Citizen Science @ Computational Foundry, Swansea, Festival of Ideas

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The Computational Foundry at the Swansea University organised two days “Festival of Ideas” as part of the activities to celebrate its opening. The first day was organised by Ben Shneiderman and focused on aspects of AI, while the second day, curated by Jenny Preece, focused on citizen science. The summary here is from the second day, which was open by Alan Dix, the Foundry director explaining that citizen science is providing new ways of understanding the social impact of data and technologies.

DSC_1716.JPGSetting the Scene: New Agendas, Broader Impacts (Professor Jenny Preece, University of Maryland).  The Computational Foundry considering how to integrate citizen science. There are opportunities for those who are coming from the science side, and the computational side – but there are tremendous opportunities for those in citizen science and Human-Computer Interaction in the field of citizen science. This is a day of action – a range of speakers on citizen science, from doing face to face – in the estuary and the field; but also an online platform on a large scale – the Zooniverse. We see also citizen science in an overseas environment, and in the context of education and public participation in science.

Jenny’s journey to citizen science came from interaction design and information studies. The aim is for interactions – new agendas research, practice, managing a local project. The broader impact – making an impact here in Swansea, but also on the wider world. We might develop a report of these new agendas and impacts. The aim is to develop a report for CSTP. Her personal journey – love the environment, and keen birders – and when NSF put out a call about social computing, she saw an opportunity to get into this area. Citizen science has a very long history within science but not within computing. In 2009, citizen science was defined by Rick Bonney and Jonathan Silvertown in papers at the time, which mostly about a partnership between scientists and volunteers to collect and analyse data. This has now shifted to a wider definition – from setting questions to producing output, and this wider understanding of citizen science is important to the way it is thought off. The work that she’s been doing recently, include small, place-based projects in NatureNet: technology for community environmental learning – see the video at videohall.com/p/963 and a paper in PNAS 2019. The project is addressing crowdsourcing – what are the special computational there? You are not using ML, drones, AI or any of this. The idea of crowdsourcing the design – that was something that made it different in terms of the NSF way to fund it. When started, the aim was to suggest design ideas of the things that they like and what they want to change. Very few design ideas came forward on a website that was set to allow participants, but there was an issue of confidence. They spend a lot of time to help small community groups to deal with watershed monitoring – the goal of the researchers was to have a preliminary map of local action projects.  In the participatory design process, the designers were thinking about a community of practice – but the participants thought that they are communicating with each other, so how to consider affinity network of ideas, and create a much more open software for sharing and communication, working together. Also, there is highly important local leadership – which can change over the lifetime of the project: from managing a team to dealing with technology. One of their participants, who is a plumber, noticed that in heavy rain events the rubbish is swept to the local river, and took his plumbing students to learn about water issues through citizen science. dsc_1717.jpgAnother project that is known in citizen science is eBird which includes amazing data visualisations of species distribution, migration and recently machine vision that is being used. The scale is from 2002 – but over 370m sighting of 10,313 species. Loads of opportunities for people in the visualisation area. iNaturalist is a social network with 20k observation a day, with 1.4m users, and aiming for 50M by 2020. There are many projects. SciStarter, and Wildlabs.net as a place for opportunities to computer scientists. Major issues – for scientists – enough data, trustworthy data, and long-term citizen participation.dsc_1718.jpg

For citizens – learning and contributing, but then they want to be acknowledged and valued. For computer scientists – it gives an opportunity to contribute to issues that are important: privacy, managing data. Some of the things that we can think of: people – how to diversify and involve more people? data quality; project management; technology and tools; values and ethics; and policies – have some real bite in different parts of the world. For Jenny – want to see leveraging the skills of HCI and citizen science to advance both, and use our knowledge to mitigate the impacts of climate change and biodiversity loss. Alan Dix – the messiness of this data is putting challenges that are very valuable.

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DSC_1721.JPGCitizen Science in Swansea and the Gower Peninsular (Professor Geoff Proffitt  University of Swansea). Trained as a botanist and marine science. Worked in the Wetland Trust and set a nature reserve in Wales, and habitat restoration – digging holes and filling them with water. Worked in GCRF work in the Gambia, to carry out recording in people in estimating the carbon that is locked in the mangrove, as part of REDD++ funding and can lead to mangrove restoration.  Citizen science in Swansea – the type of work that is being carried out. e.g. Dan Forman works on Barn owl diet project – getting local active natural history groups and students who are examining the food and see the changes in the diet of owls. Military sites are acting as a nature reserve – e.g. in Castlemartin and that is evidence of the botany of the site. Another project is about coastal otter and diets – people are reporting on dead otters, siting of them alive, and got over 3500 records from across the UK. They are being restored and help in formulating coastal otter strategy for the UK. In the site of Cym Ivy, which is an area that is on by National Trust, there is a new salt marsh as a result of a breach in the sea wall. Since 2016, and collecting otter spraints and understanding diets – also use camera traps. Within a year there is a growing salt marsh with rapid changes. The National Trust are considering what they’ll do in other sites. They also running Bioblitzes in Swansea with 30-100 members of the public: it builds confidence, interest, and awareness. The Rosehill quarry in the centre of Swansea, it is being used as a site. There are also – Clearwing moths distribution – using traps that imitate the smell of a female and that attracts species. The information allows the recording of many observations. Another project is the Oriel Science and the Swansea Science Festival (7000 people attending). The Oriel Science is op up discovery events with a wide range of engagement across the sciences and engineering. Managing to reach out to people who are from areas that are usually not involved in science (high deprivation index). dsc_1723.jpgAnother researcher, Richard Unsworth, involved in marine aspects – seagrass project to record them and collect evidence globally. The Seagrass spotter includes 900 people in 64 countries that projects evidence with 2100 observation. There is evidence in different places. Projectseagrass.org and Seagrassspotter.org is allowing collecting and sharing data. The BTO also carry out data collection and there are projects in the area of Swansea. The university also has an SSSI nearby – Crymlyn Burrows.

Restoring habitats – there are lots of work that is inspired by it and the UN declare the next decade to focus on restoration. Logistics – recruiting people is through places where you meet people, link to existing networks, and helping to get volunteers through connections. It is challenging to get people involved in apps.

DSC_1724.JPGThe COASST Project (Professor Julia K. Parrish, Associate Dean, College of the Environment, University of Washington). COASST has been running for 19 years. Natural scientists – the science goes to scientific publications, and to decision making. We need to technology as a replacement of people, a way to play, a wall and disconnector. But let’s think of technology as an amplifier to connect to nature and community, it also can act as an extender of sense, patterns, and scale. Issues of Wellbeing, we need to extend from humans to Gaia – the planetary systems. Citizen Science is about science, community, education, and enjoyment. There are lots of goals of citizen science – she’s on the area of hand on. The usual view of science is about a process that starts with a hypothesis, then experiment, results and conclude – but there is the need to put in a discover of pattern and wonder before hypothesis and also bear witness. Coastal Observation focuses – monitoring dead bird. COASST – deconstruct science: evidence first, deduction second. Second Demystifying science – no jargon, explain the process. Using science – bear witness and take action. In the COASST programme there is a contract, to survey carcases of marine bird in a given area, collect the foot, standard measurements and digital information. Recording on paper is – because of economics, context (sun, water).

There is a process of identifying the bird according to the foot and other identifying. 950 monthly participants, 4700 people participate since inception. 33% of people are retired, and the economic means to be retired. Average age 51, 65% male. The training – only 50% of people that get into training know birds. As people collect more data they get better – over 70% accuracy and higher. There is also a seasonal pattern – after a year, most people know the about 85% get the correct answer. What are the high/low pattern over the year, and that is something that professional ornithologists don’t know and they develop a good concept of the yearly average,. Active people after a year – hands-on programmes retain people over a long time. With long term retention rates: asking new participants why they joined, and long term participants why they stayed. The new people are interested in birds, the environment. dsc_1731.jpgLong term is staying to be outdoor, to contribute to the science, and to the COASST programme. There is also an aspect of personal identity between new and long term participants. There are differences between people who are going alone and experience the data collection, and then there are people who are joining pairs – so they are going with multiple people (nexus person that goes with different people to the activities). We need to design for loners and for social connectors (nexus). The data provides a good understanding of yearly patterns. There are also die off events that happen and records. COASST help in climate impacts, harmful algal blooms, changes in predator distribution and much more. There is an ability to record a mass die-off event in St Paul Island. They back calculate how far carcasses will get to the beach and can estimate and model mortality, which was 60 to 70 times higher than normal. That led to Die-off alert, of just reporting people in Alaska – it’s a food source, and can’t collect eggs: important for local practices. DSC_1729.JPGThere are events of many events of the region – can see the large scale pattern over space and time. By looking at the temperature of above normal patterns and the heating in Alaska and you can see the impact of increased mortality of birds. There are impacts of science and people – impact on coastal communities in Alaska, and in Indian communities in Washington, and ocean acidification that harms mussels. Let’s think about technology as wellbeing: connect people to passion, creativity, allow people to learn, increase ownership and stewardship of the natural world, increase realization and help them to take action. Most people are curious, attached to a place, but a very small group of people want to become scientists – and people would fundraise for the project than the analysis, and they want to see the scientists doing the work. Not making everyone a scientist, but making everyone involved.

DSC_1733.JPGThe Wisdom of the online crowd – Citizen science with the Zooniverse (Dr. Helen Spiers, Biomedical Research Lead of the Zooniverse Platform,  Department of Astrophysics, University of Oxford). Coming from developmental epigenetics and started in 2016 and covering some of the work of the universe. Currently the development of mobile apps etc. Zooniverse started from the story of Big Data in many fields of science, and especially in astronomy – we need data curation and human pattern recognition. The story started with Galaxy Zoo. The algorithm of the time couldn’t provide morphological information of galaxies, as Kevin couldn’t calculate all the galaxies – but analysed 50,000 galaxies, and it became Galaxy Zoo. The project was successful – 70,000 classification per hours, but that allows to complete analysis in a matter of months instead of years. The data was of better quality than the expert could do – more eyes on each image. There are many scientific outputs from Galaxy Zoo, but also unknown unknowns – e.g. Hanny Voorwerp. That has moved into cells with electron microscopy (with Crick Institute). There is much data that need annotation – annotation tools that allow providing recognition of cell data. The volunteer data quality is as good as experts. This allows understanding the nuclei of different cells – it opens up the ability to new areas in biology. DSC_1734.JPGThe work of volunteers can form the basis for ML. 1.75m registered users, and projects across science, humanities, and supporting humanitarian efforts. The Zooniverse project builder allows the growth in the projects and supporting different types of source data and the types of activities that you can carry out with it. Challenges include the need to understand how to facilitate engagement and scientific efficiency and it provides an opportunity to learn across projects. Looked at the volunteers’ behaviour across 63 Zooniverse projects, but found out several things: artificial scarcity can be associated with engagement – in most projects that shows a peak at the start and then dropping to an activity. when the research team upload the data in each time when it was available on a weekly basis, it raised the interest in the project and provided multiple peaks. The lessons need to be learnt with caution. Some projects get into high participation inequality, and also age and gender bias and there is a tension between social inclusivity in contrast to scientific efficiency. There is a need to be inclusive in study design – e.g. a project about body organs and checking people anatomic knowledge – there was an aim to have a more inclusive reach. This is an unusual project: it’s about data collection and how it can be used in a different way. There is also exclusivity – specialised crowds can provide specific skills – when there are needed expertise or local knowledge, or maybe you want task naivety crowd. Zooniverse also offer a linkage between ML and human contribution. e.g. throwing images that are surely not relevant, and asking the crowd to classify only those that the computer wasn’t confident about. Algorithms and volunteers offer different behaviour. There is also a lot of value in algorithmic diversity – computers can also be used to create engaging tasks, but need to be careful about using it – removing images without anything, reduced engagement in the project (the Snapshot Safari example of removing all the blanks which reduced engagement). There is an ethical issue – are you wasting people time. The future of Zooniverse is about Human:Computer collaboration, need to have a smart subject assignment – allocating tasks and ensure an engaging experience and combining modes of citizen science – interoperable systems, giving feedback. The communities are changing – e.g. DSC_1735.JPGGalaxy Zoo is very proactive which meet offline, and there are questions about the nature and characteristics of communities. Don’t waste people time – the commitment is to ensure scientific efficiency and find other ways of engaging people in an interesting way. The issue of inclusivity – how is the Zooniverse management team gatekeep the community? there is a review process, and also sharing it with volunteers who are happy to review project application – 50,000 repeat volunteers, which are self-selected, who provide feedback and say if the project is suitable for the Zooniverse. Very few of the projects that are scientifically valid, failed. There was a project that was thrown out – about facial characteristics. There is a different review of scientific relevance.

Extreme Citizen Science Professor Muki Haklay, Professor of
Geographical Information Science and co-director of the Extreme Citizen
Science group, Department of Geography, UCL

DSC_1736.JPGCitizen Science Inquiry: Contemporary Approaches (Professor Eileen Scanlon, Open University) talking about citizen science enquiry – the nQuire team. Citizen science inquiry is the general approach to it. Eileen sees citizen science as a way to enthuse people in science and engage them. There is a lot of things that were talks: scientific literacy and wider STEM learning. Then there are issues of volunteers and how they are involved in data collection and analysis. From the point of history, citizen science goes back to the 17th C and been going for a long time. Modern citizen science provides new ways of engaging online – such as Zooniverse or iNaturalist. At the Open University, they’ve done nQuire-it, iSpot and Situ8 that is about annotating physical places.dsc_1737.jpg First, they look at the personal inquiry project – inquiry-based learning across formal and informal settings (www.pi-project.ac.uk). Was coming from an interest in digital technology and learning, and was focusing on 12-16 old, and were searching for outdoor settings that allow students to link to issues that are relevant to them and within their areas. Inquiry-based learning is appearing in the education literature, and scaffolding the process can help people to learn through inquiry. It can be used through different stages in the learning process. Personalisation is important, but you do need to have a limitation – e.g. you can’t work with teenagers about issues of their daily diet: sharing it with other people in their immediate social circle is problematic. In Milton Keynes and Northampton, they manage to engage students in the investigation of urban heat islands. The work is summarised in the book “orchestrating inquiry learning”. The work was developed within the formal approach. At the same time, work by Vickie Curtis lead to the analysis of online citizen science (in her book). dsc_1738.jpgThe research on who engage and to what extent, you get a different picture – Vickie was a participant observer, and in Foldit where the science was very high – the participants were interested in games. The positioning of the people who participate in citizen science. Next, they worked with Nominet Trust and developed nQuire-it – so using smartphone sensors. They’ve done a co-design of an informal system with students and created different ways of exploring the world. The investigations were called “missions” – develop things that the participants are personally interested in and also to the book on “Citizen Inquiry” – citizen science + collaborative inquiry learning + crowdsourcing. The way that they are seen Citizen Inquiry is to think about a link between inquiry learning and citizen science. Trying to think about how these things are brought together. Another project, by Jess Carr is looking about representing ‘publics’ – e.g. developing the workaround advocacy research groups. In inclusive research is part of the work. By the collaboration with the BBC lead to extend citizen inquiry to allow mass surveys (in http://www.nquire.org.uk) which include confidential survey missions, and open social missions. The BBC helped in developing a joint platform and different missions were developed – from survey of sleep pattern, to work with FutureLearn, and to an authoring tool. One work that is currently happening is in the Forst 404 Experiment about different environmental sound and running a podcast. There are issues with owns data and ethical questions about such projects. There are also other activities – such as iSpot and Treezilla. Citizen science inquiry can provide about participation and personally relevant research. Evaluating learning is tricky. Open questions include how can citizen science projects raise interest in STEM and provide appealing science learning? Can citizen science have an impact on the participant’s identity – allow them to identify roles for themselves in the practice of science? The reputation system of iSpot is especially valuable (the Zookeys paper cover that).

The speakers had a common panel, exploring what are the new ideas and agendas that are emerging from the day. point of impact on the world, and science in general and can help; social inclusion that came in both days; growth in computing in challenges; including computers as participants; education;

From today – how we maximise the impact of the data that we produce and that we’re going to produce? How can we take the datasets that are being produced and how they are being used? Data can be repackaged and reused. Another thing is education and there is no impression of getting young people engaged with these types of project – informal involvement and practical science activity. There is a certain “flight from science” and we need to consider how to involve the youth into it. There are both men and women, and there are people who are leaving education (e.g. young males in the UK). There are lessons in museums that engage with citizen science: learning citizen science, DITOs, and the awareness of Ecsite and Aztec. From COASST there are issues about finding older adults because of the year-long needs of the project, but they do have cross-generation participation. There are also issues about the integration of citizen science and inquiry into education – but we need to be articulate about what we’re doing within citizen science. There is also a lot of data on different platforms, and linkage between seagrass and specific birds that are eating it and direct connection is something that ecologists don’t know how to link. There are also people who collected data over a long time and the data and in some cases, this is not shared. There is plenty of information on hatching and egg laying day when they are a very long time, but it is in small notebooks that need to be digitised and used – and this information needs to be collected, as otherwise will be lost. There are issues of a lot of unexpected information within environmental information – examples include the ozone layer reprocessing, or that looking at old records or mass die-off events are showing information that was not known before. This is an issue that we might want ML and other methods of uncommon analysis to provide us. There are also cultural identity issues – about the role of experts and the disrespect of experts: is citizen science are amateur scientists? Or are they are not like experts? Choice c – and there is a wider distribution. Mass mortality events that started in early 2000 made the front page, and right-leaning business groups wanted to hear about it as much as to conservation groups. The business groups was a demonstration of local people collecting information and managing their place. Citizen science is not left or right leaning and it gives a lot of communities to hold information and interpret it – that’s the democratisation. We are not doing the deficit model – bringing people to be like us. But is it useful to link citizen science to political debate? Citizen science can take out the politics and focus on the fact – using an agreed measurement and approach that is societally agreed. In the water projects, people became more educated about the situation so they could lobby the officials to act. There is also an opportunity to bring it the data as a way to challenge difference: it is about empowerment and not about right or wrong. Back to the engagement of kids – the ethical assumptions: if there is data collection then the parent is responsible for the data? In the OU system, there is a concern and that need to be addressed and it is an issue in school settings. There are also options for managing data by the teachers and let students deal with data, pictures, etc. It is tricky on how to engage in advance with parents and children – but it can lead to impacts on parents, too. There are also issues – e.g. reporting about the impact of pollution on an ecological site, and then claims that the site is spoiled so it can be used for development. There are lessons to be learned from Citizen Science: Theory and Practice special issue on ethics, and the Citizen Science Association ethics working groups. The ideas that are emerging and resources that are coming along is to find new questions.

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