Crowdsourcing the Future?

About a month ago, on 7th December 2016, DR Kingsley Purdam (Manchester) organised a one day workshop on citizen science, and in particular on citizen science from a social science methodological perspective. The day organised with the support of the National Centre for Research Methods (NCRM).

The purpose of the workshop/conference was to explore the future of citizen science and citizen social science methods as research tools. In particular, understanding the different types of applications, methods, the data and the challenges posed. Because the point of view was based on methodologies in social sciences, issues about expertise, divisions of labour, different ways of seeing, data quality, questions about what might still be going undocumented and the ethical issues raised were all discussed.

The workshop was structured around two blocks of discussion – the morning around methods, data and ethics, while the after looked at issues of participation and working in the area of policy, as well as a discussion of the specific issues that need to be discussed for a citizen social science project.

As an introduction, both natural science and social science projects were presented. You can find a summary on twitter of some of the points that came up during the day with the hashtag #crowdfutures.

Some of the important tweets are captured here with comments (bit storify style).

Chris Lintott started the day with a discussion of large-scale, online citizen science projects, with the story of Zooniverse.

People participate in Zooniverse because they want to do something useful, and he pointed to the complexities of combining machine learning with citizen science effort while maintaining motivation and interest.

While I presented after Chris, and mostly talked about a more social theory explanation of what Extreme Citizen Science is – in particular, the creation of technologies that are embedded with a social participatory process. Many of the processes that I described were small-scale, and local. I have also pointed to the growth of citizen science and the Doing It Together Science project that we currently run.

However, in the discussion that followed we agreed that the nature of participation and many of the issues that come in these projects are similar across the scales even if the mechanisms for engagement are different.

Ben Rich (BBC), covered issues of engagement in weather observation that the BBC implemented successfully, with million observations and report in the first year

Hilary Geoghegan (Reading) & Alison Dyke (SEI)  talked about the UK EOF study on the motivation of participants and the ethics of participation, as well as the tensions between contributory and co-created citizen science in environmental research.

Will Dixon (Manchester) described the Cloudy with Pain project which engaged 12,000 participants and receives substantial information. The project also experiments with some access to data and opportunity for analysis by the participants themselves.

Kingsley Purdam (Manchester) talked about the complexity of citizen social science about begging, when the beggars are involved in data collection. Another Manchester-based project looked at linguistic diversity in street signs

The next set of talks raised some important point, including by Erinma Ochu on the process of creating the Robot Orchestra as a participatory DIY electronic and creative process, raising issues about expertise and success (the orchestra is in very high demand); Monika Buscher (Lancaster) emphasising that citizen social science is not about bigger torch to understand reality, but critique science & social science; and Alex Albert (Manchester), who run  project to encourage citizen reporting of empty houses and consider what should be done with them, highlighted the challenges of starting a project and recruiting participants. Liz Richardson (Manchester), talked about the interface between participatory action research and citizen science, and described her work with a community who collected data and asked for guidance on how to analyse it. The three talks by Monika, Alex, and Liz raised many issues about the participation of people in different stages of the research process, and the role of established researchers in such projects.

The last set of talks focused back on ecological and medical projects: Rachel Webster of Manchester Museum explained the museum digitising effort, and how they are making progress one MSc in computing student at a time – the integration of citizen science with small museum activities is a resource challenge, so the work with students require some compromises. There was also a demonstration of setting systems for citizen science and then discovering how they are used:

Lamiece pointed that a challenge with such approach is to get the app downloaded and to see continued use, although so far there are 1500 participants, 800,000 observations. There is also Data challenge of presence/absence reporting to make sense of what the data means.

Ian Thornhill fro mEarthWatch who coordinates the FreshWater Watch project demonstrate how simple data collection tools open up space for participant’s innovations in tools and in data collection. He also provided different models of how projects are run – corporate sponsorship, or by payment from interested communities.

Some of the points in the discussion include the need to balance scientific data collection and activism (especially for projects such as those that Liz Richardson described). Also balancing small scale, deep engagement or large datasets, wide engagement – e.g. for 3 years as researchers on projects that got limited funding and a goal. The need to consider what participation is doing to citizen science, and what science is doing to it? How to balance between the two? and in general, the wider societal impacts of projects cannot be ignored. There are also people that coming from a policy perspective, and try to push for procedural aspects, not interested in engagement issues.

There are also ethical issues such as those that relate to volunteer management – what should be done with contributors that are not doing good work? exclude them? train? ignore them? There is a constant need to think of useful roles and how making people valued for their contribution.

Another set of questions explored what citizen social science does to science? How are issues about ownership,  responsibilities to ensuring data quality integrated into project planning and management?

UCL Synergies podcast – Congo Citizen Science

The “UCL Synergies podcasts” is series of interviews with researchers who are working on a shared problem from two disciplinary perspective. It is part of the activities to demonstrate how UCL addresses the grand challenges. The series itself is an excellent  demonstration of the issues that come up in interdisciplinary research and you can find it here

As part of this series, Jerome Lewis and I had a conversation with Sue Nelson on our work. The podcast is about 10 minutes,  and you can listen to it here.

Esri Education User Conference talk: Citizen Science & Geographical Technologies: creativity, learning, and engagement

The slides below are from my keynote talk at the Esri Education User Conference 2016. The conference focused on creativity and its relevant to education and the utilisation of GIS (especially Esri software) at different levels of education.

My talk explored the area of citizen science and extreme citizen science and the way geographical technologies contribute to creativity and learning. As I continue to assume that many of the audience don’t know about citizen science, I start with a review of the field as a way to contextualise what we, as a group, try to do.

[The talk is similar, in parts, to other talks that are captured here on my blog (workshop on theory, practice and policy, standards and recommendation for citizen science, or the current developments in ExCiteS). I’m updating the slides with lessons on what seem to work or not in previous talks. Social media is helpful for that – I can see which points people found most useful/meaningful!]

The talk starts with an historical perspective of citizen science, continue with the societal and technical trends that are at the basis of the current growth in citizen science. Having done that, I’m using a typology that looks at domain (academic discipline), technology, and engagement as a way to introduce examples of citizen science activities. I’m using the trailer for the TV series ‘the Crowd & the Cloud’ to recap the discussions on citizen science activities. I also mention the growth of practitioners community through the Citizen Science Associations.

Next, on this basis, I’m covering the concepts and practices of Extreme Citizen Science – what we do and how. I’m using examples from the work on noise, community resource management and earthquake and fire preparedness to demonstrate the concept.

The last part of the talk focuses specifically on creativity and learning from the Citizen Cyberlab project, and I explain the next steps that we will carry out in the Doing It Together Science project. I complete the talk by giving examples for activities that the audience can do by themselves.

Throughout the talk, I’m showing how Esri technologies are being used in citizen science. It wasn’t difficult to find examples – Esri’s GIS is used in BioBlitzes, Globe at Night, links to OpenStreetMap, and support the work that the ExCiteS group is doing. Survey123 and similar tools can be used to create novel projects and experiment with them. ArcGIS Online will be linked to GeoKey, to allow analysis of community mapping efforts. In short, there is plenty of scope for GIS as an integral part of citizen science projects.

Alan Irwin talk on Citizen Science and Scientific Citizenship (JRC, October 2015)

The EU Joint Research Centre in Ispra has recently released the recording of a talk by Alan Irwin at the Joint Research Centre as part of the STS “Contro  Corrente” series of seminars from 15 October 2015, with Jerome Ravetz and Silvio Funtowicz (famous for their post-normal science) as discussants. The talk, titled Citizen Science and Scientific Citizenship: same words, different meanings? is using the two keynotes at the Citizen Science Association 2015 conference (by Chris Filardi and Amy Robinson) as a starting point for a discussion about the relationships of citizen science to scientific citizenship.

If you are interested in the wider place of citizen science within the scientific enterprise, this seminar is an opportunity to hear from 3 people who thought about this for a long time (and their work influenced my thinking). It’s very much worth to spend the time to follow the whole discussion).

Two very valuable points from Irwin’s talk are, first, the identification ‘that the defining characteristics of citizen science is its location at the point where public participation and knowledge production – or societal context and epistemology – meet‘.

Secondly, the identification that scientific citizenship is having the following characteristics – focus on sociotechnical futures with specifically asking question about the relationship between knowledge and democracy; which highlights the political economy of knowledge and the changing nature of citizenship as practised engagement.

Also valuable is the linkage of knowledge, power, and justice and how these play out in citizen science in its different forms.

I’ll admit that I was especially interested in the way that my model of participation in citizen science was used in this seminar. However, having a blog is also an opportunity to respond to some of the points that were discussed in the seminar!

First, Alan Irwin note that scientific citizenship does not happen at the top level of participation but throughout the levels. This is something that I’m emphasising in every talk in which I use this model. As Silvio Funtowicz correctly identified, the model is (yet another) borrowing from Sherry Arnstein ladder of participation as I clearly indicated. However, it is wrong to put the value judgement that is at the centre of Arnstein analysis of participation into citizen science – there might be just as much engagement in volunteer computing as in ‘extreme’ citizen science.

Second, Funtowicz commented that the equivalent of ‘extreme citizen science’ in Arnstein ladder does not reach very high level of participation. I disagree. Arnstein top level is ‘Citizen Control, have-not citizens obtain the majority of decision-making seats, or full managerial power’. If in citizen science project we shift into more equal mode of knowledge production where the project is shaped by all participants, especially marginalised ones, and the scientists working as facilitators in service of the community, aren’t we at the same place?


Extreme Citizen Science in Esri ArcNews

The winter edition of Esri ArcNews (which according to Mike Gould of Esri, is printed in as many copies as Forbes) includes an article on the activities of the Extreme Citizen Science group in supporting indigenous groups in mapping. The article highlights the Geographical Information Systems (GIS) aspects of the work, and mentioning many members of the group.

You can read it here:

UCL Institute for Global Prosperity Talk: Extreme Citizen Science – Current Developments

The slides below are from a talk that I gave today at UCL Institute for Global Prosperity

The abstract for the talk is:

With a growing emphasis on civil society-led change in diverse disciplines, from International Development to Town Planning, there is an increasing demand to understand how institutions might work with the public effectively and fairly.

Extreme Citizen Science is a situated, bottom-up practice that takes into account local needs, practices and culture and works with broad networks of people to design and build new devices and knowledge creation processes that can transform the world.

In this talk, I discussed the work of UCL Extreme Citizen Science group within the wider context of the developments in the field of citizen science. I covered the work that ExCiteS has already done, currently developing and plans for the future.

Eye on Earth (Day 2 – Morning) – moving to data supply

Eye on Earth (Day 2 – Morning) – moving to data supply The second day of Eye on Earth moved from data demand to supply . You can find my posts from day one, with the morning and the afternoon sessions. I have only partial notes on the plenary Data Revolution-data supply side, although I’ve posted separately the slides from my talk. The description of the session stated: The purpose of the the session is to set the tone and direction for the “data supply” theme of the 2nd day of the Summit. The speakers focused on the revolution in data – the logarithmic explosion both in terms of data volume and of data sources. Most importantly, the keynote addresses will highlight the undiscovered potential of these new resources and providers to contribute to informed decision-making about environmental, social and economic challenges faced by politicians, businesses, governments, scientists and ordinary citizens.

The session was moderated by Barbara J. Ryan (GEO) the volume of data that was download in Landsat demonstrate the information revolution. From 53 scene/day to 5700 scene/day once it became open data – demonstrate the power of open. Now there are well over 25 million downloads a year. There is a similar experience in Canada, and there are also new and innovative ways to make the data accessible and useful.

The first talk was from Philemon Mjwara (GEO), the amount of data is growing and there is an increasing demand for Earth Observations, but even in the distilled form of academic publications there is an explosion and it’s impossible to read everything about your field. Therefore we need to use different tools – search engines, article recommendation systems. This is also true for EO data – users need the ability to search, then process and only then they can use the information. This is where GEO come in. It’s about comprehensive, effective and useful information. GEO works with 87 participating organisations. They promote Open Data policies across their membership, as this facilitate creation of a global system of systems (GEOSS). GEOSS is about supply, and through the GEO infrastructure it can be share with many users. We need to remember that the range of sources is varied: from satellite, to aerial imagery, to under-sea rovers. GEO works across the value chain – the producers, value added organisation and the users. An example of this working is in analysis that helps to link information about crops to information about potential vulnerability in food price.

Mary Glackin (the Weather Corporation), reviewed how weather data is making people safer and business smarter. The Weather Company is about the expression of climate in the patterns of weather. Extreme events make people notice. Weather is about what happen in the 100 km above the Earth surface, but also the 3.6 km average depth of the oceans, which we don’t properly observe yet and have an impact on weather. There are 3 Challenges: keep people safe, helping businesses by forecasting, and engage with decision makers. Measuring the atmosphere and the oceans is done by many bodies which go beyond official bodies – now it includes universities, companies, but also citizens observations which is done across the world (through Weather Underground). The participants, in return, receive a localised forecast for their area and details of nearby observations. It’s a very large citizen science project, and engagement with citizen scientists is part of their work. Forecasting require complex computer modelling – and they produce 11 Billion forecasts a day. Engaging decision makers can be individual fisherman who need to decide if to go out to sea or not. There is a need for authoritative voice that create trust when there are critical issues such as response to extreme events. Another example is the use of information about turbulence from airplanes which are then used to improve modelling and provide up to date information to airlines to decide on routes and operations. Technology is changing – for example, smartphones now produce air pressure data and other sensing abilities that can be used for better modelling. There are policies that are required to enable data sharing. While partnerships between government and private sector companies. A good example is NOAA agreeing to share all their data with cloud providers (Microsoft, Amazon, Google) on the condition that the raw data will be available to anyone to download free of charge, but the providers are free to create value added services on top of the data.

Next was my talk, for which a summary and slide are available in a separate post.

Chris Tucker (MapStory) suggested that it is possible to empower policy makers with open data. MapStory is an atlas of changes that anyone can edit, as can be seen in the development of a city, or the way enumeration district evolved over time. The system is about maps, although the motivation to overlay information and collect it can be genealogy – for example to be able to identify historical district names. History is a good driver to understand the world, for example maps that show the colonisation of Africa. The information can be administrative boundaries, imagery or environmental information. He sees MapStory as a community. Why should policy makers care? they should because ‘change is the only constant’, and history help us in understanding how we got here, and think about directions for the future. Policy need to rely on data that is coming from multiple sources – governmental sources, NGOs, or citizens’ data. There is a need for a place to hold such information and weave stories from it. Stories are a good way to work out the decisions that we need to make, and also allow ordinary citizens to give their interpretation on information. In a way, we are empowering people to tell story.

The final talk was from Mae Jemison (MD and former astronaut). She grow up during a period of radical innovations, both socially and scientifically – civil rights, new forms or dance, visions of a promising future in Start Trek, and the Apollo missions. These have led her to get to space in a Shuttle mission in 1992, during which she was most of the time busy with experiments, but from time to time looked out of the window, to see the tiny sliver of atmosphere around the Earth, within which whole life exist. Importantly, the planet doesn’t need protection – the question is: will humans be in the future of the planet? Every generation got a mission, and ours is to see us linked to the totality of Earth – life, plants and even minerals. Even if we create a way to travel through space, the vast majority of us will not get off this planet. So the question is: how do we get to the extraordinary? This lead us to look at data, and we need to be aware that while there is a lot of it, it doesn’t necessarily mean information, and information doesn’t mean wisdom. She note that in medical studies data (from test with patients) have characteristics of specificity (relevant to the issue at hand) and sensitivity (can it measure what we want to measure?). We tend to value and act upon what we can measure, but we need to consider if we are doing it right. Compelling data cause us to pay attention, and can lead to action. Data connect us across time and understanding a universe grater that ourselves, as the pictures from Hubble telescope that show the formation of stars do. These issues are coming together in her current initiative “100 years starship” – if we aim to have an interstellar ship built within the next 100 years, we will have to think about sustainability, life support and ecosystems in a way that will help us solve problems here on Earth. It is about how to have an inclusive journey to make transformation on Earth. She completed her talk by linking art, music and visualisation with the work of Bella Gaia

After the plenary, the session Data for Sustainable Development was building on the themes from the plenary. Some of the talks in the session were:

Louis Liebenberg presented cybertracker – showing how it evolved from early staged in the mid 1990s to a use across the world. The business model of cybertracker is such that people can download it for free, but it mostly used off-line in many places, with majority of the users that use it as local tool. This raise issues of data sharing – data doesn’t go beyond that the people who manage the project. Cybertracker address the need to to extend citizen science activities to a whole range of participants beyond the affluent population that usually participate in nature observations.

Gary Lawrence – discussed how with Big Data we can engage the public in deciding which problem need to be resolved – not only the technical or the scientific community. Ideas will emerge within Big Data that might be coincident or causality. Many cases are coincidental. The framing should be: who are we today? what are we trying to become? What has to be different two, five, ten years from now if we’re going to achieve it? most organisations don’t even know where they are today. There is also an issue – Big Data: is it driven by a future that people want. There are good examples of using big data in cities context that take into account the need of all groups – government, business and citizens in Helsinki and other places.

B – the Big Data in ESPA experience – data don’t have value until they are used. International interdisciplinary science for ecosystems services for poverty alleviation programme. Look at opportunities, then the challenges. Opportunities: SDGs are articulation of a demand to deliver benefits to societal need for new data led solution for sustainable development, with new technologies: remote sensing / UAVs, existing data sets, citizen science and mobile telephony, combined with open access to data and web-based applications. Citizen Science is also about empowering communities with access to data. We need to take commitments to take data and use it to transforming life.

Discussion: lots of people are sitting on a lots of valuable data that are considered as private and are not shared. Commitment to open data should be to help in how to solve problems in making data accessible and ensure that it is shared. We need to make projects aware that the data will be archived and have procedures in place, and also need staff and repositories. Issue is how to engage private sector actors in data sharing. In work with indigenous communities, Louis noted that the most valuable thing is that the data can be used to transfer information to future generations and explain how things are done.