Citizen Sensing: A Toolkit


Book from Making Sense: “Collaboration using open-source technologies makes it possible to create new and powerful forms of community action, social learning and citizenship. There are now widely accessible platforms through which we can come together to make sense of urgent challenges, and discover ways to address these. Together we can shape our streets, neighbourhoods, cities and countries – and in turn, shape our future. You can join with others to become the solution to challenges in our environment, in our communities and in the way we live together.

In this book, there are ideas and ways of working that can help you build collective understanding and inspire others to take action. By coming together with others on issues you identify and define yourselves, and by designing and using the right tools collaboratively, both your awareness and ability to act will be improved. In the process, everyone involved will have better insights, better arguments and better discussions; sometimes to astonishing effect!

We hope this book will help you engage people to learn more about an issue that concerns you, support you to take action, and change the world for the better. This resource will teach you how to scope your questions, identify and nurture relevant communities, and plan an effective campaign. It will then help you gather data and evidence, interpret your findings, build awareness and achieve tangible outcomes. Finally, it will show you how to reflect on these outcomes, and offers suggestions on how you can leave a lasting legacy.

This book is intended to help community activists who are curious or concerned about one or more issues, whether local or global, and are motivated to take action. This resource can also be of value to professionals in organisations which support community actions and activists. Finally, this book will be of interest to researchers in the fields of citizen science, community activism and participatory sensing, government officials and other public policy actors who wish to include citizens’ voices in the decision-making process…(More)”.

Coastal research increasingly depends on citizen scientists


Brenna Visser at CS Monitor: “…This monthly ritual is a part of the COASST survey, a program that relies on data taken by volunteers to study large-scale patterns in seabird populations on the West Coast. The Haystack Rock Awareness Program conducts similar surveys for sea stars and marine debris throughout the year.

Surveys like these play a small part in a growing trend in the science community to use citizen scientists as a way to gather massive amounts of data. Over the weekend, marine scientists and conservationists came to Cannon Beach for an annual Coast Conference, a region wide event to discuss coastal science and stewardship.

Whether the presentation was about ocean debris, marine mammals, seabirds, or ocean jellies, many relied on the data collection work of volunteers throughout the state. A database for citizen science programs called Citsci.org, which recorded only a few dozen groups 10 years ago, now has more than 500 groups registered across the country, with new ones registering every day….

Part of the rise has to do with technology, she said. Apps that help identify species and allow unprecedented access to information have driven interest up and removed barriers that would have otherwise made it harder to collect data without formal training. Another is the science community slowly coming around to accept citizen science.

“I think there’s a lot of reticence in the science community to use citizen science. There’s some doubt the data collected is of the precision or accuracy that is needed to document phenomena,” Parrish said. “But as it grows, the more standardized it becomes. What we’re seeing right now is a lot of discussion in citizen science programs asking what they need to do to get to that level.”…While a general decline in federal funding for scientific research could play a factor in the science community’s acceptance of using volunteer-collected data, Parrish said, regardless of funding, there are some projects only citizen scientists can accomplish….(More)”

The Promise of Community Citizen Science


Report by Ramya ChariLuke J. MatthewsMarjory S. BlumenthalAmanda F. Edelman, and Therese Jones: “Citizen science is public participation in research and scientific endeavors. Citizens volunteer as data collectors in science projects; collaborate with scientific experts on research design; and actively lead and carry out research, exerting a high degree of control and ownership over scientific activities. The last type — what we refer to as community citizen science — tends to involve action-oriented research to support interventional activities or policy change. This type of citizen science can be of particular importance to those working at the nexus of science and decisionmaking.

The authors examine the transformative potential of community citizen science for communities, science, and decisionmaking. The Perspective is based on the authors’ experiences working in collaboration with community groups, extensive readings of the scientific literature, and numerous interviews with leading scholars and practitioners in the fields of citizen science and participatory research. It first discusses models of citizen science in general, including community citizen science, and presents a brief history of its rise. It then looks at possible factors motivating the development of community citizen science, drawing from an exploration of the relationships among citizens, science, and decisionmaking. The final section examines areas in which community citizen science may exhibit promise in terms of outcomes and impacts, discusses concerns that may hinder its overall potential, and assesses the roles different stakeholders may play to continue to develop community citizen science into a positive force for science and society.

Key Findings

At Its Core, Citizen Science Is Public Participation in Research and Scientific Endeavors

  • Citizens volunteer as data collectors in science projects, collaborate with scientific experts on research design, and actively lead and carry out research.
  • It is part of a long tradition of rebirth of inventors, scientists, do-it-yourselfers, and makers at all levels of expertise.
  • Instead of working alone, today’s community citizen scientists take advantage of new technologies for networking and coordination to work collaboratively; learn from each other; and share knowledge, insights, and findings.

The Democratization of Science and the Increasingly Distributed Nature of Expertise Are Not Without Concern

  • There is some tension and conflict between current standards of practice and the changes required for citizen science to achieve its promising future.
  • There is also some concern about the potential for bias, given that some efforts begin as a form of activism.

Yet the Efforts of Community Citizen Science Can Be Transformative

  • Success will require an engaged citizenry, promote more open and democratic decisionmaking processes, and generate new solutions for intractable problems.
  • If its promise holds true, the relationship between science and society will be profoundly transformed for the betterment of all…(More)”.

Using new data sources for policymaking


Technical report by the Joint Research Centre (JRC) of the European Commission: “… synthesises the results of our work on using new data sources for policy-making. It reflects a recent shift from more general considerations in the area of Big Data to a more dedicated investigation of Citizen Science, and it summarizes the state of play. With this contribution, we start promoting Citizen Science as an integral component of public participation in policy in Europe.

The particular need to focus on the citizen dimension emerged due to (i) the increasing interest in the topic from policy Directorate-Generals (DGs) of the European Commission (EC); (ii) the considerable socio-economic impact policy making has on citizens’ life and society as a whole; and (iii) the clear potentiality of citizens’ contributions to increase the relevance of policy making and the effectiveness of policies when addressing societal challenges.

We explicitly concentrate on Citizen Science (or public participation in scientific research) as a way to engage people in practical work, and to develop a mutual understanding between the participants from civil society, research institutions and the public sector by working together on a topic that is of common interest.

Acknowledging this new priority, this report concentrates on the topic of Citizen Science and presents already ongoing collaborations and recent achievements. The presented work particularly addresses environment-related policies, Open Science and aspects of Better Regulation. We then introduce the six phases of the ‘cyclic value chain of Citizen Science’ as a concept to frame citizen engagement in science for policy. We use this structure in order to detail the benefits and challenges of existing approaches – building on the lessons that we learned so far from our own practical work and thanks to the knowledge exchange from third parties. After outlining additional related policy areas, we sketch the future work that is required in order to overcome the identified challenges, and translate them into actions for ourselves and our partners.

Next steps include the following:

 Develop a robust methodology for data collection, analysis and use of Citizen Science for EU policy;

 Provide a platform as an enabling framework for applying this methodology to different policy areas, including the provision of best practices;

 Offer guidelines for policy DGs in order to promote the use of Citizen Science for policy in Europe;

 Experiment and evaluate possibilities of overarching methodologies for citizen engagement in science and policy, and their case specifics; and

 Continue to advance interoperability and knowledge sharing between currently disconnected communities of practise. …(More)”.

Do-it-yourself science is taking off


The Economist: “…Citizen science has been around for ages—professional astronomers, geologists and archaeologists have long had their work supplemented by enthusiastic amateurs—and new cheap instruments can usefully spread the movement’s reach. What is more striking about bGeigie and its like, though, is that citizens and communities can use such instruments to inform decisions on which science would otherwise be silent—or mistrusted. For example, getting hold of a bGeigie led some people planning to move home after Fukushima to decide they were safer staying put.

Ms Liboiron’s research at CLEAR also stresses self-determination. It is subject to “community peer review”: those who have participated in the lab’s scientific work decide whether it is valid and merits publication. In the 1980s fishermen had tried to warn government scientists that stocks were in decline. Their cries were ignored and the sudden collapse of Newfoundland’s cod stocks in 1992 had left 35,000 jobless. The people taking science into their own hands with Ms Liboiron want to make sure that in the future the findings which matter to them get heard.

Swell maps

Issues such as climate change, plastic waste and air pollution become more tangible to those with the tools in their hands to measure them. Those tools, in turn, encourage more people to get involved. Eymund Diegel, a South African urban planner who is also a keen canoeist, has long campaigned for the Gowanus canal, close to his home in Brooklyn, to be cleaned up. Effluent from paint manufacturers, tanneries, chemical plants and more used to flow into the canal with such profligacy that by the early 20th century the Gowanus was said to be jammed solid. The New York mob started using the waterway as a dumping ground for dead bodies. In the early part of this century it was still badly polluted.

In 2009 Mr Diegel contacted Public Lab, an NGO based in New Orleans that helps people investigate environmental concerns. They directed him to what became his most powerful weapon in the fight—a mapping rig consisting of a large helium balloon, 300 metres (1,000 feet) of string and an old digital camera. A camera or smartphone fixed to such a balloon can take more detailed photographs than the satellite imagery used by the likes of Google for its online maps, and Public Lab provides software, called MapKnitter, that can stitch these photos together into surveys.

These data—and community pressure—helped persuade the Environmental Protection Agency (EPA) to make the canal eligible for money from a “superfund” programme which targets some of America’s most contaminated land. Mr Diegel’s photos have revealed a milky plume flowing into the canal from a concealed chemical tank which the EPA’s own surveys had somehow missed. The agency now plans to spend $500m cleaning up the canal….(More)”.

Augmented CI and Human-Driven AI: How the Intersection of Artificial Intelligence and Collective Intelligence Could Enhance Their Impact on Society


Blog by Stefaan Verhulst: “As the technology, research and policy communities continue to seek new ways to improve governance and solve public problems, two new types of assets are occupying increasing importance: data and people. Leveraging data and people’s expertise in new ways offers a path forward for smarter decisions, more innovative policymaking, and more accountability in governance. Yet, unlocking the value of these two assets not only requires increased availability and accessibility (through, for instance, open data or open innovation), it also requires innovation in methodology and technology.

The first of these innovations involves Artificial Intelligence (AI). AI offers unprecedented abilities to quickly process vast quantities of data that can provide data-driven insights to address public needs. This is the role it has for example played in New York City, where FireCast, leverages data from across the city government to help the Fire Department identify buildings with the highest fire risks. AI is also considered to improve education, urban transportation,  humanitarian aid and combat corruption, among other sectors and challenges.

The second area is Collective Intelligence (CI). Although it receives less attention than AI, CI offers similar potential breakthroughs in changing how we govern, primarily by creating a means for tapping into the “wisdom of the crowd” and allowing groups to create better solutions than even the smartest experts working in isolation could ever hope to achieve. For example, in several countries patients’ groups are coming together to create new knowledge and health treatments based on their experiences and accumulated expertise. Similarly, scientists are engaging citizens in new ways to tap into their expertise or skills, generating citizen science – ranging from mapping our solar system to manipulating enzyme models in a game-like fashion.

Neither AI nor CI offer panaceas for all our ills; they each pose certain challenges, and even risks.  The effectiveness and accuracy of AI relies substantially on the quality of the underlying data as well as the human-designed algorithms used to analyse that data. Among other challenges, it is becoming increasingly clear how biases against minorities and other vulnerable populations can be built into these algorithms. For instance, some AI-driven platforms for predicting criminal recidivism significantly over-estimate the likelihood that black defendants will commit additional crimes in comparison to white counterparts. (for more examples, see our reading list on algorithmic scrutiny).

In theory, CI avoids some of the risks of bias and exclusion because it is specifically designed to bring more voices into a conversation. But ensuring that that multiplicity of voices adds value, not just noise, can be an operational and ethical challenge. As it stands, identifying the signal in the noise in CI initiatives can be time-consuming and resource intensive, especially for smaller organizations or groups lacking resources or technical skills.

Despite these challenges, however, there exists a significant degree of optimism  surrounding both these new approaches to problem solving. Some of this is hype, but some of it is merited—CI and AI do offer very real potential, and the task facing both policymakers, practitioners and researchers is to find ways of harnessing that potential in a way that maximizes benefits while limiting possible harms.

In what follows, I argue that the solution to the challenge described above may involve a greater interaction between AI and CI. These two areas of innovation have largely evolved and been researched separately until now. However, I believe that there is substantial scope for integration, and mutual reinforcement. It is when harnessed together, as complementary methods and approaches, that AI and CI can bring the full weight of technological progress and modern data analytics to bear on our most complex, pressing problems.

To deconstruct that statement, I propose three premises (and subsequent set of research questions) toward establishing a necessary research agenda on the intersection of AI and CI that can build more inclusive and effective approaches to governance innovation.

Premise I: Toward Augmented Collective Intelligence: AI will enable CI to scale

Premise II: Toward Human-Driven Artificial Intelligence: CI will humanize AI

Premise III: Open Governance will drive a blurring between AI and CI

…(More)”.

Federal Crowdsourcing and Citizen Science Catalog


About: “The catalog contains information about federal citizen science and crowdsourcing projects. In citizen science, the public participates voluntarily in the scientific process, addressing real-world problems in ways that may include formulating research questions, conducting scientific experiments, collecting and analyzing data, interpreting results, making new discoveries, developing technologies and applications, and solving complex problems. In crowdsourcing,organizations submit an open call for voluntary assistance from a group of individuals for online, distributed problem solving.

Projects in the catalog must meet the following criteria:

  • The project addresses societal needs or accelerates science, technology, and innovation consistent with a Federal agency’s mission.
  • Project outcomes include active management of data and data quality.
  • Participants serve as contributors, collaborators or co-creators in the project.
  • The project solicits engagement from individuals outside of a discipline’s or program’s traditional participants in the scientific enterprise.
  • Beyond practical limitations, the project does not seek to limit the number of participants or partners involved.
  • The project is opt-in; participants have full control over the extent that they participate.
  • The US Government enables or enhances the project via funding or providing an in-kind contribution. The US Government’s in-kind contribution to the project may be active or passive, formal or informal….(More)”.

Let’s create a nation of social scientists


Geoff Mulgan in Times Higher Education: “How might social science become more influential, more relevant and more useful in the years to come?

Recent debates about impact have largely assumed a model of social science in which a cadre of specialists, based in universities, analyse and interpret the world and then feed conclusions into an essentially passive society. But a very different view sees specialists in the academy working much more in partnership with a society that is itself skilled in social science, able to generate hypotheses, gather data, experiment and draw conclusions that might help to answer the big questions of our time, from the sources of inequality to social trust, identity to violence.

There are some powerful trends to suggest that this second view is gaining traction. The first of these is the extraordinary explosion of new ways to observe social phenomena. Every day each of us leaves behind a data trail of who we talk to, what we eat and where we go. It’s easier than ever to survey people, to spot patterns, to scrape the web or to pick up data from sensors. It’s easier than ever to gather perceptions and emotions as well as material facts and easier than ever for organisations to practice social science – whether investment organisations analysing market patterns, human resources departments using behavioural science, or local authorities using ethnography.

That deluge of data is a big enough shift on its own. However, it is also now being used to feed interpretive and predictive tools using artificial intelligence to predict who is most likely to go to hospital, to end up in prison, which relationships are most likely to end in divorce.

Governments are developing their own predictive tools, and have also become much more interested in systematic experimentation, with Finland and Canada in the lead,  moving us closer to Karl Popper’s vision of “methods of trial and error, of inventing hypotheses which can be practically tested…”…

The second revolution is less visible but could be no less profound. This is the hunger of many people to be creators of knowledge, not just users; to be part of a truly collective intelligence. At the moment this shift towards mass engagement in knowledge is most visible in neighbouring fields.  Digital humanities mobilise many volunteers to input data and interpret texts – for example making ancient Arabic texts machine-readable. Even more striking is the growth of citizen science – eBird had 1.5 million reports last January; some 1.5 million people in the US monitor river streams and lakes, and SETI@home has 5 million volunteers. Thousands of patients also take part in funding and shaping research on their own conditions….

We’re all familiar with the old idea that it’s better to teach a man to fish than just to give him fish. In essence these trends ask us a simple question: why not apply the same logic to social science, and why not reorient social sciences to enhance the capacity of society itself to observe, analyse and interpret?…(More)”.

BBC Four to investigate how flu pandemic spreads by launching BBC Pandemic app


BBC Press Release: “In a first of its kind nationwide citizen science experiment, Dr Hannah Fry is asking volunteers to download the BBC Pandemic App onto their smartphones. The free app will anonymously collect vital data on how far users travel over a 24 hour period. Users will be asked for information about the number of people they have come into contact with during this time. This data will be used to simulate the spread of a highly infectious disease to see what might happen when – not if – a real pandemic hits the UK.

By partnering with researchers at the University of Cambridge and the London School of Hygiene and Tropical Medicine, the BBC Pandemic app will identify the human networks and behaviours that spread infectious disease. The data collated from the app will help improve public health planning and outbreak control.

The results of the experiment will be revealed in a 90 minute landmark documentary, BBC Pandemic which will air in spring 2018 on BBC Four with Dr Hannah Fry and Dr Javid Abdelmoneim. The pair will chart the creation of the first ever life-saving pandemic, provide new insight into the latest pandemic science and use the data collected by the BBC Pandemic app to chart how an outbreak would spread across the UK.

In the last 100 years there have been four major flu pandemics including the Spanish Influenza outbreak of 1918 that killed up to 100 million people world wide. The Government National Risk Register estimates that infectious diseases are an even greater risk since 2015 and pandemic flu is the key concern as 50% of the population could be affected.

“Nobody knows when the next epidemic will hit, how far it will spread, or how many people will be affected. And yet, because of the power of mathematics, we can still be prepared for whatever lies ahead. What’s really important is that every single download will help improve our models so please please do take part – it will make a difference.” explains Dr Fry.

Dr Abdelmoneim says: “We shouldn’t underestimate the flu virus. It could easily be the cause of a major pandemic that could sweep around the world in a matter of weeks. I’m really excited about the BBC Pandemic app. If it can help predict the spread of a disease and be used to work out ways to slow that spread, it will be much easier for society and our healthcare system to manage”.

Cassian Harrison, Editor BBC Four says: “This is a bold and tremendously exciting project; bringing genuine insight and discovery, and taking BBC Four’s Experimental brief absolutely literally!”…(More)”

Crowdsourcing citizen science: exploring the tensions between paid professionals and users


Jamie Woodcock et al in the Journal of Peer Production: “This paper explores the relationship between paid labour and unpaid users within the Zooniverse, a crowdsourced citizen science platform. The platform brings together a crowd of users to categorise data for use in scientific projects. It was initially established by a small group of academics for a single astronomy project, but has now grown into a multi-project platform that has engaged over 1.3 million users so far. The growth has introduced different dynamics to the platform as it has incorporated a greater number of scientists, developers, links with organisations, and funding arrangements—each bringing additional pressures and complications. The relationships between paid/professional and unpaid/citizen labour have become increasingly complicated with the rapid expansion of the Zooniverse. The paper draws on empirical data from an ongoing research project that has access to both users and paid professionals on the platform. There is the potential through growing peer-to-peer capacity that the boundaries between professional and citizen scientists can become significantly blurred. The findings of the paper, therefore, address important questions about the combinations of paid and unpaid labour, the involvement of a crowd in citizen science, and the contradictions this entails for an online platform. These are considered specifically from the viewpoint of the users and, therefore, form a new contribution to the theoretical understanding of crowdsourcing in practice….(More)”.