Gartner’s hype cycle and citizen science

Google Trends 'Citizen Science' (July 2013)
Google Trends ‘Citizen Science’ (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.

There are more academic conferences and publications that cover citizen science, a Google Plus community dedicated to citizen science with 1400 members, a clear trend in Google searches and so on.

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‘.

Gartner Hype Cycle

One way to  explore what is going on is to consider the evolution of the ‘hype’ around citizen science throughGartner’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.

Gartner 2012 Hype Cycle

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.


Spatial Data Infrastructures, Crowdsourcing and VGI

The Spatial Data Infrastructure Magazine ( is a relatively new e-zine dedicated to the development of spatial  data infrastructures around the world. Roger Longhorn, the editor of the magazine, conducted an email interview with me, which is now published.

In the interview, we are covering the problematic terminology used to describe a wider range of activities; the need to consider social and technical aspects as well as goals of the participants; and, of course, the role of the information that is produced through crowdsourcing, citizen science, VGI with spatial data infrastructures.

The full interview can be found here.


Citizen Science as Participatory Science

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:

Sui, D.Z., Elwood, S. and M.F. Goodchild (eds.), 2013. Crowdsourcing Geographic Knowledge. Berlin: Springer. Here is a link to freely downloadable version .

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 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.

Levels of Participation in Citizen Science

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.

GISRUK 2011 talk – Participatory GIS, Volunteered Geographic Information and Citizen Science

GIS Research UK (GISRUK) is a long running conference series, and the 2011 instalment was hosted by the University of Portsmouth at the end of April.

During the conference, I was asked to give a keynote talk about Participatory GIS. I decided to cover the background of Participatory GIS in the mid-1990s, and the transition to more advanced Web Mapping applications from the mid-2000s. Of special importance are the systems that allow user-generated content, and the geographical types of systems that are now leading to the generation of Volunteer Geographic Information (VGI).

The next part of the talk focused on Citizen Science, culminating with the ideas that are the basis for Extreme Citizen Science.

Interestingly, as in previous presentations, one of the common questions about Citizen Science came up. Professional scientists seem to have a problem with the suggestion that citizens are as capable as scientists in data collection and analysis. While there is an acceptance about the concept, the idea that participants can suggest problems, collect data rigorously and analyse it seems to be too radical – or worrying.

What is important to understand is that the ideas of Extreme Citizen Science are not about replacing the role of scientists, but are a call to rethink the role of the participants and the scientists in cases where Citizen Science is used. It is a way to consider science as a collaborative process of learning and exploration of issues. My own experience is that participants have a lot of respect for the knowledge of the scientists, as long as the scientists have a lot of respect for the knowledge and ability of the participants. The participants would like to learn more about the topic that they are exploring and are keen to know: ‘what does the data that I collected mean?’ At the same time, some of the participants can become very serious in terms of data collection, reading about the specific issues and using the resources that are available online today to learn more. At some point, they are becoming knowledgeable participants and it is worth seeing them as such.

The slides below were used for this talk, and include links to the relevant literature.

A postdoctoral position and 3 PhD studentships in Extreme Citizen Science

Following successful funding for the European Union FP7 EveryAware and the EPSRC Extreme Citizen Science activities, the department of Civil, Environmental and Geomatic Engineering at UCL is inviting applications for a postdoctoral position and 3 PhD studentships. Please note that these positions are open to students from any EU country.

These positions are in the ‘Extreme Citizen Science’ (ExCiteS) research group. The group’s activities focus on the theory, methodologies, techniques and tools that are needed to allow any community to start its own bottom-up citizen science activity, regardless of the level of literacy of the users. Importantly, Citizen Science is understood in the widest sense, including perceptions and views – so participatory mapping and participatory geographic information are integral parts of the activities.

The research themes that the group explores include Citizen Science and Citizen Cyberscience; Community and participatory mapping/GIS; Volunteered Geographic Information (OpenStreetMap, Green Mapping, Participatory GeoWeb); Usability of geographic information and geographic information technology, especially with non-expert users;  GeoWeb and mobile GeoWeb technologies that facilitate Extreme Citizen Science; and identifying scientific models and visualisations that are suitable for Citizen Science.

The positions that are opening now are part of an effort to extend Dr Jerome Lewis’ research with forest communities (see BBC Report and report on software development):

Research Associate in Extreme Citizen Science – a 2-year, postdoctoral research associate position commencing 1 May 2011.

The research associate will lead the development of an ‘Intelligent Map’ that allows non-literate users to upload data securely; and the system should allow the users to visualise their information with data from other users. Permissions need to be developed in accordance with cultural sensitivities. As uploaded data from multiple users sharing the same system increase over time, repeating patterns will begin to emerge that indicate particular environmental trends.

The role will also include some general project-management duties, guiding the PhD students who are working on the project. Travel to Cameroon to the forest communities that we are working with is necessary.

Complete details about this post and application procedure are available on the UCL jobs website.

PhD Studentship – understanding citizen scientists’ motivations, incentives and group organisation – a 3.5-year fully funded studentship. We are looking for applicants with a good honours degree (1st Class or 2:1 minimum), and an MA or MSc in anthropology, geography, sociology, psychology or related discipline. The applicant needs to be familiar with quantitative and qualitative research methods, and be able to work with a team that will include programmers and human-computer interaction experts who will design systems to be used in citizen science projects. Travel will be required as part of the project. A willingness to live for short periods in remote forest locations in simple lodgings, eating local food, will be necessary. French language skills are desirable.

The research itself will focus on motivations, incentives and understanding of the needs and wishes of participants in citizen science projects. We will specifically focus on engagement of non-literate people in such projects and need to understand how the process – from data collection to analysis – can be made meaningful and useful for their everyday life. The research will involve using quantitative methods to analyse large-scale patterns of engagement in existing projects, as well as ethnographic and qualitative study of participants. The project will include working with non-literate forest communities in Cameroon as well as marginalised communities in London.

Complete details about this post and application procedure are available on the UCL jobs website.

PhD Studentship in geographic visualisation for non-literate citizen scientists – a 3.5-year fully funded studentship. The applicant should possess a good honours degree (1st Class or 2:1 minimum), and an MSc in computer science, human-computer interaction, electronic engineering or related discipline. In addition, they need to be familiar with geographic information and software development, and be able to work with a team that will include anthropologists and human-computer interaction experts who will design systems to be used in citizen science projects. Travel will be required as part of the project. A willingness to live for short periods in remote forest locations in simple lodgings, eating local food, will be necessary. French language skills are desirable.

Complete details about this post and application procedure are available on the UCL jobs website.

In addition, we offer a PhD Studentship on How interaction design and mobile mapping influences participation in Citizen Science, which is part of the EveryAware project and is also open to any EU citizen.

Extreme Citizen Science – ExCiteS

Challenging Engineering is an EPSRC programme aimed at supporting individuals in building  a research group and to ‘establish themselves as the future leaders of research’. As can be imagined, this is a both prestigious and well-funded programme – it provides enough resources to establish a group, recruit postdoctoral and PhD researchers, visit external laboratories and run innovative research activities.

The process of selecting the UCL candidates started in mid-May 2010, with the final interviews at the end of December, just before the Christmas break. Therefore, it was very satisfying to open the email from EPSRC while at a visit to the Technion and see that my application will be funded.

The proposal itself focused on Citizen Science – the participation of amateurs, volunteers and enthusiasts in scientific projects – which is not new, given activities such as the Christmas Bird Count or the British Trust for Ornithology Survey, in which volunteers observe birds and report to a national repository. Such projects date back to the early 20th century, and many of the temperature records used in climate modelling today have been collected by amateur enthusiasts operating their own weather stations.

Over the past decade, Web 2.0 technologies have led to the proliferation of Citizen Science activities, from SETI@Home, where people volunteer their unused computer processing power, to Galaxy Zoo, where amateur astronomers suggest interpretations of images from the Hubble telescope, to the Pepys Estate in Deptford, London, where residents carried out community noise monitoring for six weeks to challenge the activities of a local scrapyard operator.

However, the current range of Citizen Science projects is limited in several respects. First, in most instances the participants are trusted only as passive participants (by donating CPU cycles), or as active participants but limited to basic observation and data collection. They do not participate in problem definition or in the scientific analysis itself. Second, there is an implicit assumption that participants will have a relatively advanced level of education. Third, and largely because of the educational requirements, Citizen Science occurs mostly in affluent places, and therefore most of the places that are critical for encouraging biodiversity conservation, and where population growth is most rapid, are effectively excluded.

The new research group will challenge this current mode of Citizen Science by suggesting the establishment of an interdisciplinary team that will focus on ‘Extreme’ Citizen Science (ExCiteS). ExCiteS is extreme in three ways: first, it aims to develop the theories and methodologies to allow any community to start a Citizen Science project that will deal with the issues that concern them – from biodiversity to food production; second, it will provide a set of tools that can be used by any user, regardless of their level of literacy, to collect, analyse and act on information by using established scientific methods; finally, it aims to use the methodologies of Citizen Science around the globe, by developing a technology, through collaborative activities, that can involve communities from housing estates in London to hunter-gatherers and forest villagers in the Congo Basin. The underlying technology is intended to be universal and to provide the foundations for many other projects and activities.

The technology that will be developed will rely on spatial and geographical representations of information. The reason for focusing on this mode of representation is that, as a form of human communication, geographical representations predate text, and are likely to be accessible by many people with limited reading and technology literacy.

ExCiteS has the transformative potential to deal with some of the major sustainability challenges involved in using science and Information and Communication Technologies in a hot (due to climate change), flat (due to globalisation) and crowded (due to population increase) world, by creating tools that will help communities understand their environment as it changes, and manage it by using scientific modelling and management methods.

The proposal focuses not only on the development of ExCiteS as a practice, but, significantly, on developing a fundamental understanding of Citizen Science by studying the motivation of participants and their incentives, identifying patterns of data collection, and dealing with the uncertainty and validity of data collected in this way.

The activities of the ExCiteS group will officially start in May, and I will be working closely with Dr Jerome Lewis, at UCL Anthropology, to develop the area of Extreme Citizen Science. We are going to start by recruiting a postdoctoral fellow and 2 PhD students – so if you are interested in this type of challenge, get in touch.