The value of marine ecological data collected by volunteers

Foster-Smith, Judy; Evans, Stewart M.

doi:10.1016/s0006-3207(02)00373-7

Cited by 157 publications

(149 citation statements)

References 15 publications

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“…On average, observers detected 38 % of the models and ranged from 0 to 75 %, comparable to other work (Foster-Smith and Evans 2003). The majority of models detected were snakes (41 %), followed by frogs (33 %) and lizards (26 %).…”

Section: Resultssupporting

confidence: 81%

“…Data collected by volunteers often contribute significantly to research projects, especially when guided by experienced scientists (Foster-Smith and Evans 2003). This 'citizen-science' model has also been applied within the tourism industry to generate what has been termed 'conservation voluntourism', 'scientific tourism' or, relatedly, the 'conservation holiday' (Brown and Morrison 2003).…”

Section: Introductionmentioning

confidence: 99%

“…Many components of scientific research can be learned relatively quickly and volunteers, if sufficiently trained, can gather high quality data (Foster-Smith and Evans 2003;Newman et al 2003). However for some tasks, the learning is more protracted, with expertise slow to accumulate and the data collected by novice volunteers has sometimes been questioned (Cohn 2008;Léopold et al 2009).…”

Section: Introductionmentioning

confidence: 99%

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How useful are volunteers for visual biodiversity surveys? An evaluation of skill level and group size during a conservation expedition

et al. 2016

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The ability of volunteers to undertake different tasks and accurately collect data is critical for the success of many conservation projects. In this study, a simulated herpetofauna visual encounter survey was used to compare the detection and distance estimation accuracy of volunteers and more experienced observers. Experience had a positive effect on individual detection accuracy. However, lower detection performance of less experienced volunteers was not found in the group data, with larger groups being more successful overall, suggesting that working in groups facilitates detection accuracy of those with less experience. This study supports the idea that by optimizing survey protocols according to the available resources (time and volunteer numbers), the sampling efficiency of monitoring programs can be improved and that non-expert volunteers can provide valuable contributions to visual encounter-based biodiversity surveys. Recommendations are made for the improvement of survey methodology involving non-expert volunteers.

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Section: Resultssupporting

confidence: 81%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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How useful are volunteers for visual biodiversity surveys? An evaluation of skill level and group size during a conservation expedition

et al. 2016

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“…For example, data inconsistency may result from volunteers' lack of experience, inadequate guidelines and insufficient training [4], "rolled up" into larger monitoring projects [6]. Training, while generally desirable, may not always be possible, especially for low budget projects.…”

Section: The Challenge -Facilitating Participationmentioning

confidence: 99%

“…Yet, given the expertise and language gap between scientists and ordinary people, information transfer in citizen science projects is not straightforward. While citizen scientists can offer insights and generate new ideas [4], their lack of training and expertise results in inconsistent and incorrect data [5,6,7]. In particular, where direct elicitation of people's opinions is required we can expect lower scientific accuracy of data as wider audiences with lesser expertise get engaged.…”

Section: Introductionmentioning

confidence: 99%

Citizen Science 2.0: Data Management Principles to Harness the Power of the Crowd

Lukyanenko

Parsons

Wiersma

2011

Service-Oriented Perspectives in Design Science Research

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Abstract. Citizen science refers to voluntary participation by the general public in scientific endeavors. Although citizen science has a long tradition, the rise of online communities and user-generated web content has the potential to greatly expand its scope and contributions. Citizens spread across a large area will collect more information than an individual researcher can. Because citizen scientists tend to make observations about areas they know well, data are likely to be very detailed. Although the potential for engaging citizen scientists is extensive, there are challenges as well. In this paper we consider one such challenge -creating an environment in which non-experts in a scientific domain can provide appropriate and accurate data regarding their observations. We describe the problem in the context of a research project that includes the development of a website to collect citizen-generated data on the distribution of plants and animals in a geographic region. We propose an approach that can improve the quantity and quality of data collected in such projects by organizing data using instance-based data structures. Potential implications of this approach are discussed and plans for future research to validate the design are described.

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