Citizen science is booming during the pandemic


Sigal Samuel at Vox: “…The pandemic has driven a huge increase in participation in citizen science, where people without specialized training collect data out in the world or perform simple analyses of data online to help out scientists.

Stuck at home with time on their hands, millions of amateurs arouennd the world are gathering information on everything from birds to plants to Covid-19 at the request of institutional researchers. And while quarantine is mostly a nightmare for us, it’s been a great accelerant for science.

Early in the pandemic, a firehose of data started gushing forth on citizen science platforms like Zooniverse and SciStarter, where scientists ask the public to analyze their data online.It’s a form of crowdsourcing that has the added bonus of giving volunteers a real sense of community; each project has a discussion forum where participants can pose questions to each other (and often to the scientists behind the projects) and forge friendly connections.

“There’s a wonderful project called Rainfall Rescue that’s transcribing historical weather records. It’s a climate change project to understand how weather has changed over the past few centuries,” Laura Trouille, vice president of citizen science at the Adler Planetarium in Chicago and co-lead of Zooniverse, told me. “They uploaded a dataset of 10,000 weather logs that needed transcribing — and that was completed in one day!”

Some Zooniverse projects, like Snapshot Safari, ask participants to classify animals in images from wildlife cameras. That project saw daily classifications go from 25,000 to 200,000 per day in the initial days of lockdown. And across all its projects, Zooniverse reported that 200,000 participants contributed more than 5 million classifications of images in one week alone — the equivalent of 48 years of research. Although participation has slowed a bit since the spring, it’s still four times what it was pre-pandemic.

Many people are particularly eager to help tackle Covid-19, and scientists have harnessed their energy. Carnegie Mellon University’s Roni Rosenfeld set up a platform where volunteers can help artificial intelligence predict the spread of the coronavirus, even if they know nothing about AI. Researchers at the University of Washington invited people to contribute to Covid-19 drug discovery using a computer game called Foldit; they experimented with designing proteins that could attach to the virus that causes Covid-19 and prevent it from entering cells….(More)”.

Using Data and Citizen Science for Gardening Success


Article by Elizabeth Waddington: “…Data can help you personally by providing information you can use. And it also allows you to play a wider role in boosting understanding of our planet and tackling the global crises we face in a collaborative way. Consider the following examples.

Grow Observatory

This is one great example of data gathering and citizen science. Grow Observatory is a European citizen’s observatory through which people work together to take action on climate change, build better soil, grow healthier food and corroborate data from the new generation of Copernicus satellites.

Twenty-four Grow communities in 13 European countries created a network of over 6,500 ground-based soil sensors and collected a lot of soil-related data. And many insights have helped people learn about and test regenerative food growing techniques.

On their website, you can explore sensor locations, or make use of dynamic soil moisture maps. With the Grow Observatory app, you can get crop and planting advice tailored to your location, and get detailed, science-based information about regenerative growing practices. Their water planner also allows small-scale growers to learn more about how much water their plants will need in their location over the coming months if they live in one of the areas which currently have available data…

Cooperative Citizen Science: iNaturalist, Bioblitzes, Bird Counts, and More

Wherever you live, there are many different ways to get involved and help build data. From submitting observations on wildlife in your garden through apps like iNaturalist to taking part in local Bioblitzes, bird counts, and more – there are plenty of ways we can collect data that will help us – and others – down the road.

Collecting data through our observations, and, crucially, sharing that data with others can help us create the future we all want to see. We, as individuals, can often feel powerless. But citizen science projects help us to see the collective power we can wield when we work together. Modern technology means we can be hyper-connected, and affect wider systems, even when we are alone in our own gardens….(More)”

Citizen social science in practice: the case of the Empty Houses Project


Paper by Alexandra Albert: “The growth of citizen science and participatory science, where non-professional scientists voluntarily participate in scientific activities, raises questions around the ownership and interpretation of data, issues of data quality and reliability, and new kinds of data literacy. Citizen social science (CSS), as an approach that bridges these fields, calls into question the way in which research is undertaken, as well as who can collect data, what data can be collected, and what such data can be used for. This article outlines a case study—the Empty Houses Project—to explore how CSS plays out in practice, and to reflect on the opportunities and challenges it presents. The Empty Houses Project was set up to investigate how citizens could be mobilised to collect data about empty houses in their local area, so as to potentially contribute towards tackling a pressing policy issue. The study shows how the possibilities of CSS exceed the dominant view of it as a new means of creating data repositories. Rather, it considers how the data produced in CSS is an epistemology, and a politics, not just a realist tool for analysis….(More)”.

As Jakarta floods again, humanitarian chatbots on social media support community-led disaster response


Blog by Petabencana: “On February 20th, #banjir and #JakartaBanjir were the highest trending topics on Twitter Indonesia, as the capital city was inundated for the third major time this year, following particularly heavy rainfall from Friday night (19/2/2021) to Saturday morning (20/02/2021). As Jakarta residents turned to social media to share updates about the flood, they were greeted by “Disaster Bot” – a novel AI-assisted chatbot that monitors social media for posts about disasters and automatically invites users to submit more detailed disaster reports. These crowd-sourced reports are used to map disasters in real-time, on a free and open source website, PetaBencana.id.

As flooding blocked major thoroughfares and toll roads, disrupted commuter lines, and cut off electricity to over 60,000 homes, residents continued to share updates about the flood situation in order to stay alert and make timely decisions about safety and response. Hundreds of residents submitted flood reports to PetaBencana.id, alerting each other about water levels, broken infrastructures and road accessibility. The Jakarta Emergency Management Agency also updated the map with official information about flood affected  areas, and monitored the map to respond to resident needs. PetaBencana.id experienced a 2000% in activity in under 12 hours as residents actively checked the map to understand the flooding situation, avoid flooded areas, and make decisions about safety and response. 

Residents share updates about flood-affected road access through the open source information sharing platform, PetaBencana.id. Thousands of residents used the map to navigate safely as heavy rainfall inundated the city for the third major time this year.

As flooding incidents continue to occur with increasing intensity across the country, community-led information sharing is once again proving its significance in supporting response and planning at multiple scales. …(More)”.

Citizen Scientists Are Filling Research Gaps Created by the Pandemic


Article by  Theresa Crimmins, Erin Posthumus, and Kathleen Prudic: “The rapid spread of COVID-19 in 2020 disrupted field research and environmental monitoring efforts worldwide. Travel restrictions and social distancing forced scientists to cancel studies or pause their work for months. These limits measurably reduced the accuracy of weather forecasts and created data gaps on issues ranging from bird migration to civil rights in U.S. public schools.

Our work relies on this kind of information to track seasonal events in nature and understand how climate change is affecting them. We also recruit and train citizens for community science – projects that involve amateur or volunteer scientists in scientific research, also known as citizen science. This often involves collecting observations of phenomena such as plants and animalsdaily rainfall totalswater quality or asteroids.

Participation in many community science programs has skyrocketed during COVID-19 lockdowns, with some programs reporting record numbers of contributors. We believe these efforts can help to offset data losses from the shutdown of formal monitoring activities….(More)”.

Geographic Citizen Science Design


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


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


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


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


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)”.