Geographic Citizen Science Design

Curated on Posted on by Stefaan Verhulst

Book edited by Artemis Skarlatidou and Muki Haklay: “Little did Isaac Newton, Charles Darwin and other ‘gentlemen scientists’ know, when they were making their scientific discoveries, that some centuries later they would inspire a new field of scientific practice and innovation, called citizen science. The current growth and availability of citizen science projects and relevant applications to support citizen involvement is massive; every citizen has an opportunity to become a scientist and contribute to a scientific discipline, without having any professional qualifications. With geographic interfaces being the common approach to support collection, analysis and dissemination of data contributed by participants, ‘geographic citizen science’ is being approached from different angles.

Geographic Citizen Science Design takes an anthropological and Human-Computer Interaction (HCI) stance to provide the theoretical and methodological foundations to support the design, development and evaluation of citizen science projects and their user-friendly applications. Through a careful selection of case studies in the urban and non-urban contexts of the Global North and South, the chapters provide insights into the design and interaction barriers, as well as on the lessons learned from the engagement of a diverse set of participants; for example, literate and non-literate people with a range of technical skills, and with different cultural backgrounds.

Looking at the field through the lenses of specific case studies, the book captures the current state of the art in research and development of geographic citizen science and provides critical insight to inform technological innovation and future research in this area….(More)”.

Mapping urban temperature using crowd-sensing data and machine learning

Curated on Posted on by Stefaan Verhulst

Paper by Marius Zumwald, Benedikt Knüsel, David N.Bresch and Reto Knutti: :”Understanding the patterns of urban temperature a high spatial and temporal resolution is of large importance for urban heat adaptation and mitigation. Machine learning offers promising tools for high-resolution modeling of urban heat, but it requires large amounts of data. Measurements from official weather stations are too sparse but could be complemented by crowd-sensed measurements from citizen weather stations (CWS). Here we present an approach to model urban temperature using the quantile regression forest algorithm and CWS, open government and remote sensing data. The analysis is based on data from 691 sensors in the city of Zurich (Switzerland) during a heat wave using data from for 25-30th June 2019. We trained the model using hourly data from for 25-29th June (n = 71,837) and evaluate the model using data from June 30th (n = 14,105). Based on the model, spatiotemporal temperature maps of 10 × 10 m resolution were produced. We demonstrate that our approach can accurately map urban heat at high spatial and temporal resolution without additional measurement infrastructure. We furthermore critically discuss and spatially map estimated prediction and extrapolation uncertainty. Our approach is able to inform highly localized urban policy and decision-making….(More)”.

Scaling up Citizen Science

Curated on Posted on by Stefaan Verhulst

Report for the European Commission: “The rapid pace of technology advancements, the open innovation paradigm, and the ubiquity of high-speed connectivity, greatly facilitate access to information to individuals, increasing their opportunities to achieve greater emancipation and empowerment. This provides new opportunities for widening participation in scientific research and policy, thus opening a myriad of avenues driving a paradigm shift across fields and disciplines, including the strengthening of Citizen Science. Nowadays, the application of Citizen Science principles spans across several scientific disciplines, covering different geographical scales. While the interdisciplinary approach taken so far has shown significant results and findings, the current situation depicts a wide range of projects that are heavily context-dependent and where the learning outcomes of pilots are very much situated within the specific areas in which these projects are implemented. There is little evidence on how to foster the spread and scalability in Citizen Science. Furthermore, the Citizen Science community currently lacks a general agreement on what these terms mean, entail and how these can be approached.

To address these issues, we developed a theoretically grounded framework to unbundle the meaning of scaling and spreading in Citizen Science. In this framework, we defined nine constructs that represent the enablers of these complex phenomena. We then validated, enriched, and instantiated this framework through four qualitative case studies of, diverse, successful examples of scaling and spreading in Citizen Science. The framework and the rich experiences allow formulating four theoretically and empirically grounded scaling scenarios. We propose the framework and the in-depth case studies as the main contribution from this report. We hope to stimulate future research to further refine our understanding of the important, complex and multifaceted phenomena of scaling and spreading in Citizen Science. The framework also proposes a structured mindset for practitioners that either want to ideate and start a new Citizen Science intervention that is scalable-by-design, or for those that are interested in assessing the scalability potential of an existing initiative….(More)”.

Mapping citizen science contributions to the UN sustainable development goals

Curated on Posted on by Stefaan Verhulst

Paper by Dilek Frais: “The UN Sustainable Development Goals (SDGs) are a vision for achieving a sustainable future. Reliable, timely, comprehensive, and consistent data are critical for measuring progress towards, and ultimately achieving, the SDGs. Data from citizen science represent one new source of data that could be used for SDG reporting and monitoring. However, information is still lacking regarding the current and potential contributions of citizen science to the SDG indicator framework. Through a systematic review of the metadata and work plans of the 244 SDG indicators, as well as the identification of past and ongoing citizen science initiatives that could directly or indirectly provide data for these indicators, this paper presents an overview of where citizen science is already contributing and could contribute data to the SDG indicator framework.

The results demonstrate that citizen science is “already contributing” to the monitoring of 5 SDG indicators, and that citizen science “could contribute” to 76 indicators, which, together, equates to around 33%. Our analysis also shows that the greatest inputs from citizen science to the SDG framework relate to SDG 15 Life on Land, SDG 11 Sustainable Cities and Communities, SDG 3 Good Health and Wellbeing, and SDG 6 Clean Water and Sanitation. Realizing the full potential of citizen science requires demonstrating its value in the global data ecosystem, building partnerships around citizen science data to accelerate SDG progress, and leveraging investments to enhance its use and impact….(More)”.

The people solving mysteries during lockdown

Curated on Posted on by Stefaan Verhulst

Frank Swain at the BBC: “For almost half a century, Benedictine monks in Herefordshire dutifully logged the readings of a rain gauge on the grounds of Belmont Abbey, recording the quantity of rain that had fallen each month without fail. That is, until 1948, when measurements were suspended while the abbot waited for someone to repair a bullet hole in the gauge funnel.

How the bullet hole came to be there is still a mystery, but it’s just one of the stories uncovered by a team of 16,000 volunteers who have been taking part in Rainfall Rescue, a project to digitise hand-written records of British weather. The documents, held by the Met Office, contain 3.5 million datapoints and stretch as far back as 1820.

Ed Hawkins, a climate scientist at the University of Reading, leads the project. “It launched at the end of March, we realised people would have a lot of spare time on their hands,” he explains. “It was completed in 16 days. I was expecting 16 weeks, not 16 days… the volunteers absolutely blitzed it.” He says the data will be used to improve future weather predictions and climate modelling.

With millions of people trapped at home during the pandemic, citizen science projects are seeing a boom in engagement. Rainfall Rescue uses a platform called Zooniverse, which hosts dozens of projects covering everything from artworks to zebra. While the projects generally have scientific aims, many allow people to also contribute some good to the world. 

Volunteers can scour satellite images for rural houses across Africa so they can be connected to the electricity grid, for example. Another – led by researchers at the University of Nottingham in the UK – is hunting for signs of modern slavery in the shape of brick kilns in South Asia (although the project has faced some criticism for being an over-simplified way of looking at modern slavery).

Others are trying to track the spread of invasive species in the ocean from underwater photographs, or identify earthquakes and tremors by speeding up the seismic signals so they become audible and can be classified by sharp-eared volunteers. “You could type in data on old documents, count penguins, go to the Serengeti and look at track camera images – it’s an incredible array,” says Hawkins. “Whatever you’re interested in there’s something for you.”…(More)”.

Data Sharing in the Context of Health-Related Citizen Science

Curated on Posted on by Stefaan Verhulst

Paper by Mary A. Majumder and Amy L. McGuire: “As citizen science expands, questions arise regarding the applicability of norms and policies created in the context of conventional science. This article focuses on data sharing in the conduct of health-related citizen science, asking whether citizen scientists have obligations to share data and publish findings on par with the obligations of professional scientists. We conclude that there are good reasons for supporting citizen scientists in sharing data and publishing findings, and we applaud recent efforts to facilitate data sharing. At the same time, we believe it is problematic to treat data sharing and publication as ethical requirements for citizen scientists, especially where there is the potential for burden and harm without compensating benefit…(More)”.

Ask a Scientist

Curated on Posted on by Stefaan Verhulst

NYU Press Release: “Unreliable tips on how to protect oneself from the novel coronavirus and fake news about the COVID-19 pandemic are spreading as quickly as the virus itself.

The Governance Lab (The GovLab) at the New York University Tandon School of Engineering has collaborated with the Federation of American Scientists (FAS) and the State of New Jersey Office of Innovation to launch a free, interactive tool aimed at cutting through the noise and presenting clear, scientist-led, and evidence-based information and advice to the public.

Available in English and Spanish, “Ask a Scientist,” allows users to find answers to a wide range of commonly asked questions about the virus, the severity of the outbreak, best methods of prevention, and steps to take in the event you fall ill. All posted content is obtained from the World Health Organization, the Centers for Disease Control and Prevention, and other rigorously verified sources.

screenshot of website that allows users to type in questions about COVID-19

“Ask a Scientist” features a free, interactive tool allowing users to submit questions to a team of FAS researchers and a crowdsourced network of vetted science experts. In English and Spanish, the site also includes top articles and the latest information, and answers to a wide range of commonly asked questions about the COVID-19 epidemic, the severity of the outbreak, best methods of prevention, and steps to take in the event you fall ill.

If users do not find an answer to their specific questions, they have the option of submitting them to a team of FAS researchers and a crowdsourced network of vetted science experts led by the National Science Policy Network. Users can expect an answer within an hour, although that timeframe is expected to shorten as the network increases in size. Every answer is reviewed to ensure accuracy and timeliness, then added to the knowledge base for the benefit of others….(More)”.

How scientists are crowdsourcing a coronavirus treatment

Curated on Posted on by Stefaan Verhulst

Article by Evan Nicole Brown: “… There’s currently no cure for COVID-19, but scientists are working on drugs that could help slow its spread. Fortunately, citizens can get involved in the process.

Foldit is an online video game that challenges players to fold various proteins into shapes where they are stable. Generally, folding proteins allows scientists (and citizens) to design new proteins from scratch, but in the case of coronavirus, Foldit players are trying to design the drugs to combat it. “Coronavirus has a ‘spike’ protein that it uses to recognize human cells,” says Brian Koepnick, a biochemist and researcher with the University of Washington’s Institute for Protein Design who has been using Foldit for protein research for six years. “Foldit players are designing new protein drugs that can bind to the COVID spike and block this recognition, [which could] potentially stop the virus from infecting more cells in an individual who has already been exposed to the virus.”

“In Foldit, you change the shape of a protein model to optimize your score. This score is actually a sophisticated calculation of the fold’s potential energy,” says Koepnick, adding that professional researchers use an identical score function in their work. “The coronavirus puzzles are set up such that high-scoring models have a better chance of actually binding to the target spike protein.” Ultimately, high-scoring solutions are analyzed by researchers and considered for real-world use….(More)”.

Crowdsourcing hypothesis tests: making transparent how design choices shape research results

Curated on Posted on by Stefaan Verhulst

Paper by J.F. Landy and Leonid Tiokhin: “To what extent are research results influenced by subjective decisions that scientists make as they design studies?

Fifteen research teams independently designed studies to answer five original research questions related to moral judgments, negotiations, and implicit cognition. Participants from two separate large samples (total N > 15,000) were then randomly assigned to complete one version of each study. Effect sizes varied dramatically across different sets of materials designed to test the same hypothesis: materials from different teams rendered statistically significant effects in opposite directions for four out of five hypotheses, with the narrowest range in estimates being d = -0.37 to +0.26. Meta-analysis and a Bayesian perspective on the results revealed overall support for two hypotheses, and a lack of support for three hypotheses.

Overall, practically none of the variability in effect sizes was attributable to the skill of the research team in designing materials, while considerable variability was attributable to the hypothesis being tested. In a forecasting survey, predictions of other scientists were significantly correlated with study results, both across and within hypotheses. Crowdsourced testing of research hypotheses helps reveal the true consistency of empirical support for a scientific claim….(More)”.

Research co-design in health: a rapid overview of reviews

Curated on Posted on by Stefaan Verhulst

Paper by Peter Slattery, Alexander K. Saeri & Peter Bragge: “Billions of dollars are lost annually in health research that fails to create meaningful benefits for patients. Engaging in research co-design – the meaningful involvement of end-users in research – may help address this research waste. This rapid overview of reviews addressed three related questions, namely (1) what approaches to research co-design exist in health settings? (2) What activities do these research co-design approaches involve? (3) What do we know about the effectiveness of existing research co-design approaches? The review focused on the study planning phase of research, defined as the point up to which the research question and study design are finalised….

A total of 26 records (reporting on 23 reviews) met the inclusion criteria. Reviews varied widely in their application of ‘research co-design’ and their application contexts, scope and theoretical foci. The research co-design approaches identified involved interactions with end-users outside of study planning, such as recruitment and dissemination. Activities involved in research co-design included focus groups, interviews and surveys. The effectiveness of research co-design has rarely been evaluated empirically or experimentally; however, qualitative exploration has described the positive and negative outcomes associated with co-design. The research provided many recommendations for conducting research co-design, including training participating end-users in research skills, having regular communication between researchers and end-users, setting clear end-user expectations, and assigning set roles to all parties involved in co-design…

Research co-design appears to be widely used but seldom described or evaluated in detail. Though it has rarely been tested empirically or experimentally, existing research suggests that it can benefit researchers, practitioners, research processes and research outcomes. Realising the potential of research co-design may require the development of clearer and more consistent terminology, better reporting of the activities involved and better evaluation….(More)”.