Gamification in citizen science systems combines play elements with scientific tasks. We posit that gamified elements are connected through “framings,” layers of meaning overlaid onto core tasks to shape an overall experience. Drawing upon self-determination theory, we propose a research model to investigate how users’ perceptions of framings contribute to motivational needs and contribution behavior. In a full study, we plan to conduct an online survey to validate our research model and elaborate upon the promise of gamification in information systems.

Source: Tang, Jian and Prestopnik, N., 2017. Effects of Framing on User Contribution: Story, Gameplay and Science. In America’s Conference on Information Systems 2017 Conference Proceedings

The benefit of engaging volunteers in marine citizen science projects goes beyond generation of data and has intrinsic value with regards to community capacity-building and education. Yet, despite the documented benefits of citizen science, there can be barriers to the process of developing strategic citizen science projects and translating data into valued results with natural resource management applications. This paper presents four case-studies from fifteen years of Reef Check Australia (RCA) marine citizen science research and education projects. These case studies convey approaches and lessons-learned from the process of designing, implementing and sharing citizen science programs with the goal to create valuable social and environmental outcomes:

  1. Demonstrating citizen science data quality through a precision study on data and analysis of 15 years of standardized Reef Check (RC) reef health data in Queensland, Australia.
  2. Identifying and responding to data gaps through volunteer monitoring of sub-tropical rocky reefs in South East Queensland, Australia.
  3. Adapting citizen science protocols to enhance capacity building, partnerships and strategic natural resource management applications through reef habitat mapping.
  4. Tailoring new pathways for sharing citizen science findings and engaging volunteers with the community via a Reef Check Australia Ambassadors community outreach program.

These case studies offer insights into considerations for developing targeted and flexible citizen science projects, showcasing the work of volunteers and project stakeholders, and collaborating with partners for applications beneficial to research, management and education.
doi: 10.3389/fmars.2017.00146

Source: Schläppy, M-L., Loder, J., Salmond, J., Lea, A., Dean, A.J., Roelfsema, C.M., 2017. Making Waves: Marine Citizen Science for Impact. Frontiers in Marine Science, 4:146. doi: 10.3389/fmars.2017.00146

This article examines certain guiding tenets of science journalism in the era of big data by focusing on its engagement with citizen science. Having placed citizen science in historical context, it highlights early interventions intended to help establish the basis for an alternative epistemological ethos recognising the scientist as citizen and the citizen as scientist. Next, the article assesses further implications for science journalism by examining the challenges posed by big data in the realm of citizen science. Pertinent issues include potential risks associated with data quality, access dynamics, the difficulty investigating algorithms, and concerns about certain constraints impacting on transparency and accountability.

Source: Allan, S., Redden, J., 2017. Making citizen science newsworthy in the era of big data. Journal of Science Communication 16(02)(2017)C05.

As part of a national research program studying the sources, distribution, and effects of litter entering the ocean, we established a national citizen science program engaging nearly 7000 primary and secondary students, teachers and corporate participants in collecting marine debris data around Australia’s coastline. Citizen scientists undertook a one-day training program, which addressed data collection skills and academic topics in the national science curriculum. A subset of teachers and corporate sponsor staff participated in an intensive multi-day training program with researchers before venturing into the field.

Data collected by citizen scientists were compared with data collected by researchers at nearby locations. We found the citizen science data were of equivalent quality to those collected by researchers, but there were differences among students. Primary school students detected more debris than did older secondary students. Students detected small items (<1 cm^2), and were as accurate as researchers in identifying debris type and size categories. However, sampling approach was important — students detected more debris during quadrat searches than during strip transects. Comparing researcher effort to volunteer-collected data, citizen scientists were often more efficient (per m^2) than researchers at collecting marine debris, but the results varied among methods. Researchers made more surveys within a given day (0.8 surveys/person-day). However, participants of one day programs working with secondary students or adults were nearly as efficient (0.6 surveys/person-day). This study shows that engaging with citizen scientists can broaden the coverage and increase the sampling power of coastal litter and other ecological survey assessments without compromising the data. Source: Van der Velde, T., Milton, D.A., Lawson, T.J., Wilcox, C., Lansdell, M., Davis, G., Perkins, G., Hardesty, B.D., 2017. Comparison of marine debris data collected by researchers and citizen scientists: Is citizen science data worth the effort? Biological Conservation 208: 127–138. DOI: https://doi.org/10.1016/j.biocon.2016.05.025

Phone-wielding and bare-armed, I follow Scott Edmunds and Mendel Wong to a small park in the Mid-Levels area of Hong Kong Island, where a dengue outbreak occurred last year. We hit the jackpot within five minutes – a swarm of mosquitoes around a tree. With his phone, Wong snaps a picture of one that lands on his arm, as well as the breeding site – a pile of discarded rubbish in the alley nearby. From the picture, we can clearly see the white lines on its legs, the distinctive characteristic of both the tiger mosquito (Aedes albopictus) and yellow fever mosquito (Aedes aegypti). “You don’t necessarily have to let it feed on you. You just need a clear picture of the front of its head,” says Wong. He uploads the picture to Mosquito Alert, an app which taps into the power of citizen science by allowing people to report sightings of mosquitoes and their breeding sites.

Source: Cheung, R., 2017. Hong Kong citizen scientists localise mosquito tracking app to let people report sightings of the disease carriers. South China Morning Post, 30 May.

As citizen science methodologies mature and number of participants increases, it is becoming more possible to understand the role and necessity of experts in relation to data quality. This article is a great example of how expertise can be assessed and utilized. — LFF —


  1. Citizen science data are increasingly making valuable contributions to ecological studies. However, many citizen science surveys are also designed to encourage wide participation and therefore the participants have a range of natural history expertise, leading to variation and potentially bias in the data.
  2. We assessed a recently proposed measure of observer expertise, calculated based on the average numbers of species recorded by observers. We investigated if this observer expertise score is associated with how often an observer records any individual species. Species reporting rates increased monotonically with the observer’s expertise score for 197 of 200 species, suggesting that this expertise score describes inter-observer variation in the detectability of individual species.
  3. Expertise scores were incorporated into single-species occupancy models as a covariate, to explain inter-observer variation in detectability. Including expertise as a detectability covariate led to improved model fit and improved predictive performance on validation data. The expertise score had a large effect on the estimated detectability, comparable in magnitude to the effect of the duration of the observation period.
  4. Expertise scores were also included into single-species occupancy models that estimated seasonal patterns in species occupancy and seasonal expertise effects. The addition of a seasonal effect of expertise led to improved model fit and increased predictive performance on validation data. The seasonal expertise variables accounted for bias that may be introduced by seasonal differences in the effect of expertise, caused by changes in the environment or species behaviour.
  5. Measures of observer expertise included in models as a covariate can account for heterogeneity and bias introduced by variable expertise, although in this example the differences in estimated occupancy were small. This method of incorporating observer expertise can be used in any regression model of species occurrence, occupancy, abundance, or density to produce more reliable ecological inference and may be most important where citizen science schemes encourage wide participation. Overall, the results highlight the value of recording observer identity and other detectability covariates, to control for sources of bias associated with the observation process.

Figure 3 from article, Johnston et al., 2017

Source: Johnston, A., Fink, D., Hochachka, W.M., Kelling, S., 2017. Estimates of observer expertise improve species distributions from citizen science data. Methods in Ecology and Evolution. DOI: 10.1111/2041-210X.12838

Citizen science opens new pathways that can complement traditional scientific practice. Intuition and reasoning often make humans more effective than computer algorithms in various realms of problem solving. In particular, a simple visual comparison of spatial patterns is a task where humans are often considered to be more reliable than computer algorithms. However, in practice, science still largely depends on computer based solutions, which inevitably gives benefits such as speed and the possibility to automatize processes. However, the human vision can be harnessed to evaluate the reliability of algorithms which are tailored to quantify similarity in spatial patterns. We established a citizen science project to employ the human perception to rate similarity and dissimilarity between simulated spatial patterns of several scenarios of a hydrological catchment model. In total, the turnout counts more than 2500 volunteers that provided over 43000 classifications of 1095 individual subjects. We investigate the capability of a set of advanced statistical performance metrics to mimic the human perception to distinguish between similarity and dissimilarity. Results suggest that more complex metrics are not necessarily better at emulating the human perception, but clearly provide auxiliary information that is valuable for model diagnostics. The metrics clearly differ in their ability to unambiguously distinguish between similar and dissimilar patterns which is regarded a key feature of a reliable metric. The obtained dataset can provide an insightful benchmark to the community to test novel spatial metrics.

Source: Koch, J., Stisen, S., 2017. Citizen science: A new perspective to advance spatial pattern evaluation in hydrology. PLoS ONE 12(5): e0178165. https://doi.org/10.1371/journal.pone.0178165

Editor’s Choice: This article will get your mental wheels turning about identity, power, and the nature of work at disciplinary boundaries. The authors carefully scrutinize words to unpack divergent connotations, examining how positive, neutral, and negative associations influence us. This is a must-read for all who aspire to make “citizen science” a just, inclusive, and equitable endeavor. — AWA —

Abstract: Much can be at stake depending on the choice of words used to describe citizen science, because terminology impacts how knowledge is developed. Citizen science is a quickly evolving field that is mobilizing people’s involvement in information development, social action and justice, and large-scale information gathering. Currently, a wide variety of terms and expressions are being used to refer to the concept of ‘citizen science’ and its practitioners. Here, we explore these terms to help provide guidance for the future growth of this field. We do this by reviewing the theoretical, historical, geopolitical, and disciplinary context of citizen science terminology; discussing what citizen science is and reviewing related terms; and providing a collection of potential terms and definitions for ‘citizen science’ and people participating in citizen science projects. This collection of terms was generated primarily from the broad knowledge base and on-the-ground experience of the authors, by recognizing the potential issues associated with various terms. While our examples may not be systematic or exhaustive, they are intended to be suggestive and invitational of future consideration. In our collective experience with citizen science projects, no single term is appropriate for all contexts. In a given citizen science project, we suggest that terms should be chosen carefully and their usage explained; direct communication with participants about how terminology affects them and what they would prefer to be called also should occur. We further recommend that a more systematic study of terminology trends in citizen science be conducted.

Source: Eitzel, M.V. et al., 2017. Citizen Science Terminology Matters: Exploring Key Terms. Citizen Science: Theory and Practice. 2(1), p.1. DOI: http://doi.org/10.5334/cstp.96

Scientists expect Africa to be hardest hit by climate change: its dependence on agriculture, hot temperatures, and poor infrastructure mean its citizens are likely to feel the pressure of a changing climate more than most others. But there are big gaps in our knowledge of how ecosystems and microclimates work.
“We don’t have an operating manual for the planet and we need one,” says Guy Midgley, a professor at Stellenbosch University who was part of the United Nations’ climate change panel. “It’s frustrating to see incomplete knowledge being implemented as policy.

“It’s why we need more science.”

That’s where rePhotoSA comes in: this ambitious citizen science project wants to recreate southern African historic landscapes through photography, and compare new and old vistas.

Source: Wild, S., 2017. Climate change’s impact on Southern Africa is captured in the photos of a citizen science project — Quartz. 3 June. Available at https://qz.com/996437/the-photos-from-a-citizen-science-project-capture-southern-africas-climate-change-future/ [Last accessed 3 July 2017].

Editor’s Choice: This is an excellent example of real “co-created” science between a non-salaried scientist (aka citizen scientist) and salaried scientists. –LFF–

Amateur naturalists from the UK have a distinguished pedigree, from Henry Walter Bates and Marianne North, to Alfred Russel Wallace and Mary Anning. But arguably, the rise of post-war academia in the fifties displaced them from mainstream scientific discourse and discovery. Recently, there has been a resurgence of the ‘citizen scientist’, like me, in the UK and elsewhere – although the term may refer to more than one kind of beast.

To me, the ‘citizen scientist’ label feels a little patronising – conveying an image of people co-opted en masse for top-down, scientist-led, large-scale biological surveys. That said, scientist-led surveys can offer valid contributions to conservation and documentation of the effects of climate change (among other objectives). They also engage the public (not least children) in science, although volunteers usually have an interest in natural history and science already. For me though, the real excitement comes in following a bottom-up path: making my own discoveries and approaching scientists for assistance with my projects.

Source: Grieves, Chris, 2017. Bottom-up Citizen Science and Biodiversity Statistics. 6 June. Available at methods.blog, https://methodsblog.wordpress.com/2017/06/06/citizen-science-biodiversity-statistics/