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The challenge is the integration of citizens as “community-based” observation providers, giving the odour perception and discomfort and getting feed-back in real time from a learning monitoring system. The level of annoyance de-pends on how odours are emitted and in what intensity, their dispersion under ambient atmospheric conditions and finally o...
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... biodiversity and environmental phenomena or conditions using image acquisition, web-and smartphone-based applications and surveys (Couvet and Prevot 2015;Havlik and Schimak 2014;Wallace, Snedigar, and Cameron 2015). More and more CS projects also explore the use of low-cost devices, including handheld or portable sensor systems Thompson 2016;Uhrner et al. 2014). Data collected are increasingly visualized in web-based portals or via smart phone apps in near real time. ...
... The experts and CS practitioners involved in the projects include, but are not limited to, environmental scientists, social scientists, hardware and software specialists, and data analysts. Depending on the type of CS project, the target group of volunteers and other stakeholders might involve locals living nearby who are affected by the issue at hand (Grossberndt and Liu 2016;Uhrner et al. 2014), schools (Hunt et al. 2015;Kobernus et al. 2013;Momin o, Piera, and Jurado 2016), representatives of local officials (Mietlicki, Gaudibert, and Vincent 2012) and do-it-yourself (DIY) communities (Busch et al. 2016). In addition, external stakeholders such as scientists from other domains, NGOs, and government agencies may want to harness the data for various purposes, such as complementing their own data sets (Cooper et al. 2017;Ferster and Coops 2013;Hunt et al. 2015;Wehn and Evers 2015). ...
Citizen Science (CS) projects vary greatly. The aims and goals of a CS project determine the type of citizen involvement and the tools to be used, which in most cases also entail information and communication technology (ICT) that facilitates public participation in scientific research. Resource limitations in CS projects often require adopting suboptimal tools, which, however, may come with hidden costs stemming from poor usability and underwhelming functionality, thus reducing volunteers’ motivation. Meeting the volunteers’ expectations by designing or using existing tools with functional features which fulfill and nurture their motivations, will foster long-term participation and contribute to project sustainability. This paper reviews the types of CS projects, volunteer motivation and retention strategies from the literature and classifies them thematically. This is distilled into guidance that can help CS practitioners to design and implement CS tools and plan and manage CS projects, which better serve their scientific and volunteer-related goals.
... Citizen observatories have been researched in several EU-funded projects. Finished projects (CITI-SENSE, Citclops, COBWEB, OMNISCIENTIS and WeSenseIt) have already resulted in valuable contributions to the field ( Alfonso et al., 2015;Aspuru et al., 2016;Friedrichs et al., 2014;Higgins et al., 2016;Uhrner et al., 2013). For example, the CITISENSE project managed to simultaneously collect perception data and acoustic measurements in an approach that can be used to develop citizen empowerment initiatives in case of noise management ( Aspuru et al., 2016), while in COBWEB project processes of quality assurance, data conflation and data fusion were studied and recommendations were made ( Friedrichs et al., 2014). ...
Citizen contributions to science have been successfully implemented in many fields, and water resources is one of them. Through citizens, it is possible to collect data and obtain a more integrated decision-making process. Specifically, data scarcity has always been an issue in flood modelling, which has been addressed in the last decades by remote sensing and is already being discussed in the citizen science context. With this in mind, this article aims to review the literature on the topic and analyse the opportunities and challenges that lie ahead. The literature on monitoring, mapping and modelling, was evaluated according to the flood-related variable citizens contributed to. Pros and cons of the collection/analysis methods were summarised. Then, pertinent publications were mapped into the flood modelling cycle, considering how citizen data properties (spatial and temporal coverage, uncertainty and volume) are related to its integration into modelling. It was clear that the number of studies in the area is rising. There are positive experiences reported in collection and analysis methods, for instance with velocity and land cover, and also when modelling is concerned, for example by using social media mining. However, matching the data properties necessary for each part of the modelling cycle with citizen-generated data is still challenging. Nevertheless, the concept that citizen contributions can be used for simulation and forecasting is proved and further work lies in continuing to develop and improve not only methods for collection and analysis, but certainly for integration into models as well. Finally, in view of recent automated sensors and satellite technologies, it is through studies as the ones analysed in this article that the value of citizen contributions, complementing such technologies, is demonstrated.
... This article is based on the work performed in the FP7 European project OMNISCIENTIS ( (Ledent et al. 2013), (OMNISCIENTIS 2014)). In this project, we propose an approach which relies on the establishment of a physical and intellectual space which drives the management of interaction between industry, citizens' representatives and public authorities impacted by an environmental problem (odour emission). ...
... Sometimes they may be asked to contribute to solving the problem in "passive" observatories, allowing them to complain but, in the majority of cases, without getting feedback in return. Their input is seldom used to validate the results of models or measuring devices such as e-noses (Ledent et al. 2013). ...
Vendors’ Challenges in e‐Government Projects in
Pakistan: Experience Report of Prisons Automation
Citizen contributions to science have been successfully implemented in many fields – and water resources is one of them. Through citizens, it is possible to collect data and obtain a more integrated decision-making process. Specifically, data scarcity has always been an issue in flood modelling, which has been addressed in the last decades by remote sensing and is already being discussed in a citizen science scenario. In this context, this article aims to review the literature on the topic and analyse the opportunities and challenges that lie ahead. The literature on monitoring, mapping and modelling, was evaluated according to the flood-related variable citizens contributed to. Pros and cons of the collection/analysis methods were summarised. Then, pertinent publications were mapped into the flood modelling cycle, considering how citizen data properties (spatial and temporal coverage, uncertainty and volume) are related to its integration into modelling. It was clear that the number of studies in the area is rising. There are positive experiences reported in collection and analysis methods, for instance with velocity and land cover, and also when modelling is concerned, for example by using social media mining. However, matching the data properties necessary for each part of the modelling cycle with citizen generated data is still challenging. Nevertheless, the concept that citizen contributions can be used for simulation and forecasting is proved and further work lies in continuing developing and improving not only methods for collection and analysis but certainly for integration into models as well. Finally, in view of recent automated sensors and satellite technologies, it is through studies as the ones analysed in this article that the value of citizen contributions is demonstrated.
