Lights, Camera…Citizen Science: Assessing the Effectiveness of Smartphone-Based Video Training in Invasive Plant Identification

Starr, Jared; Schweik, Charles M.; Bush, Nathan; Fletcher, Lena; Finn, John T.; Fish, Jennifer N.; Bargeron, Charles T.

doi:10.1371/journal.pone.0111433

Cited by 50 publications

(55 citation statements)

References 12 publications

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“…With suitable resource allocation and a training protocol (e.g., Kitching et al 2005;Starr et al 2014), citizen involvement and environmental engagement can be fostered for short-and long-term projects (cf. Weaver 2013).…”

Section: Discussionmentioning

confidence: 99%

DIY meteorology: Use of citizen science to monitor snow dynamics in a data-sparse city

Appels

Bradford

Chun

et al. 2017

FACETS

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Cities are under pressure to operate their services effectively and project costs of operations across various timeframes. In high-latitude and high-altitude urban centers, snow management is one of the larger unknowns and has both operational and budgetary limitations. Snowfall and snow depth observations within urban environments are important to plan snow clearing and prepare for the effects of spring runoff on cities' drainage systems. In-house research functions are expensive, but one way to overcome that expense and still produce effective data is through citizen science. In this paper, we examine the potential to use citizen science for snowfall data collection in urban environments. A group of volunteers measured daily snowfall and snow depth at an urban site in Saskatoon (Canada) during two winters. Reliability was assessed with a statistical consistency analysis and a comparison with other data sets collected around Saskatoon. We found that citizen-sciencederived data were more reliable and relevant for many urban management stakeholders. Feedback from the participants demonstrated reflexivity about social learning and a renewed sense of community built around generating reliable and useful data. We conclude that citizen science holds great potential to improve data provision for effective and sustainable city planning and greater social learning benefits overall.

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Section: Discussionmentioning

confidence: 99%

DIY meteorology: Use of citizen science to monitor snow dynamics in a data-sparse city

Appels

Bradford

Chun

et al. 2017

FACETS

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“…It has previously been observed that crowdsourcing can be improved by various means, including self-censoring of submissions when a user is uncertain of a response (Shah and Zhou, 2015), using videos rather than only text- or image-based instruction (Starr et al , 2014), having mini-breaks especially for complicated tasks (Rzeszotarski et al , 2013), presenting context-sensitive help (Andersen et al , 2012), and financial punishment for disagreement with other users (Shaw et al , 2011). Most research in crowdsourcing accuracy has been on paid workers, for example recruited through Amazon Turk.…”

Section: Discussionmentioning

confidence: 99%

Crowdsourcing for translational research: analysis of biomarker expression using cancer microarrays

et al. 2016

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Background:Academic pathology suffers from an acute and growing lack of workforce resource. This especially impacts on translational elements of clinical trials, which can require detailed analysis of thousands of tissue samples. We tested whether crowdsourcing – enlisting help from the public – is a sufficiently accurate method to score such samples.Methods:We developed a novel online interface to train and test lay participants on cancer detection and immunohistochemistry scoring in tissue microarrays. Lay participants initially performed cancer detection on lung cancer images stained for CD8, and we measured how extending a basic tutorial by annotated example images and feedback-based training affected cancer detection accuracy. We then applied this tutorial to additional cancer types and immunohistochemistry markers – bladder/ki67, lung/EGFR, and oesophageal/CD8 – to establish accuracy compared with experts. Using this optimised tutorial, we then tested lay participants' accuracy on immunohistochemistry scoring of lung/EGFR and bladder/p53 samples.Results:We observed that for cancer detection, annotated example images and feedback-based training both improved accuracy compared with a basic tutorial only. Using this optimised tutorial, we demonstrate highly accurate (>0.90 area under curve) detection of cancer in samples stained with nuclear, cytoplasmic and membrane cell markers. We also observed high Spearman correlations between lay participants and experts for immunohistochemistry scoring (0.91 (0.78, 0.96) and 0.97 (0.91, 0.99) for lung/EGFR and bladder/p53 samples, respectively).Conclusions:These results establish crowdsourcing as a promising method to screen large data sets for biomarkers in cancer pathology research across a range of cancers and immunohistochemical stains.

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“…On the other hand, it has been shown that the effectiveness of citizen monitoring declines rapidly when the taxonomical difficulty of a monitored group increases (Starr et al. ).…”

Section: Discussionmentioning

confidence: 99%

“…; Starr et al. ). Such an approach provides an opportunity to collect large amounts of data from large areas and also allows the dispersal of organisms to be tracked.…”

Section: Introductionmentioning

confidence: 97%

Citizen monitoring of invasive species: wing morphometry as a tool for detection of alien Tetropium species

Goczał

Rossa

Sweeney

et al. 2016

J Applied Entomology

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The increasing threat of alien wood‐boring insect has resulted in the initiation of large‐scale monitoring programmes. These programmes are most often based on pheromone‐bailed traps, which allow the early detection and monitoring of invasive species. This approach is expensive because it entails the processing and accurate identification of large numbers of specimens. One of the most often suggested solutions to this problem is citizen participation in the monitoring of invasive species. Such an approach has the potential for reducing costs as well as providing data from a larger number of sites. However, citizens vary in taxonomic expertise and experience which can result in identification errors. This may be particularly important in the case of wood borers which include many morphologically similar species. In this study, we develop and discuss a semi‐automated method of identifying four morphologically similar and invasive Tetropium spp. wood borers as a potential tool for citizen‐based monitoring programmes. Identification is based on wing measurements and requires neither specialist knowledge nor expensive equipment. The method correctly identified the species of Tetropium with an error ranging from 1.3% for T. fuscum to 7.5% for T. cinnamopterum. We found that experience level of the individual user was not essential for correct identification; on average, inexperienced volunteers correctly identified the Tetropium species in 93% of cases. Further development of this method may be a significant step to overcoming the taxonomical impediment to citizen monitoring of taxonomically challenging groups of insects.

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Lights, Camera…Citizen Science: Assessing the Effectiveness of Smartphone-Based Video Training in Invasive Plant Identification

Cited by 50 publications

References 12 publications

DIY meteorology: Use of citizen science to monitor snow dynamics in a data-sparse city

DIY meteorology: Use of citizen science to monitor snow dynamics in a data-sparse city

Crowdsourcing for translational research: analysis of biomarker expression using cancer microarrays

Citizen monitoring of invasive species: wing morphometry as a tool for detection of alien Tetropium species

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