust needs to be built among key stakeholders to agree on common goals that would facilitate the use of Picture Pile or other citizen science tools and data for SDG monitoring and impact.

There are many new land use and land cover (LULC) products emerging yet there is still a lack of in situ data for training, validation, and change detection purposes. The LUCAS (Land Use Cover Area frame Sample) survey is one of the few authoritative in situ field campaigns, which takes place every three years in European Union member countries. More recently, a study has considered whether citizen science and crowdsourcing could complement LUCAS survey data, e.g., through the FotoQuest Austria mobile app and crowdsourcing campaign. Although the data obtained from the campaign were promising when compared with authoritative LUCAS survey data, there were classes that were not well classified by the citizens. Moreover, the photographs submitted through the app were not always of sufficient quality. For these reasons, in the latest FotoQuest Go Europe 2018 campaign, several improvements were made to the app to facilitate interaction with the citizens contributing and to improve their accuracy in LULC identification. In addition to extending the locations from Austria to Europe, a change detection component (comparing land cover in 2018 to the 2015 LUCAS photographs) was added, as well as an improved LC decision tree. Furthermore, a near real-time quality assurance system was implemented to provide feedback on the distance to the target location, the LULC classes chosen and the quality of the photographs. Another modification was a monetary incentive scheme in which users received between 1 to 3 Euros for each successfully completed quest of sufficient quality. The purpose of this paper is to determine whether citizens can provide high quality in situ data on LULC through crowdsourcing that can complement LUCAS. We compared the results between the FotoQuest campaigns in 2015 and 2018 and found a significant improvement in 2018, i.e., a much higher match of LC between FotoQuest Go Europe and LUCAS. As shown by the cost comparisons with LUCAS, FotoQuest can complement LUCAS surveys by enabling continuous collection of large amounts of high quality, spatially explicit field data at a low cost.

There are many new land use and land cover (LULC) products emerging yet there is still a lack of in situ data for training, validation, and change detection purposes. The LUCAS (Land Use Cover Area frame Sample) survey is one of the few authoritative in situ field campaigns, which takes place every three years in European Union member countries. More recently, a study has considered whether citizen science and crowdsourcing could complement LUCAS survey data, e.g., through the FotoQuest Austria mobile app and crowdsourcing campaign. Although the data obtained from the campaign were promising when compared with authoritative LUCAS survey data, there were classes that were not well classified by the citizens. Moreover, the photographs submitted through the app were not always of sufficient quality. For these reasons, in the latest FotoQuest Go Europe 2018 campaign, several improvements were made to the app to facilitate interaction with the citizens contributing and to improve their accuracy in LULC identification. In addition to extending the locations from Austria to Europe, a change detection component (comparing land cover in 2018 to the 2015 LUCAS photographs) was added, as well as an improved LC decision tree. Furthermore, a near real-time quality assurance system was implemented to provide feedback on the distance to the target location, the LULC classes chosen and the quality of the photographs. Another modification was a monetary incentive scheme in which users received between 1 to 3 Euros for each successfully completed quest of sufficient quality. The purpose of this paper is to determine whether citizens can provide high quality in situ data on LULC through crowdsourcing that can complement LUCAS. We compared the results between the FotoQuest campaigns in 2015 and 2018 and found a significant improvement in 2018, i.e., a much higher match of LC between FotoQuest Go Europe and LUCAS. As shown by the cost comparisons with LUCAS, FotoQuest can complement LUCAS surveys by enabling continuous collection of large amounts of high quality, spatially explicit field data at a low cost.

The contribution of citizen science to addressing societal challenges has long been recognized. The United Nations (UN) Sustainable Development Goals (SDGs), as an overarching policy framework and a roadmap to guide global development efforts until 2030 for achieving a better future for all, could benefit from the potential that citizen science offers. However, there is a lack of knowledge on the value of citizen science, particularly in addressing the data needs for SDG monitoring, among the UN agencies, national statistical offices, policy makers and the citizen science community itself. To address this challenge, we launched a Community of Practice on Citizen Science and the SDGs (SDGs CoP) in November 2018 as part of the EU Horizon 2020 funded WeObserve project. The SDGs CoP brings together citizen science researchers, practitioners, UN custodian agencies, broader data communities and other key actors to develop an understanding on how to demonstrate the value of citizen science for SDG achievement. The initial focus and the main objective of the SDGs CoP has been to conduct a research study to understand the contribution of citizen science to SDG monitoring and implementation. In this talk, we will present the work of the SDGs CoP. We will first discuss existing data gaps and needs for measuring progress on the SDGs, and then provide an overview on the results of a systematic review that we undertook within the CoP, showing where citizen science is already contributing and could contribute data to the SDG framework. We will provide concrete examples of our findings to demonstrate how citizen science data could inform the SDGs. We will also touch on the challenges for and barriers to the uptake of citizen science data for the SDG monitoring processes, and how to bring this source of data into the scope of official statistics.

The contribution of citizen science to addressing societal challenges has long been recognized. The United Nations (UN) Sustainable Development Goals (SDGs), as an overarching policy framework and a roadmap to guide global development efforts until 2030 for achieving a better future for all, could benefit from the potential that citizen science offers. However, there is a lack of knowledge on the value of citizen science, particularly in addressing the data needs for SDG monitoring, among the UN agencies, national statistical offices, policy makers and the citizen science community itself. To address this challenge, we launched a Community of Practice on Citizen Science and the SDGs (SDGs CoP) in November 2018 as part of the EU Horizon 2020 funded WeObserve project. The SDGs CoP brings together citizen science researchers, practitioners, UN custodian agencies, broader data communities and other key actors to develop an understanding on how to demonstrate the value of citizen science for SDG achievement. The initial focus and the main objective of the SDGs CoP has been to conduct a research study to understand the contribution of citizen science to SDG monitoring and implementation. In this talk, we will present the work of the SDGs CoP. We will first discuss existing data gaps and needs for measuring progress on the SDGs, and then provide an overview on the results of a systematic review that we undertook within the CoP, showing where citizen science is already contributing and could contribute data to the SDG framework. We will provide concrete examples of our findings to demonstrate how citizen science data could inform the SDGs. We will also touch on the challenges for and barriers to the uptake of citizen science data for the SDG monitoring processes, and how to bring this source of data into the scope of official statistics.