Project description DEENESFRITPL Making the most of citizen science in nature Citizen science is a broad term used to describe the general public’s engagement in scientific research activities. It spans a range of levels of engagement: from being better informed about science to participating in the scientific process (observing, gathering or processing data). Citizen science can be particularly valuable for society, ecology and conservation. The EU-funded OptimCS project will build a workflow to maximise the information that citizen scientists contribute to our collective knowledge of biodiversity. The data collection power of citizen science is enormous, but as citizen science at this scale is a new development in ecology and conservation, there is a great deal of inefficiency in this process. Show the project objective Hide the project objective Objective Citizen science – research conducted in whole or in part by people for whom science is not their profession – is increasingly valuable for society, ecology, and conservation. Natural resource and landscape management based on the best available science is increasingly relying, at least in part, on citizen science data to make informed and adaptive decisions supporting biodiversity conservation . The data collection power of citizen science is enormous, but as citizen science at this scale is a new development in ecology and conservation, there is a great deal of inefficiency in this process. The largest inefficiency is that, to this point, the most ‘successful’ citizen science projects generally have a haphazard sampling regime replete with redundancies and gaps in the associated citizen science data. Can we direct this enormous amount of effort more efficiently? What steps can be taken at the upstream portion of citizen science projects to maximise efficiency of analyses with downstream datasets? This project will build a workflow which allows us to maximise the information content that citizen scientists contribute to our collective knowledge of biodiversity by developing algorithms that predict the highest ‘valued’ sites in time and space for biodiversity sampling by citizen scientists which leads to more efficiently directing effort in space and time. Fields of science natural sciencescomputer and information sciencesdata sciencebig datanatural sciencesbiological sciencesbiodiversity conservationnatural sciencesbiological sciencesecologyecosystemssocial sciencespolitical sciencespolitical policiescivil society Keywords ecological modelling species distribution models citizen science biodiversity trend models pareto frontier Programme(s) H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions Main Programme H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility Topic(s) MSCA-IF-2019 - Individual Fellowships Call for proposal H2020-MSCA-IF-2019 See other projects for this call Funding Scheme MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF) Coordinator MARTIN-LUTHER-UNIVERSITAT HALLE-WITTENBERG Net EU contribution € 174 806,40 Address Universitatsplatz 10 6108 Halle Germany See on map Region Baden-Württemberg Stuttgart Stuttgart, Stadtkreis Activity type Higher or Secondary Education Establishments Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Other funding € 0,00
