23 February, 2014
After a day of ‘listening‘, and a day of ‘talking‘, the final day of the citizen cyberscience summit brought ‘doing‘ to the summit. Although the art installation on the second day of the summit would clearly fall into the ‘doing’ category, participation in the installation was mostly in the ‘contributory’ form: after summit participants handed over the citizen (cyber)science objects, the decisions on how to use them in the installation were left to the artist, Leni Diner Dothan.
The day started with setting up desks for each of the hackday challenges. The challenges ranged from Synthetic Biology to Citizen Science & Big Data. While those interested in assisting the challenge proposers to develop their ideas set to work, a set of shorter talks and discussions continued - including a set of impromptu 5 minute talks in an unconference session. Despite the compactness of the session, it was clear that people are responding to themes that appeared in the two previous days of the summit. For example, Jeff Parsons addressed the common ‘how good is the data from citizen science?‘ question, which made an appearance in several talks. Jeff pointed to his Nature paper that ‘easier citizen science is better‘. Francois Grey started the conversation which he is developing with Creative Commons and Open Knowledge Foundation about the relationships between Open Science and Citizen Science, asking if there should be an ‘Open Citizen Science’.
Geographical citizen Science was at the heart of several talks that explored the links between mapping technologies, DIY sensors and citizen science. The summit benefited from the participation of several early career researchers who were funded to visit UCL as part of the COST ENERGIC scientific network. The exchange of knowledge that is not only enabled through networks, but also through the communities of practice in DIY electronics or VGI, was clearly visible. One talk discussed using Public Laboratory technologies in schools in Germany and in another talk about using those technologies in Jerusalem. Another example of such links was demonstrated in the collaboration between Chinese and UK-based students to build a new DIY microscope.
Personally, the re-appearance of my ‘levels of participation in citizen science‘ classification is both satisfying (someone found it useful!) and fascinating, as each use of it illustrated a different interpretation and understanding of it. The levels are fuzzy and open to interpretation, so these discussions help the process of understanding what should be included in each category, and how the different levels map onto a specific project or activity.
The final talk by Jeff Howe – who coined the term crowdsourcing - discussed the way new ideas emerge from allowing a large group of people to participate in solving problems as this can open up a wider set of skills and expertise. He noted that in many cases, the success of large collaborations comes from a ‘gift’, which is creating a system or a service that provides something that people want, or which can help them to do what interests them. Or, as he phrased it, ‘ask not what your community can do for you, but what you can do for your community‘.
An example of some of the issues that Jeff covered was provided during the presentations from the hackday. As in the previous summit, we carefully measured the applause from the audience with a noise meter, to ascertain the activity that the participants in the summit liked the most. This time, it was the development of a bio-sensor that can be integrated into textiles. This challenge was led by Paula Nerlich, who is studying at the Edinburgh College of Art, showing that citizen science ideas can come from outside the traditional scientific disciplines (image by Cindy Regalado).
To get a better sense of the atmosphere, you can find plenty of interviews on the ‘Citizens of Science’ podcast board which explores the needs of the citizen science community.
Since we first began to organise the summit almost a year ago, I have had a lingering concern that the summit would not fulfill the expectations and the success of the previous one. Once the summit ended, I was more relaxed about this – I noticed many new connections being made, and new ideas discovered by participants. Now it is time to sit back and watch what will come out of these!
21 February, 2014
The second day of the summit (see my reflections on the first day) started with an unplanned move to the Darwin Lecture Theatre of UCL. This was appropriate, as the theatre is sited in a place where Charles Darwin used to live, and he is mentioned many times as a citizen scientist. Moreover, the unplanned move set the tone for a day which paid more attention to DIY science.
We started with a vision for the future of citizen science by Rick Bonney from Cornell Lab of Ornithology in which he highlighted how important it is to keep growing the field and bring together different approaches to citizen science to save the world. This was followed by a panel that explored the experiences and wishes of citizen scientists themselves – from participant in Zooniverse, to DIY electronic and environmental justice applications of citizen science (image from Daniel Lombrana Glez). The panel demonstrated the level of interest and the commitment that people that are engaged in citizen science have, and that it is taken seriously by the participants. It also gave a glimpse to the empowerment aspect of citizen science.
In my opening, I have pressed the message that while the first day of the summit involve a lot of listening, the second day is about talking with one another and sharing ideas, in order to move to doing in the third day. In fact, this was not needed, and throughout the day many conversations were happening in workshops, in the main meeting area of the conference and during the coffee and tea breaks.
Another aspects that gave a different atmosphere to the day was the work of Leni Diner-Dothan. Leni is studying at UCL Slade School, and accepted a request to create an art installation during the summit. After collecting both operational and defunct items of citizen science and developing the concept, the work commenced during the day.
With the help of the technicians from my own department, she developed the ‘citizen cyberscience nightmare wall‘ which have pieces of citizen cyberscience embedded in concrete with a reliquary. It is a thought provoking and fascinating piece of art, and I hope to write about it more soon.
The citizen science cafe that closed the day open up thematic conversation, and I encountered discussions between related projects that the summit provided an opportunity for.
Now, it’s time to move to the doing – let’s see what ideas will come tomorrow…
19 February, 2014
The Citizen Cyberscience Summit that will be running in London this week sparked the interest of the producers of BBC World Service ‘Click’ programme, and it was my first experience of visiting BBC Broadcasting House – about 15 minutes walk from UCL.
Here is the clip from the programme that covers the discussion about the summit and Extreme Citizen Science
More information is provided in the Citizens of Science podcast - where myself and the other organisers discuss and preview the summit. That is an opportunity to recommend the other podcasts that can be found in the series.
8 July, 2013
The term ‘Citizen Science’ is clearly gaining more recognition and use. It is now get mentioned in radio and television broadcasts, social media channels as well as conferences and workshops. Some of the clearer signs for the growing attention include discussion of citizen science in policy oriented conferences such as UNESCO’s World Summit on Information Society (WSIS+10) review meeting discussion papers (see page ), or the Eye on Earth users conference (see the talks here) or the launch of the European Citizen Science Association in the recent EU Green Week conference.
Another aspect of the expanding world of citizen science is the emerging questions from those who are involved in such projects or study them about the efficacy of the term. As is very common with general terms, some reflections on the accuracy of the term are coming to the fore – so Rick Bonney and colleagues suggest to use ‘Public Participation in Scientific Research‘ (significantly, Bonney was the first to use ‘Citizen Science’ in 1995); Francois Grey coined Citizen Cyberscience to describe projects that are dependent on the Internet; recently Chris Lintott discussed some doubts about the term in the context of Zooniverse; and Katherine Mathieson asks if Citizen Science is just a passing fad. In our own group, there are also questions about the correct terminology, with Cindy Regalado suggestions to focus on ‘Publicly Initiated Scientific Research (PIScR)‘, and discussion on the meaning of ‘Extreme Citizen Science‘.
One way to explore what is going on is to consider the evolution of the ‘hype’ around citizen science through ‘Gartner’s Hype Cycle‘ which can be seen as a way to consider the way technologies are being adopted in a world of rapid communication and inflated expectations from technologies. leaving aside Gartner own hype, the story that the model is trying to tell is that once a new approach (technology) emerges because it is possible or someone reconfigured existing elements and claim that it’s a new thing (e.g. Web 2.0), it will go through a rapid growth in terms of attention and publicity. This will go on until it reaches the ‘peak of inflated expectations’ where the expectations from the technology are unrealistic (e.g. that it will revolutionize the way we use our fridges). This must follow by a slump, as more and more failures come to light and the promises are not fulfilled. At this stage, the disillusionment is so deep that even the useful aspects of the technology are forgotten. However, if it passes this stage, then after the realisation of what is possible, the technology is integrated into everyday life and practices and being used productively.
So does the hype cycle apply to citizen science?
If we look at Gartner cycle from last September, Crowdsourcing is near the ‘peak of inflated expectations’ and some descriptions of citizen science as scientific crowdsourcing clearly match the same mindset.
There is a growing evidence of academic researchers entering citizen science out of opportunism, without paying attention to the commitment and work that is require to carry out such projects. With some, it seems like that they decided that they can also join in because someone around know how to make an app for smartphones or a website that will work like Galaxy Zoo (failing to notice the need all the social aspects that Arfon Smith highlights in his talks). When you look around at the emerging projects, you can start guessing which projects will succeed or fail by looking at the expertise and approach that the people behind it take.
Another cause of concern are the expectations that I noticed in the more policy oriented events about the ability of citizen science to solve all sort of issues – from raising awareness to behaviour change with limited professional involvement, or that it will reduce the resources that are needed for activities such as environmental monitoring, but without an understanding that significant sustained investment is required – community coordinator, technical support and other aspects are needed here just as much. This concern is heightened by statements that promote citizen science as a mechanism to reduce the costs of research, creating a source of free labour etc.
On the other hand, it can be argued that the hype cycle doesn’t apply to citizen science because of history. Citizen science existed for many years, as Caren Cooper describe in her blog posts. Therefore, conceptualising it as a new technology is wrong as there are already mechanisms, practices and institutions to support it.
In addition, and unlike the technologies that are on Gartner chart, academic projects within which citizen science happen benefit from access to what is sometime termed patient capital without expectations for quick returns on investment. Even with the increasing expectations of research funding bodies for explanations on how the research will lead to an impact on wider society, they have no expectations that the impact will be immediate (5-10 years is usually fine) and funding come in chunks that cover 3-5 years, which provides the breathing space to overcome the ‘through of disillusionment’ that is likely to happen within the technology sector regarding crowdsourcing.
And yet, I would guess that citizen science will suffer some examples of disillusionment from badly designed and executed projects – to get these projects right you need to have a combination of domain knowledge in the specific scientific discipline, science communication to tell the story in an accessible way, technical ability to build mobile and web infrastructure, understanding of user interaction and user experience to to build an engaging interfaces, community management ability to nurture and develop your communities and we can add further skills to the list (e.g. if you want gamification elements, you need experts in games and not to do it amateurishly). In short, it need to be taken seriously, with careful considerations and design. This is not a call for gatekeepers , more a realisation that the successful projects and groups are stating similar things.
Which bring us back to the issue of the definition of citizen science and terminology. I have been following terminology arguments in my own discipline for over 20 years. I have seen people arguing about a data storage format for GIS and should it be raster or vector (answer: it doesn’t matter). Or arguing if GIS is tool or science. Or unhappy with Geographic Information Science and resolutely calling it geoinformation, geoinformatics etc. Even in the minute sub-discipline that deals with participation and computerised maps that are arguments about Public Participation GIS (PPGIS) or Participatory GIS (PGIS). Most recently, we are debating the right term for mass-contribution of geographic information as volunteered geographic information (VGI), Crowdsourced geographic information or user-generated geographic information.
It’s not that terminology and precision in definition is not useful, on the contrary. However, I’ve noticed that in most cases the more inclusive and, importantly, vague and broad church definition won the day. Broad terminologies, especially when they are evocative (such as citizen science), are especially powerful. They convey a good message and are therefore useful. As long as we don’t try to force a canonical definition and allow people to decide what they include in the term and express clearly why what they are doing is falling within citizen science, it should be fine. Some broad principles are useful and will help all those that are committed to working in this area to sail through the hype cycle safely.
The talk, which is titled ‘Science for everyone by everyone – the re-emergence of citizen science‘ covered the area of citizen science and explained what we are trying to achieve within the Extreme Citizen Science research group.
Because the lunch hour lectures are open to all, I preferred not to assume any prior knowledge of citizen science (or public participation in scientific research) and start by highlighting that public participation in scientific research is not new. After a short introduction to the history and to the fact that many people are involved in scientific activities in their free time, from bird watching to weather or astronomical observations and that this never stopped, there is a notable difference in the attention that is paid to citizen science in recent years.
Therefore, I covered the trends in education and technology that are ushering in a new era of citizen science – access to information through the internet, use of location aware mobile devices, growth in social knowledge creation web-based systems, increased in education and the ability to deal with abstract ideas (Flynn effect is an indicator of this last point). The talk explored the current trends and types of citizen science, and demonstrate a model for extreme citizen science, in which any community, regardless of their literacy, can utilise scientific methods and tools to understand and control their environment. I have used examples of citizen science activities from other groups at UCL, to demonstrate the range of topics, domains and activities that are now included in this area.
The talk was recorded, and is available on YouTube and below
5 December, 2012
Recently, I attended a meeting with people from a community that is concerned with vibration and noise caused by a railway near their homes. We have discussed the potential of using citizen science to measure the vibrations that pass the sensory threshold and that people classify as unpleasant, together with other perceptions and feeling about these incidents. This can form the evidence to a discussion with the responsible authorities to see what can be done.
As a citizen science activity, this is not dissimilar from the work carried out around Heathrow to measure the level of noise nuisance or air pollution monitoring that ExCiteS and Mapping for Change carried out in other communities.
In the meetings, the participants felt that they need to emphasise that they are not against the use of the railway or the development of new railway links. Like other groups that I have net in the past, they felt that it is important to emphasise that their concern is not only about their locality – in other words, this is not a case of ‘Not In My Back Yard’ (NIMBY) which is the most common dismissal of local concerns. The concern over NIMBY and citizen science is obvious one, and frequently come up in questions about the value and validity of data collected through this type of citizen science.
During my masters studies, I was introduced to Maarten Wolsink (1994) analysis of NIMBY as a compulsory reading in one of the courses. It is one of the papers that I keep referring to from time to time, especially when complaints about participatory work and NIMBY come up.
Inherently, what Wolsink is demonstrating is that the conceptualisation of the people who are involved in the process as selfish and focusing on only their own area is wrong. Through the engagement with environmental and community concerns, people will explore issues at wider scales and many time will argue for ‘Not in Anyone’s Back Yard’ or for a balance between the needs of infrastructure development and their own quality of life. Studies on environmental justice also demonstrated that what the people who are involved in such activities ask for are not narrow, but many times mix aspects of need for recognition, expectations of respect, arguments of justice, and participation in decision-making (Schlosberg 2007).
In other words, the citizen science and systematic data collection are a way for the community to bring to the table evidence that can enhance arguments beyond NIMBY, and while it might be part of the story it is not the whole story.
For me, these interpretations are part of the reason that such ‘activism’-based citizen science should receive the same attention and respect as any other data collection, most notably by the authorities.
Wolsink, M. (1994) Entanglement of Interests and Motives: Assumptions Behind the NIMBY-Theory on Facility Siting, Urban Studies, 31(6), pp. 851-866.
Scholsberg, D. (2007) Defining Environmental Justice: Theories, Movements, and Nature. Oxford University Press, 2007
8 August, 2012
On the 4th and 5th August, Portland, OR, was the gathering place for 300 participants that came to the workshop on Public Participation in Scientific Research. The workshop was timed just before the annual meeting of the Ecological Society of America, and therefore it was not surprising that the workshop focused on citizen science projects that are linked to ecology and natural environments monitoring. These projects are some of the longest running citizen science activities, that are now gaining recognition and attention.
The workshop was organised as a set of thematic talks interlaced with long poster sessions. This way, the workshop included over 180 presentations in a day and a half. That set the scene for a detailed discussion at the end of the second day, to explore what is the way forward to the field of PPSR/Citizen Science/Civic Science etc., with attention to sharing lessons, developing and supporting new activities, considering codes of ethics, etc.
I presented the last talk of the workshop, describing Extreme Citizen Science and arguing for the potential of public participation to go much deeper in terms of engagement. The presentation is provided below, together with an interview that was conducted with me shortly after it.
And the interview,
The London Citizen Cyberscience Summit ran in the middle of February, from 16th (Thursday) to 18th (Saturday). It marked the launch of the UCL Extreme Citizen Science (ExCiteS) group, while providing an opportunity for people who are interested in different aspects of citizen science to come together, discuss, share ideas, consider joint projects and learn from other people. The original idea for the summit, when the first organisational meeting took place in October last year, was to set a programme that would include academics who research citizen science or develop citizen science projects; practitioners and enthusiasts who are developing technologies for citizen science activities; and people who are actively engaged in citizen science.Therefore, we included a mix of talks, workshops and hack days and started approaching speakers who would cover the range of interests, backgrounds and knowledge.
The announcement about the summit came out only in late December, so it was somewhat surprising to see the level of interest in the topic of citizen science. Considering that the previous summit, in 2010, attracted about 60 or 70 participants, it was pleasing to see that the second summit attracted more than 170 people.
To read about what happened in the summit there is plenty of material online. Nature news reported it as ‘Citizen science goes extreme‘. The New Scientist blog post discussed the ‘Intelligent Maps’ project of ExCiteS in ‘Interactive maps help pygmy tribes fight back‘, which was also covered by the BBC World Service Newshour programme (around 50 minutes in) and the Canadian CBC Science Shift programme. Le Monde also reported on ‘Un laboratoire de l’extrême‘.
Another report in New Scientist focused on the Public Laboratory for Open Technology and Science (PLOTS) development of a thermal flashlight in ‘Thermal flashlight “paints” cold rooms with colour‘. The China Dialogue ‘Scientists and Citizens‘ provided a broader review of the summit.
In terms of blogs, there are summaries on the GridCast blog (including some video interviews), and a summary by one of the speakers, Andrea Wiggins, of day 1, day 2 and day 3. Nicola Triscott from the Arts Catalyst provides another account of the summit and her Arctic Perspective Initiative linkage. Another participant, Célya Gruson-Daniel, discussed the summit in French at MyScienceWork, which also provided a collection of social media from the first day at http://storify.com/mysciencework/london-citizen-cyberscience-summit-16-18th-februar.
The talks are available to view again on the LiveStream account of ExCiteS at http://www.livestream.com/excites and there are also summaries on the ExCiteS blog http://uclexcites.wordpress.com/ and on the conference site http://cybersciencesummit.org/blog/ . Flickr photos from MyScienceWork and UCL Engineering (where the image on the right is from) are also available.
For me, several highlights of the conference included the impromptu integration of different projects during the summit. Ellie D’Hondt and Matthias Stevens from BrusSense and NoiseTube used the opportunity of the PLOTS balloon mapping demonstration to extend it to noise mapping; Darlene Cavalier from SciStarter discussed with the Open Knowledge Foundation people how to use data about citizen science projects; and the people behind Xtribe at the University of Rome considered how their application can be used for Intelligent Maps – all these are synergies, new connections and new experimentation that the summit enabled. The enthusiasm of people who came to the summit contributed significantly to its success (as well as the hard work of the ExCiteS team).
Especially interesting, because of the wide-ranging overview of examples and case studies, is how the activity is conceptualised in different ways across the spectrum of DIY citizen science to structured observations that are managed by professional scientists. This is also apparent in the reports about the summit. I have commented in earlier blog posts about the need to understand citizen science as a different way of producing scientific knowledge. What might be helpful is a clear ‘code of ethics’ or ‘code of conduct’ for scientists who are involved in such projects. As Francois Taddei highlighted in his talk at the summit, there is a need to value the shared learning among all the participants, and not to keep the rigid hierarchies of university academics/public in place. There is also a need to allow for the creativity, exploration and development of ideas that we have seen during the summit to blossom – but only happen when all the sides that are involved in the process are open to such a process.
The previous post focused on citizen science as participatory science. This post is discussing the meaning of this differentiation. It is the final part of the chapter that will appear in the book:
The typology of participation can be used across the range of citizen science activities, and one project should not be classified only in one category. For example, in volunteer computing projects most of the participants will be at the bottom level, while participants that become committed to the project might move to the second level and assist other volunteers when they encounter technical problems. Highly committed participants might move to a higher level and communicate with the scientist who coordinates the project to discuss the results of the analysis and suggest new research directions.
This typology exposes how citizen science integrates and challenges the way in which science discovers and produces knowledge. Questions about the way in which knowledge is produced and truths are discovered are part of the epistemology of science. As noted above, throughout the 20th century, as science became more specialised, it also became professionalised. While certain people were employed as scientists in government, industry and research institutes, the rest of the population – even if they graduated from a top university with top marks in a scientific discipline – were not regarded as scientists or as participants in the scientific endeavour unless they were employed professionally to do so. In rare cases, and following the tradition of ‘gentlemen/women scientists’, wealthy individuals could participate in this work by becoming an ‘honorary fellow’ or affiliated to a research institute that, inherently, brought them into the fold. This separation of ‘scientists’ and ‘public’ was justified by the need to access specialist equipment, knowledge and other privileges such as a well-stocked library. It might be the case that the need to maintain this separation is a third reason that practising scientists shy away from explicitly mentioning the contribution of citizen scientists to their work in addition to those identified by Silvertown (2009).
However, similarly to other knowledge professionals who operate in the public sphere, such as medical experts or journalists, scientists need to adjust to a new environment that is fostered by the Web. Recent changes in communication technologies, combined with the increased availability of open access information and the factors that were noted above, mean that processes of knowledge production and dissemination are opening up in many areas of social and cultural activities (Shirky 2008). Therefore, some of the elitist aspects of scientific practice are being challenged by citizen science, such as the notion that only dedicated, full-time researchers can produce scientific knowledge. For example, surely it should be professional scientists who can solve complex scientific problems such as long-standing protein-structure prediction of viruses. Yet, this exact problem was recently solved through a collaboration of scientists working with amateurs who were playing the computer game Foldit (Khatib et al. 2011). Another aspect of the elitist view of science can be witnessed in interaction between scientists and the public, where the assumption is of unidirectional ‘transfer of knowledge’ from the expert to lay people. Of course, as in the other areas mentioned above, it is a grave mistake to argue that experts are unnecessary and can be replaced by amateurs, as Keen (2007) eloquently argued. Nor is it suggested that, because of citizen science, the need for professionalised science will diminish, as, in citizen science projects, the participants accept the difference in knowledge and expertise of the scientists who are involved in these projects. At the same time, the scientists need to develop respect towards those who help them beyond the realisation that they provide free labour, which was noted above.
Given this tension, the participation hierarchy can be seen to be moving from a ‘business as usual’ scientific epistemology at the bottom, to a more egalitarian approach to scientific knowledge production at the top. The bottom level, where the participants are contributing resources without cognitive engagement, keeps the hierarchical division of scientists and the public. The public is volunteering its time or resources to help scientists while the scientists explain the work that is to be done but without expectation that any participant will contribute intellectually to the project. Arguably, even at this level, the scientists will be challenged by questions and suggestions from the participants and, if they do not respond to them in a sensitive manner, they will risk alienating participants. Intermediaries such as the IBM World Community Grid, where a dedicated team is in touch with scientists who want to run projects and a community of volunteered computing providers, are cases of ‘outsourcing’ the community management and thus allowing, to an extent, the maintenance of the separation of scientists and the public.
As we move up the ladder to a higher level of participation, the need for direct engagement between the scientist and the public increases. At the highest level, the participants are assumed to be on equal footing with the scientists in terms of scientific knowledge production. This requires a different epistemological understanding of the process, in which it is accepted that the production of scientific insights is open to any participant while maintaining scientific standards and practices such as systematic observations or rigorous statistical analysis to verify that the results are significant. The belief that, given suitable tools, many lay people are capable of such endeavours is challenging to some scientists who view their skills as unique. As the case of the computer game that helped in the discovery of new protein formations (Khatib et al. 2011) demonstrated, such collaboration can be fruitful even in cutting-edge areas of science. However, it can be expected that the more mundane and applied areas of science will lend themselves more easily to the fuller sense of collaborative science in which participants and scientists identify problems and develop solutions together. This is because the level of knowledge required in cutting-edge areas of science is so demanding.
Another aspect in which the ‘extreme’ level challenges scientific culture is that it requires scientists to become citizen scientists in the sense that Irwin (1995), Wilsdon, Wynne and Stilgoe (2005) and Stilgoe (2009) advocated (Notice Stilgoe’s title: Citizen Scientists). In this interpretation of the phrase, the emphasis is not on the citizen as a scientist, but on the scientist as a citizen. It requires the scientists to engage with the social and ethical aspects of their work at a very deep level. Stilgoe (2009, p.7) suggested that, in some cases, it will not be possible to draw the line between the professional scientific activities, the responsibilities towards society and a fuller consideration of how a scientific project integrates with wider ethical and societal concerns. However, as all these authors noted, this way of conceptualising and practising science is not widely accepted in the current culture of science.
Therefore, we can conclude that this form of participatory and collaborative science will be challenging in many areas of science. This will not be because of technical or intellectual difficulties, but mostly because of the cultural aspects. This might end up being the most important outcome of citizen science as a whole, as it might eventually catalyse the education of scientists to engage more fully with society.
27 November, 2011
This post continues to the theme of the previous one, and is also based on the chapter that will appear next year in the book:
The post focuses on the participatory aspect of different Citizen Science modes:
Against the technical, social and cultural aspects of citizen science, we offer a framework that classifies the level of participation and engagement of participants in citizen science activity. While there is some similarity between Arnstein’s (1969) ‘ladder of participation’ and this framework, there is also a significant difference. The main thrust in creating a spectrum of participation is to highlight the power relationships that exist within social processes such as urban planning or in participatory GIS use in decision making (Sieber 2006). In citizen science, the relationship exists in the form of the gap between professional scientists and the wider public. This is especially true in environmental decision making where there are major gaps between the public’s and the scientists’ perceptions of each other (Irwin 1995).
In the case of citizen science, the relationships are more complex, as many of the participants respect and appreciate the knowledge of the professional scientists who are leading the project and can explain how a specific piece of work fits within the wider scientific body of work. At the same time, as volunteers build their own knowledge through engagement in the project, using the resources that are available on the Web and through the specific project to improve their own understanding, they are more likely to suggest questions and move up the ladder of participation. In some cases, the participants would want to volunteer in a passive way, as is the case with volunteered computing, without full understanding of the project as a way to engage and contribute to a scientific study. An example of this is the many thousands of people who volunteered to the Climateprediction.net project, where their computers were used to run global climate models. Many would like to feel that they are engaged in one of the major scientific issues of the day, but would not necessarily want to fully understand the science behind it.
Therefore, unlike Arnstein’s ladder, there shouldn’t be a strong value judgement on the position that a specific project takes. At the same time, there are likely benefits in terms of participants’ engagement and involvement in the project to try to move to the highest level that is suitable for the specific project. Thus, we should see this framework as a typology that focuses on the level of participation.
At the most basic level, participation is limited to the provision of resources, and the cognitive engagement is minimal. Volunteered computing relies on many participants that are engaged at this level and, following Howe (2006), this can be termed ‘crowdsourcing’. In participatory sensing, the implementation of a similar level of engagement will have participants asked to carry sensors around and bring them back to the experiment organiser. The advantage of this approach, from the perspective of scientific framing, is that, as long as the characteristics of the instrumentation are known (e.g. the accuracy of a GPS receiver), the experiment is controlled to some extent, and some assumptions about the quality of the information can be used. At the same time, running projects at the crowdsourcing level means that, despite the willingness of the participants to engage with a scientific project, their most valuable input – their cognitive ability – is wasted.
The second level is ‘distributed intelligence’ in which the cognitive ability of the participants is the resource that is being used. Galaxy Zoo and many of the ‘classic’ citizen science projects are working at this level. The participants are asked to take some basic training, and then collect data or carry out a simple interpretation activity. Usually, the training activity includes a test that provides the scientists with an indication of the quality of the work that the participant can carry out. With this type of engagement, there is a need to be aware of questions that volunteers will raise while working on the project and how to support their learning beyond the initial training.
The next level, which is especially relevant in ‘community science’ is a level of participation in which the problem definition is set by the participants and, in consultation with scientists and experts, a data collection method is devised. The participants are then engaged in data collection, but require the assistance of the experts in analysing and interpreting the results. This method is common in environmental justice cases, and goes towards Irwin’s (1995) call to have science that matches the needs of citizens. However, participatory science can occur in other types of projects and activities – especially when considering the volunteers who become experts in the data collection and analysis through their engagement. In such cases, the participants can suggest new research questions that can be explored with the data they have collected. The participants are not involved in detailed analysis of the results of their effort – perhaps because of the level of knowledge that is required to infer scientific conclusions from the data.
Finally, collaborative science is a completely integrated activity, as it is in parts of astronomy where professional and non-professional scientists are involved in deciding on which scientific problems to work and the nature of the data collection so it is valid and answers the needs of scientific protocols while matching the motivations and interests of the participants. The participants can choose their level of engagement and can be potentially involved in the analysis and publication or utilisation of results. This form of citizen science can be termed ‘extreme citizen science’ and requires the scientists to act as facilitators, in addition to their role as experts. This mode of science also opens the possibility of citizen science without professional scientists, in which the whole process is carried out by the participants to achieve a specific goal.
This typology of participation can be used across the range of citizen science activities, and one project should not be classified only in one category. For example, in volunteer computing projects most of the participants will be at the bottom level, while participants that become committed to the project might move to the second level and assist other volunteers when they encounter technical problems. Highly committed participants might move to a higher level and communicate with the scientist who coordinates the project to discuss the results of the analysis and suggest new research directions.