Context Of Citizen Science Research Articles

Living the DReaM: The interrelations between statistical, scientific and nature of science uncertainty articulations through citizen science.

Responsible citizenship and sound decision-making in today's information age necessitate an appreciation of the role of uncertainty in the process of generating data-based scientific knowledge. The latter calls for coordinating between different types of uncertainties, related to three types of relevant reasoning: statistical, scientific, and nature of science uncertainties. This article examines separately the uncertainties that young students articulate as they engage in activities designed to concurrently foster all three types of reasoning, and also explores how these different types can interrelate. The context of Citizen Science is particularly suited for this goal, providing a unique pedagogical opportunity for learning scientific content by engaging learners in authentic scientific practices, including data analysis. Based on literature from the three fields of statistics, science and nature of science education, we offer an integrative framework, Deterministic Relativistic and Middle ground (DReaM), which consists of nine sub-categories of uncertainty articulations. We utilize it to analyze an instrumental case study of a pair of middle school students' (ages 13 and 14) participation in a pilot study of an interdisciplinary extended learning sequence, as part of the Radon Citizen Science Project. The results of an interpretative microgenetic analysis identified all nine DReaM uncertainty articulations sub-categories. These are illustrated in the Findings section with key scenes from the pair's participation. The discussion depicts how these sub-categories manifested in this particular case study and suggests interrelations between them in a more extended depiction of the DReaM framework. We conclude with the pedagogical implications of the extended framework.

Cyber-Cosmos: A new citizen science concept in a dark sky destination

Astrotourism and related citizen science activities are becoming a major trend of a sustainable, high-quality tourism segment, core elements to the protection of Dark skies in many countries. In the Summer of 2020, in the middle of COVID pandemics, we started an initiative to train young students – Cyber-Cosmos – using an Unistellar eVscope, a smart, compact and user-friendly digital telescope that offers unprecedented opportunities for deep-sky observation and citizen science campaigns. Sponsored by the Ciência Viva Summer program, this was probably the first continuous application of this equipment in a pedagogical and citizen-science context, and in a pandemic context. Pampilhosa da Serra, home to a certified Dark Sky destination (Aldeias do Xisto) in central Portugal, was the chosen location for this project, where we expect astrotourism and citizen science to flourish and contribute to space sciences education.

Citizens’ views on home experiments in the context of a chemistry citizen science project

Citizen science has gained importance in recent years and revealed great potential, especially regarding science learning and environmental education. However, little is known about ways of supporting individual learning processes within citizen science. With this in mind, a home experiment set, the Nitrogen Box, was developed within a chemistry citizen science project on nitrogen pollution of water bodies. The aim of the box was primarily to deepen the subject matter and to sensitize the citizens to the topic. To gain deeper insights into the usability and added value of home experiments in a citizen science context, semi-structured interviews were conducted with ten citizens. Analysis of these interviews revealed that the nitrogen box contributed to a consolidation and deepening of knowledge of the nitrogen problem in Northwest Germany. Home experiment sets like Nitrogen Box can motivate and enable citizens to engage more deeply with the scientific topic in the future, to reflect on it and discuss it. We discuss how heterogeneity of the target group presents challenges for designing citizen science projects and provide recommendations for the future projects.

A handmade trap for malaria mosquito surveillance by citizens in Rwanda.

For effective sampling of mosquitoes in malaria surveillance programmes, it is essential to include attractive cues in traps. With the aim of implementing a citizen science project on malaria vectors in rural Rwanda, a handmade plastic bottle trap was designed and tested in the field to determine its effectiveness in capturing adult Anopheles gambiae sensu lato, the main malaria vector, and other mosquito species. Carbon dioxide (CO2) and light were used as attractive cues. CO2 was produced by inoculating sugar with yeast and water. Light was emitted from a torch by light-emitting diodes (LEDs). Under field conditions in rural Rwanda, three handmade trap designs were compared to Centers for Disease Control and Prevention miniature light traps (CDC-LT) in houses. The trap baited with yeast produced CO2 and light caught the highest number of mosquitoes compared to the traps baited with light alone or CO2 alone. The number of An. gambiae s.l. in the handmade trap with light and CO2 was approximately 9–10% of the number caught with a CDC light trap. This suggests that about 10 volunteers with a handmade trap could capture a similar-sized sample of An. gambiae as one CDC-LT would collect. Based on these findings, the handmade plastic bottle trap baited with sugar fermenting yeast and light represents an option for inclusion in mosquito surveillance activities in a citizen science context.

Ethics framework for citizen science and public and patient participation in research

BackgroundCitizen science and models for public participation in health research share normative ideals of participation, inclusion, and public and patient engagement. Academic researchers collaborate in research with members of the public involved in an issue, maximizing all involved assets, competencies, and knowledge. In citizen science new ethical issues arise, such as who decides, who participates, who is excluded, what it means to share power equally, or whose knowledge counts. This article aims to present an ethics framework that offers a lens of understanding and heuristic guidelines to deal with ethical issues in citizen science.MethodsWe conducted seven case studies between 2015 and 2021 to attune and validate the ethics framework for the context of citizen science. The cases related to studies with older adults, people with a psychiatric vulnerability, people dependent on community care, people who are unemployed or living in poverty or both, and young adults with respiratory disease.ResultsEthics in citizen science reaches beyond the ethical issues in traditional biomedical and health research. It entails more than following procedures about informed consent and privacy and submitting a proposal to a Medical Research Ethics Committee. Ethics in citizen science relates to everyday ethical issues during the study, including relational and moral complexities concerning collaboration, sharing power, and democratic decision-making. Dealing with these issues requires ethics work of researchers. This entails seeing ethically salient issues and reflecting on everyday ethical issues. Ethics work consists of seven features: framing work, role work, emotion work, identity work, reason work, relationship work, and performance work. All are relevant for researchers in citizen science.ConclusionsEthical issues in citizen science often relate to power differentials, partnership, and collaboration between academics and non-academics. The ethics framework prepares researchers for the work needed in citizen science to act responsibly and offers a heuristic guide to reflect on ethics. Reflection on ethics is a pathway towards ethical citizen science, especially if researchers collaboratively reflect in partnership with non-academics who are subject to the moral issue.

The Citizen Observatory: Enabling Next Generation Citizen Science

Abstract Background: Citizen science offers an attractive paradigm for addressing some of the complex problems facing society. However, translating the paradigm’s potential into meaningful action and sustainable impact remains a formidable challenge. Historically, the citizen science landscape was fractured into silos of activities; nonetheless, it has demonstrably delivered credible results. An innovative concept of the Citizen Observatory offers a tractable means of mitigating many of the recurring issues that historically afflicted citizen science initiatives, thus empowering a new generation of citizen scientists. Citizen Observatories may be regarded as open, standardised software platforms for community-based monitoring of any phenomenon of interest. Objectives: This paper seeks to validate a Citizen Observatory in a traditional citizen science context, that of butterfly recording. Methods/Approach: A case study was undertaken in a UNESCO-designated Biosphere Reserve. Results: A community of citizen scientists successfully recorded various observations concerning butterflies, their feeding behaviours, and their habitat. The resultant dataset was made available to the local government environmental agency. Conclusions: The Citizen Observatory model offers a realistic basis for enabling more sustainable participatory science activities. Such developments have implications for non-government organisations, businesses, and local governments.

Coordinator Perceptions When Assessing the Impact of Citizen Science towards Sustainable Development Goals

Tracking progress towards the United Nations’ Sustainable Development Goals (SDGs) requires high-quality, timely, and accessible data, often in areas where data are rarely available. Problems exist due to socioeconomic variations between countries and the qualitative nature of certain indicators in their definition. Citizen science has the potential to contribute to several SDGs. However, whilst citizen science’s potential to contribute towards SDGs is well documented, limitations exist when measuring the impact that citizen science has made toward SDG progress. To better understand the issues and prospective solutions surrounding impact assessment towards SDG progress, this work presents the outcomes of semi-structured interviews with citizen science project coordinators. They reveal the complex nature of impact assessment within a citizen science context. Coordinators demonstrate greater confidence when the project is easier to relate to the SDGs, and the project methodology can objectively measure indicators. Issues exist, however, when considering SDGs with a broader, global context, those more difficult to link to project goals and when the project’s impact on them happens at timescales beyond the funding period. If the full potential of citizen-science contributions to the SDGs is to be realised, approaches are needed to fully consider practitioners’ needs and motivations.

Citclops: Anext-generation sensor system for the monitoring of natural waters and a citizens' observatory for the assessment of ecosystems' status.

The European-Commission-funded project 'Citclops' (Citizens' observatory for coast and ocean optical monitoring) developed methods, tools and sensors, which can be used by citizens to monitor natural waters, with a strong focus on long-term data series related to environmental sciences. The new sensors, based on optical technologies, respond to a number of scientific, technical and societal objectives, ranging from more precise monitoring of key environmental descriptors of the aquatic environment (water colour, transparency and fluorescence) to an improved management of data collected with citizen participation. The sensors were tested, calibrated, integrated on several platforms, scientifically validated and demonstrated in the field. The new methods and tools were tested in a citizen-science context. The general conclusion is that citizens are valuable contributors in quality and quantity to the objective of collecting, integrating and analysing fragmented and diverse environmental data. An integration of these data into data-analysis tools has a large potential to support authoritative monitoring and decision-making. In this paper, the project's objectives, results, technical achievements and lessons learned are presented.

Galaxy-Bricks a tool for data literacy and scientific approach education in the context of citizen science

Galaxy-Bricks a tool for data literacy and scientific approach education in the context of citizen science

Expecting the Unexpected: Effects of Data Collection Design Choices on the Quality of Crowdsourced User-Generated Content

As crowdsourced user-generated content becomes an important source of data for organizations, a pressing question is how to ensure that data contributed by ordinary people outside of traditional organizational boundaries is of suitable quality to be useful for both known and unanticipated purposes. This research examines the impact of different information quality management strategies, and corresponding data collection design choices, on key dimensions of information quality in crowdsourced user-generated content. We conceptualize a contributor-centric information quality management approach focusing on instance-based data collection. We contrast it with the traditional consumer-centric fitness-for-use conceptualization of information quality that emphasizes class-based data collection. We present laboratory and field experiments conducted in a citizen science domain that demonstrate trade-offs between the quality dimensions of accuracy, completeness (including discoveries), and precision between the two information management approaches and their corresponding data collection designs. Specifically, we show that instance-based data collection results in higher accuracy, dataset completeness, and number of discoveries, but this comes at the expense of lower precision. We further validate the practical value of the instance-based approach by conducting an applicability check with potential data consumers (scientists, in our context of citizen science). In a follow-up study, we show, using human experts and supervised machine learning techniques, that substantial precision gains on instance-based data can be achieved with post-processing. We conclude by discussing the benefits and limitations of different information quality and data collection design choices for information quality in crowdsourced user-generated content.

Social Information as a Means to Enhance Engagement in Citizen Science‐Based Telerehabilitation

Advancements in computer‐mediated exercise put forward the feasibility of telerehabilitation, but it remains a challenge to retain patients' engagement in exercises. Building on our previous study demonstrating enhanced engagement in citizen science through social information about others' contributions, we propose a novel framework for effective telerehabilitation that integrates citizen science and social information into physical exercise. We hypothesized that social information about others' contributions would augment engagement in physical activity by encouraging people to invest more effort toward discovery of novel information in a citizen science context. We recruited healthy participants to monitor the environment of a polluted canal by tagging images using a haptic device toward gathering environmental information. Along with the images, we displayed the locations of the tags created by the previous participants. We found that participants increased both the amount and duration of physical activity when presented with a larger number of the previous tags. Further, they increased the diversity of tagged objects by avoiding the locations tagged by the previous participants, thereby generating richer information about the environment. Our results suggest that social information is a viable means to augment engagement in rehabilitation exercise by incentivizing the contribution to scientific activities.

Marine litter detection and correlation with the seabird nest content

A 3 year monitoring programme, realized in a citizen science context, from 2014 until 2016, allowed us to gather information on the prevalent quantities and qualities of anthropogenic waste in five Mediterranean coastal areas within the Pelagos Sanctuary, three of them located in Liguria, near La Spezia Gulf, and the other two in Tuscany. Here, we present results concerning the Polymeric Articles’ abundances registered during the survey. Moreover, we show the results of the first study devoted to describe and quantify the anthropogenic content of the nest of a pair of Northern Gannets (Morus bassanus), a pelagic bird that, starting from some years, has been reproducing regularly in La Spezia Gulf. This breeding is atypical for this species, as is associated with artificial structures such as piers, floating docks, or boats; the material used in the construction of the nest reflects the “anthropogenic” link with the chosen location and objects of polymeric origin in particular abound. We detect the existence of a correlation between the most abundant types of Anthropogenic Marine Debris found in the Northern Gannet’ nest (fragments of polypropylene nets) and one of the productive activities of the zones.

Citizen observations contributing to flood modelling: opportunities and challenges

Abstract. 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.

Simplified and still meaningful: assessing butterfly habitat quality in grasslands with data collected by pupils

Public participation in scientific research, now commonly referred to as citizen science, is increasingly promoted as a possibility to overcome the large-scale data limitations related to biodiversity and conservation research. Furthermore, public data-collection projects can stimulate public engagement and provide transformative learning situations. However, biodiversity monitoring depends on sound data collection and warranted data quality. Therefore, we investigated if and how trained and supervised pupils are able to systematically collect data about the occurrence of diurnal butterflies, and how this data could contribute to a permanent butterfly monitoring system. We developed a specific assessment scheme suitable for laypeople and applied it at 35 sampling sites in Tyrol, Austria. Data quality and its explanatory power to predict butterfly habitat quality was investigated comparing data collected by pupils with independent assessments of professional butterfly experts. Despite substantial identification uncertainties for some species or species groups, the data collected by pupils was successfully used to predict the general habitat quality for butterflies using a linear regression model (r² = 0.73, p <0.001). Applying the proposed method in a citizen science context with laypeople could support both the long term monitoring of butterfly habitat quality, as well as the efficient selection of sites for professional in-depth assessments.

Spatial memory training in a citizen science context

Memory deficit is one of the primary effects of intellectual disability, and has a great impact on daily life. Here, we propose a novel spatial memory training system based on a citizen science virtual environment, in which users navigate an aquatic robot in a polluted canal and identify specific objects from images acquired by the robot. A portable low-cost electroencephalography device is utilized to enhance the degree of interactivity and enable real-time estimation of the affective state of the user. We involved a cohort of 60 healthy adult subjects to evaluate users' interest, memory performance, and affective variables as a function of navigation modality (active versus passive) and interface (a traditional computer mouse versus the headset). Despite offering a higher level of difficulty, the headset was preferred over a traditional mouse control by the users, whose spatial memory performance did not vary with the navigation modality or the interface. Active navigation was found to lead to a higher level of engagement, as measured by the headset. These findings suggest the possibility of a new, effective, and entertaining form of intellectual rehabilitation with potential impact on fetal alcohol syndrome.

Data Analytics in Citizen Cyberscience: Evaluating Participant Learning and Engagement with Analytics

Citizen Cyberscience (CCS) projects are online projects that engage participants with no necessary prior scientific experience in online tasks of very varied types and that contribute to the scientific research in different domains. Many research studies confirm the usefulness of CCS projects to researchers while less has been done to explore their added-value for the participants. Specifically, we are interested to know to what extent CCS projects help participants learn while participating through typically small-sized and very specific tasks.We propose in this work to include another source of quantitative data to the research toolbox usually used to evaluate learning in informal learning contexts as the context of citizen science. This data source is learning analytics that makes use of the already very ubiquitous web analytics and that is heavily used in varied online learning environments. Based on our experience with two CCS pilot projects, we created a framework to help CCS project designers properly implement learning analytics in their project in order to make the full use of these analytics and integrate them with other sources of quantitative data related to the user experience. We apply the proposed framework to explore the interaction between learning and engagement in two pilot CCS projects of different types: volunteer thinking and gaming. We conclude with a number of recommendations to avoid pitfalls and proposals for best practice based on our experience.

Citizen science regarding invasive lionfish in Dutch Caribbean MPAs: Drivers and barriers to participation

Understanding the drivers and barriers to participation in citizen science initiatives for conservation is important if long-term involvement from volunteers is expected. This study investigates the motivations of individuals from five marine protected areas (MPAs) in the Dutch Caribbean to (not) participate in different initiatives around lionfish. Following an interpretive approach, semi-structured interviews with seventy-eight informants were conducted and analyzed using thematic network analysis. Approximately 60% (n = 48) of informants indicated that they had participated in citizen science initiatives at the outset of the invasion. From this group, almost half said that they still participated in some type of data collection, but only a few did so within a citizen science context. Many informants were initially motivated to participate in lionfish detection and response initiatives due to concern for the environment. Personal meanings attached to both the data collection experiences and to the data influenced informants’ motivations to sustain or cease data collection and/or sharing. In time, the view of lionfish as a threat changed for many informants as this species’ recreational and/or commercial value increased. Enabling and constraining factors for data collection and sharing were identified at the personal, interpersonal, organizational and technical levels. Our findings have implications for the design of future citizen science initiatives focused on invasive species.

Initiating and continuing participation in citizen science for natural history.

BackgroundNatural history has a long tradition in the UK, dating back to before Charles Darwin. Developing from a principally amateur pursuit, natural history continues to attract both amateur and professional involvement. Within the context of citizen science and public engagement, we examine the motivations behind citizen participation in the national survey activities of the Open Air Laboratories (OPAL) programme, looking at: people’s experiences of the surveys as ‘project-based leisure’; their motivations for taking part and barriers to continued participation; where they feature on our continuum of engagement; and whether participation in an OPAL survey facilitated their movement between categories along this continuum. The paper focuses on a less-expected but very significant outcome regarding the participation of already-engaged amateur naturalists in citizen science.ResultsOur main findings relate to: first, how committed amateur naturalists (already-engaged) have also enjoyed contributing to OPAL and the need to respect and work with their interest to encourage broader and deeper involvement; and second, how new (previously-unengaged) and relatively new participants (casually-engaged) have gained confidence, renewed their interests, refocussed their activities and/or gained validation from participation in OPAL. Overall, we argue that engagement with and enthusiasm for the scientific process is a motivation shared by citizens who, prior to participating in the OPAL surveys, were previously-unengaged, casually-engaged or already-engaged in natural history activities.ConclusionsCitizen science has largely been written about by professional scientists for professional scientists interested in developing a project of their own. This study offers a qualitative example of how citizen science can be meaningful to participants beyond what might appear to be a public engagement data collection exercise.

Embedded Assessment as an Essential Method for Understanding Public Engagement in Citizen Science

Citizen science is an important way of engaging a broad range of audiences in science inquiry by participating in research that asks novel questions and unearths new knowledge and new questioning. Though citizen science projects are quite diverse in their scientific pursuits, all projects share the common element of involving volunteers directly in some aspect of science inquiry. Thus, it is essential for citizen science projects to determine their participants’ capacity to learn and successfully perform science inquiry skills, such as making scientific observations, collecting and analyzing data, and sharing findings. Such skill gains are essential to (a) ensure high quality data that can be used in meaningful scientific research, and (b) achieve broader goals such as developing a participant’s identity as a contributor to science. However, we do not yet fully understand how improvement in participants’ inquiry skills through citizen science advances our knowledge of public engagement with science. In this essay, we offer embedded assessment as an effective method to capture participant skill gains, and encourage citizen science leaders, evaluators, and researchers to develop authentic methods that address the complexities of measuring skill development within the context of citizen science.

The Validation of the Citizen Science Self-Efficacy Scale (CSSES)

Citizen science programs provide opportunities for students to help professional scientists while fostering science achievement and motivation. Instruments which measure the effects of this type of programs on student motivational beliefs are limited. The purpose of this study was to describe the process of examining the reliability and validity of The Citizen Science Self-Efficacy Scale (CSSES) designed to measure the effectiveness of citizen science programs on student self-efficacy for scientific observation skills. Fifteen (n =15) field experts and 248 (n = 248) eighth grade students participated in three studies. The results suggest that the psychometric properties of this scale are sufficient. Implications for the development and utility of self-efficacy scales in a variety of citizen science contexts are discussed. The aim of the present study is twofold: (a) to establish the psychometric properties of a scale developed to measure student self-efficacy beliefs for scientific observations in citizen science programs and (b) to describe the process in the validation of a self-efficacy scale to support researchers who want to create their own scales for similar citizen science programs. Three studies were conducted to develop the Citizen Science Scale (CSSES) and evaluate its psychometric properties. The purpose of the CSSES was to develop a measure suitable for analysis within a social cognitive career framework and informal natural science contexts. The findings in the present study found that the measure had an acceptable unitary factorial structure and high internal reliability of .89 for the CSSES. The purpose of the Citizen Science Self-Efficacy Scale (CSSES) is to assess individual’s beliefs about their capabilities for scientific observational skills. This scale is applicable to measuring individual’s self-efficacy in outdoor learning contexts (e.g., horseshoe crab citizen science context). Given that self-efficacy is a strong predictor of academic achievement and motivation, self-efficacy scales like the CSSES may provide a way for stakeholders involved in outdoor education to measure student gains and to substantiate program effectiveness. From a methods standpoint, the contribution of this work is to serve as a guide of how to develop a self-efficacy scale.