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.
20 July, 2011
As part of the Volunteered Geographic Information (VGI) workshop that was held in Seattle in April 2011, Daniel Sui, Sarah Elwood and Mike Goodchild announced that they will be editing a volume dedicated to the topic, published as ‘Crowdsourcing Geographic Knowledge‘ .
My contribution to this volume focuses on citizen science, and shows the links between it and VGI. The chapter is currently under review, but the following excerpt discusses different types of citizen science activities, and I would welcome comments:
“While the aim here is not to provide a precise definition of citizen science. Yet, a definition and clarification of what the core characteristics of citizen science are is unavoidable. Therefore, it is defined as scientific activities in which non-professional scientists volunteer to participate in data collection, analysis and dissemination of a scientific project (Cohn 2008; Silvertown 2009). People who participate in a scientific study without playing some part in the study itself – for example, volunteering in a medical trial or participating in a social science survey – are not included in this definition.
While it is easy to identify a citizen science project when the aim of the project is the collection of scientific information, as in the recording of the distribution of plant species, there are cases where the definition is less clear-cut. For example, the process of data collection in OpenStreetMap or Google Map Maker is mostly focused on recording verifiable facts about the world that can be observed on the ground. The tools that OpenStreetMap mappers use – such as remotely sensed images, GPS receivers and map editing software – can all be considered scientific tools. With their attempt to locate observed objects and record them on a map accurately, they follow the footsteps of surveyors such as Robert Hooke, who also carried out an extensive survey of London using scientific methods – although, unlike OpenStreetMap volunteers, he was paid for his effort. Finally, cases where facts are collected in a participatory mapping activity, such as the one that Ghose (2001) describes, should probably be considered a citizen science only if the participants decided to frame it as such. For the purpose of the discussion here, such a broad definition is more useful than a limiting one that tries to reject certain activities.
Notice also that, by definition, citizen science can only exist in a world in which science is socially constructed as the preserve of professional scientists in academic institutions and industry, because, otherwise, any person who is involved in a scientific project would simply be considered a contributor and potentially a scientist. As Silvertown (2009) noted, until the late 19th century, science was mainly developed by people who had additional sources of employment that allowed them to spend time on data collection and analysis. Famously, Charles Darwin joined the Beagle voyage, not as a professional naturalist but as a companion to Captain FitzRoy. Thus, in that era, almost all science was citizen science albeit mostly by affluent gentlemen scientists and gentlewomen. While the first professional scientist is likely to be Robert Hooke, who was paid to work on scientific studies in the 17th century, the major growth in the professionalisation of scientists was mostly in the latter part of the 19th and throughout the 20th centuries.
Even with the rise of the professional scientist, the role of volunteers has not disappeared, especially in areas such as archaeology, where it is common for enthusiasts to join excavations, or in natural science and ecology, where they collect and send samples and observations to national repositories. These activities include the Christmas Bird Watch that has been ongoing since 1900 and the British Trust for Ornithology Survey, which has collected over 31 million records since its establishment in 1932 (Silvertown 2009). Astronomy is another area where amateurs and volunteers have been on par with professionals when observation of the night sky and the identification of galaxies, comets and asteroids are considered (BBC 2006). Finally, meteorological observations have also relied on volunteers since the early start of systematic measurements of temperature, precipitation or extreme weather events (WMO 2001).
This type of citizen science provides the first type of ‘classic’ citizen science – the ‘persistence’ parts of science where the resources, geographical spread and the nature of the problem mean that volunteers sometimes predate the professionalisation and mechanisation of science. These research areas usually require a large but sparse network of observers who carry out their work as part of a hobby or leisure activity. This type of citizen science has flourished in specific enclaves of scientific practice, and the progressive development of modern communication tools has made the process of collating the results from the participants easier and cheaper, while inherently keeping many of the characteristics of data collection processes close to their origins.
A second set of citizen science activities is environmental management and, even more specifically, within the context of environmental justice campaigns. Modern environmental management includes strong technocratic and science oriented management practices (Bryant & Wilson 1998; Scott & Barnett 2009) and environmental decision making is heavily based on scientific environmental information. As a result, when an environmental conflict emerges – such as a community protest over a local noisy factory or planned expansion of an airport – the valid evidence needs to be based on scientific data collection. This aspect of environmental justice struggle is encouraging communities to carry out ‘community science’ in which scientific measurements and analysis are carried out by members of local communities so they can develop an evidence base and set out action plans to deal with problems in their area. A successful example of such an approach is the ‘Global Community Monitor’ method to allow communities to deal with air pollution issues (Scott & Barnett 2009). This is performed through a simple method of sampling air using plastic buckets followed by analysis in an air pollution laboratory, and, finally, the community being provided with instructions on how to understand the results. This activity is termed ‘Bucket Brigade’ and was used across the world in environmental justice campaigns. In London, community science was used to collect noise readings in two communities that are impacted by airport and industrial activities. The outputs were effective in bringing environmental problems to the policy arena (Haklay, Francis & Whitaker 2008). As in ‘classic’ citizen science, the growth in electronic communication has enabled communities to identify potential methods – e.g. through the ‘Global Community Monitor’ website – as well as find international standards , regulations and scientific papers that can be used together with the local evidence.
However, the emergence of the Internet and the Web as a global infrastructure has enabled a new incarnation of citizen science: the realisation of scientists that the public can provide free labour, skills, computing power and even funding, and, the growing demands from research funders for public engagement all contributing to the motivation of scientists to develop and launch new and innovative projects (Silvertown 2009; Cohn 2008). These projects utilise the abilities of personal computers, GPS receivers and mobile phones to double as scientific instruments.
This third type of citizen science has been termed ‘citizen cyberscience’ by Francois Grey (2009). Within it, it is possible to identify three sub-categories: volunteered computing, volunteered thinking and participatory sensing.
Volunteered computing was first developed in 1999, with the foundation of SETI@home (Anderson et al. 2002), which was designed to distribute the analysis of data that was collected from a radio telescope in the search for extra-terrestrial intelligence. The project utilises the unused processing capacity that exists in personal computers, and uses the Internet to send and receive ‘work packages’ that are analysed automatically and sent back to the main server. Over 3.83 million downloads were registered on the project’s website by July 2002. The system on which SETI@home is based, the Berkeley Open Infrastructure for Network Computing (BOINC), is now used for over 100 projects, covering Physics, processing data from the Large Hadron Collider through LHC@home; Climate Science with the running of climate models in Climateprediction.net; and Biology in which the shape of proteins is calculated in Rosetta@home.
While volunteered computing requires very little from the participants, apart from installing software on their computers, in volunteered thinking the volunteers are engaged at a more active and cognitive level (Grey 2009). In these projects, the participants are asked to use a website in which information or an image is presented to them. When they register onto the system, they are trained in the task of classifying the information. After the training, they are exposed to information that has not been analysed, and are asked to carry out classification work. Stardust@home (Westphal et al. 2006) in which volunteers were asked to use a virtual microscope to try to identify traces of interstellar dust was one of the first projects in this area, together with the NASA ClickWorkers that focused on the classification of craters on Mars. Galaxy Zoo (Lintott et al. 2008), a project in which volunteers classify galaxies, is now one of the most developed ones, with over 100,000 participants and with a range of applications that are included in the wider Zooniverse set of projects (see http://www.zooniverse.org/) .
Participatory sensing is the final and most recent type of citizen science activity. Here, the capabilities of mobile phones are used to sense the environment. Some mobile phones have up to nine sensors integrated into them, including different transceivers (mobile network, WiFi, Bluetooth), FM and GPS receivers, camera, accelerometer, digital compass and microphone. In addition, they can link to external sensors. These capabilities are increasingly used in citizen science projects, such as Mappiness in which participants are asked to provide behavioural information (feeling of happiness) while the phone records their location to allow the linkage of different locations to wellbeing (MacKerron 2011). Other activities include the sensing of air-quality (Cuff 2007) or noise levels (Maisonneuve et al. 2010) by using the mobile phone’s location and the readings from the microphone.”
12 May, 2011
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.
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.
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.
7 March, 2011
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.
PhD Studentship – How interaction design and mobile mapping influence participation in Citizen Science?
24 February, 2011
Geographic and scientific information created by amateur citizens, represents a shift from authoritative data towards information generated by the general public through collaboration. The increasing emergence of such data has been brought about by the advent of Web 2.0 technologies, and mirrors other information sharing activities such as Wikipedia and Flickr. Such activity has also contributed towards the emergence of citizen science where the general public not only collect scientific data (such as noise or pollution information) but also participate in its processing and interpretation, benefitting as a group from the resulting output. Much of this information is geographic in nature and can be communicated to the participants through maps and geographic visualisations.
The PhD forms part of, and will be contextualised by, the European Union FP7 project everyAware. This project will integrate digital technologies and theoretical analytical techniques to collect both physical measurements and subjective opinions about environmental conditions – such as pollution measurements for cyclists alongside their impressions of the environment – using crowd-sourcing techniques on mobile devices (such as Android devices or iPhone – for example, see www.noisetube.net). The data, collected through four case study sites in the UK and Europe, will be analysed and user-oriented results fed back to the end users. A crucial challenge for this project is the seamless integration of participatory sensing with subjective opinions, allowing the investigation into the opinion dynamics mechanisms taking place in the communities. Within this project, UCL team is responsible for the building of a set of tools that will enable citizens to integrate live, personalised environmental information in their behavioral choices and orientations. The research will investigate, both theoretically and empirically, the drivers of shifts in public opinion, with subsequent changes in individual behaviour, by means of targeted environmental knowledge and information dissemination.
More specifically, the PhD will examine two aspects of citizen science:
- Whether factors such as human-computer software interface design, interaction processes, access to maps of the resulting scientific data and associated qualitative information can be used to recruit people to citizen science projects.
- Can these concepts be used to retain participants and encourage additional, more regular, ongoing and repeated contributions to such activities.
Given the technical nature of the project, we expect that the candidate will have a strong background in programming, preferably including experience of application development for mobile devices. The candidate should also hold an MSc. in Computer Science, Geographical Information Systems, Human-Computer Interaction or other related disciplines. An interest in interaction and usability, in particular looking at the perspective of non-expert users, would be an asset. This position is open to all European Union Citizens. The stipend will be at least £16,500 (tax-free). Additionally, PhD tuition fees will be paid for by the everyAware project. Some travel may be required to everyAware Case Study locations in the UK and Europe.
Please send a CV and a personal statement explaining your interest in citizen science, usability and geographic information, why you are interested in the project and how you would approach the development of a mobile application for everyAware, with examples of previous software development to me at firstname.lastname@example.org
Application Closing Date: 1st May 2011
7 January, 2011
EveryAware is a three-year research project, funded under the European Union Seventh Framework Programme (FP7).
The project’s focus is on the development of Citizen Science techniques to allow people to find out about their local environmental conditions, and then to see if the provision of this information leads to behaviour change.
The abstract of the project highlights the core topics that will be covered:
‘The enforcement of novel policies may be triggered by a grassroots approach, with a key contribution from information and communication technology (ICT). Current low-cost sensing technologies allow the citizens to directly assess the state of the environment; social networking tools allow effective data and opinion collection and real-time information-spreading processes. Moreover theoretical and modelling tools developed by physicists, computer scientists and sociologists allow citizens to analyse, interpret and visualise complex data sets.
‘The proposed project intends to integrate all crucial phases (environmental monitoring, awareness enhancement, behavioural change) in the management of the environment in a unified framework, by creating a new technological platform combining sensing technologies, networking applications and data-processing
tools; the Internet and the existing mobile communication networks will provide the infrastructure hosting this platform, allowing its replication in different times and places. Case studies concerning different numbers of participants will test the scalability of the platform, aiming to involve as many citizens as possible thanks to
low cost and high usability. The integration of participatory sensing with the monitoring of subjective opinions is novel and crucial, as it exposes the mechanisms by which the local perception of an environmental issue, corroborated by quantitative data, evolves into socially-shared opinions, and how the latter, eventually, drives behavioural changes. Enabling this level of transparency critically allows an effective communication of desirable environmental strategies to the general public and to institutional agencies.’
The project will be coordinated by Fondazione ISI (Institute for Scientific Interchange) and the Physics department at Sapienza Università di Roma. Other participants include the L3S Research Center at the Gottfried Wilhelm Leibniz Universität, Hannover, and finally the Environmental Risk and Health unit at the Flemish Institute of Technological Research (VITO).
At UCL, I will run the project together with Dr Claire Ellul. We will focus on Citizen Science, the interaction with mobile phones for data collection and understanding behaviour change. We are looking for a PhD student to work on this project so, if this type of activity is of interest, get it touch.
5 October, 2010
The London Citizen Cyberscience Summit in early September was a stimulating event, which brought together a group of people with an interest in this area. A report from the event, with a very good description of the presentations, including a reflection piece, is available on the ‘Strange Attractor’ blog.
During the summit, I discussed the aspects of ‘Extreme’ Citizen Science, where we move from usual science to participatory research. The presentation was partly based on a paper that I wrote and that I presented during the workshop on the value of Volunteered Geographical Information in advancing science, which was run as part of the GIScience 2010 conference towards the middle of September. Details about the workshop are available on the workshop’s website including a set of interesting position papers.
The presentation below covers the topics that I discussed in both workshops. Here, I provide a brief synopsis for the presentation, as it is somewhat different from the paper.
In the talk, I started by highlighting that by using different terminologies we can notice different facets of the practice of crowd data collection (VGI within the GIScience community, crowdsourcing, participatory mapping …).
The first way in which we can understand this information is in the context of Web 2.0 applications. These applications can be non-spatial (such as Wikipedia or Twitter), or implicitly spatial (such as Flickr – you need to be in a location before you can capture a photograph), or explicitly spatial , in applications that are about collecting geographical information – for example OpenStreetMap. When looking at VGI from the perspective of Web 2.0 it’s possible to identify the specific reasons that it emerged and how other similar applications influence its structure and practices.
The second way to view this information is as part of geographical information produced by companies who need mapping information (such as Google or TomTom). In this case, you notice that it’s about reducing the costs of labour and the need for active or passive involvement of the person who carries out the mapping.
The third, and arguably new way to view VGI is as part of Citizen Science. These activities have been going for a long time in ornithology and in meteorology. However, there are new forms of Citizen Science that rely on ICT – such as movement-activated cameras (slide 11 on the left) that are left near animal trails and are operated by volunteers, or a network of accelerometers that form a global earthquake monitoring network. Not all Citizen Science is spatial, and there are very effective examples, especially in the area of Citizen Cyberscience. So in this framing of VGI we can pay special attention to the collection of scientific information. Importantly, as in the case of spatial application, some volunteers become experts, such as Hanny van Arkel who has discovered a type of galaxy in Galaxy Zoo.
Slides 16-17 show the distribution of crowdsourced images, and emphasise the spatial distribution of information near population centres and tourist attractions. Slides 19-25 show the analysis of the data that was collected by OpenStreetMap volunteers and highlight bias towards highly populated and affluent areas.
Citizen Science is not just about the data collections. There are also cultural problems regarding the trustworthiness of the data, but slides 28-30 show that the data is self-improving as more volunteers engage in the process (in this case, mapping in OpenStreetMap). On that basis, I do question the assumption about trustworthiness of volunteers and the need to change the way we think about projects. There are emerging examples of such Citizen Science where the engagement of participants is at a higher level. For example, noise mapping activities that a community near London City Airport carried out (slides 34-39) which shows that people can engage in science and are well placed when there are opportunities, such as the ash cloud in April 2010, to collect ‘background’ noise. This is not possible without the help of communities.
Finally, slides 40 and 41 demonstrate that it is possible to engage non-literate users in environmental data collection.
So in summary, a limitless Citizen Science is possible – we need to create the tool for it and understand how to run such projects, as well study them.
3 June, 2008
While the new Defra noise maps provide the results of a computerised model, the experience of noisy places can be mapped through community mapping, as was demonstrated recently in the Royal Docks area and the Pepys Estate.
Within the Mapping Change for Sustainable Communities project, and through the collaboration with London Sustainability Exchange and London 21 projects on Environmental Justice and with the help of Christian Nold, we have recently carried out studies of noise in two areas in east London. While the method is based on a systematic data collection framework, it does not intend to replace detailed acoustics studies that the authorities should carry out regarding sources of noise which influence residential areas. What it does is enable communities to get evidence about their experience, the maximum levels of noise that they are exposed to and to identify the sources of noise that influence the specific place.
The following text is taken from the press release that we have just issued:
People living in the Pepys Estate in Lewisham and in the Royal Docks area in Newham have led the way with a new way to tackle noise. The Pepys Estate currently suffers noise pollution from a scrapyard near the centre of the estate and very close to both a primary and nursery school, while Royal Docks suffers noise problems resulting from flights in and out of London City Airport (LCA), where a major expansion is threatened.
The project supplied local residents with noise meters and trained them in how to use these devices. They went on to make over 1500 measurements at all times of day and night and developed their own ‘noise maps’.
The results of this ‘citizen science’ have been remarkable. On the Pepys Estate members of the Community Forum found disturbingly high levels of noise, often continuing outside normal working hours. This noise affected quality of life up to 350 metres from the scrapyard. They have been trying to deal with this problem for over six years, initially raising concerns with the Mayor of Lewisham and others in September 2002. Since this time the disturbance has actually escalated. Now armed with this information they called a public meeting to present their findings to the council and the Environment Agency.
Lewisham Council and the Environment Agency accept that there is a problem. After seeing the results of the survey the Agency has appointed an acoustic consultant to carry out a detailed analysis of noise in and from the scrapyard. The residents who carried out the survey will meet with the consultant to share their information, and will work with the council to agree an action plan for moving forward.
The communities surrounding London City Airport (LCA), including Virginia Quays and Thamesmead, also found troubling results. Many readings exceed levels deemed to cause serious annoyance under the World Health Organisation community noise guidelines. The measurements gathered by the community revealed a clear correlation between unacceptable levels of noise and the LCA operational hours. More interestingly, the results obtained by both communities indicate that people are quite accurate in their perceptions of noise levels and the survey enabled them to express how these affected them. One of the residents said ‘the noise is irritable, I can’t relax or have the window open – but I can’t shut out the noise so have to turn the TV up – but everything is then so loud.’
The full press release is available here.