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 next year 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.
6 June, 2011
It is always nice to announce good news. Back in February, together with Richard Treves at the University of Southampton, I submitted an application to the Google’s Faculty Research Award program for a grant to investigate Google Earth Tours in education. We were successful in getting a grant worth $86,883 USD. The project builds on my expertise in usability studies of geospatial technologies, including the use of eye tracking and other usability engineering techniques for GIS and Richard’s expertise in Google Earth tours and education, and longstanding interest in usability issues.
In this joint UCL/Southampton project, UCL will be lead partner and we will appoint a junior researcher for a year to develop run experiments that will help us in understanding of the effectiveness of Google Earth Tours in geographical learning, and we aim to come up with guidelines to their use. If you are interested, let me know.
Our main contact at Google for the project is Ed Parsons. We were also helped by Tina Ornduff and Sean Askay who acted as referees for the proposal.
The core question that we want to address is “How can Google Earth Tours be used create an effective learning experience?”
So what do we plan to do? Previous research on Google Earth Tours (GETs) has shown them to be an effective visualization technique for teaching geographical concepts, yet their use in this way is essentially passive. Active learning is a successful educational approach where student activity is combined with instruction to enhance learning. In the proposal we suggest that there is great education value in combining the advantages of the rich visualization of GETs with student activities. Evaluating the effectiveness of this combination is the purpose of the project, and we plan to do this by creating educational materials that consist of GETs and activities and testing them against other versions of the materials using student tests, eye tracking and questionnaires as data gathering techniques.
We believe that by improving the techniques by which spatial data is visualized we are improving spatial information access overall.
A nice aspect of the getting the project funded is that it works well with a project that is led by Claire Ellul and Kate Jones and funded by JISC. The G3 project, or “Bridging the Gaps between the GeoWeb and GIS” is touching on similar aspects and we surely going to share knowledge with them.
For more background on Richard Treves, see his blog (where the same post is published!)
In March 2008, I started comparing OpenStreetMap in England to the Ordnance Survey Meridian 2, as a way to evaluate the completeness of OpenStreetMap coverage. The rational behind the comparison is that Meridian 2 represents a generalised geographic dataset that is widely use in national scale spatial analysis. At the time that the study started, it was not clear that OpenStreetMap volunteers can create highly detailed maps as can be seen on the ‘Best of OpenStreetMap‘ site. Yet even today, Meridian 2 provides a minimum threshold for OpenStreetMap when the question of completeness is asked.
So far, I have carried out 6 evaluations, comparing the two datasets in March 2008, March 2009, October 2009, March 2010, September 2010 and March 2011. While the work on the statistical analysis and verification of the results continues, Oliver O’Brien helped me in taking the results of the analysis for Britain and turn them into an interactive online map that can help in exploring the progression of the coverage over the various time period.
Notice that the visualisation shows the total length of all road objects in OpenStreetMap, so does not discriminate between roads, footpaths and other types of objects. This is the most basic level of completeness evaluation and it is fairly coarse.
The application will allow you to browse the results and to zoom to a specific location, and as Oliver integrated the Ordnance Survey Street View layer, it will allow you to see what information is missing from OpenStreetMap.
Finally, note that for the periods before September 2010, the coverage is for England only.
Some details on the development of the map are available on Oliver’s blog.
31 March, 2011
The G3 Project, is a new project led by Claire Ellul and Kate Jones and funded by the JISC geospatial working group. The project’s aim is to create an interactive online mapping tutorial system for students in areas that are not familiar with GIS such as urban design, anthropology and environmental management.
The project can provides a template for the introduction of geographical concepts to new groups of learners. By choosing a discipline specific scenario, key geographic concepts and functions will be presented to novices in a useful and useable manner so the learning process is improved. Users will be introduced to freely available geographic data relevant to their particular discipline and know where to look for more. G3 Project will create a framework to support learners and grow their confidence without facing the difficult interfaces and complexity of desktop mapping systems that are likely to create obstacles for students, with the feeling that ‘this type of analysis is not for me’.
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 email@example.com
Application Closing Date: 1st May 2011
10 February, 2011
In 2009, Ud Doron, who studied on our MSc in Environmental Systems Engineering developed a research project together with Tse-Hui Teh, who is doing her PhD on urban water issues. The project was co-supervised by Sarah Bell.
The focus of the project was on a series of participatory workshops to understand the relationships between urban residents and water technology. The workshops explored the perceptions and actions of environmentally aware citizens. Ud also explored the use of environmental information by the participants of the workshops. The output of this work is now written and published in the Water and Environment Journal.
The paper is titled Public engagement with water conservation in London
The abstract is:
Understanding water demand and consumers’ capacity for change is essential in underpinning water demand management and water efficiency programmes. This paper presents the outcomes of a qualitative study, which used discussion groups relating to water infrastructure with environmentally aware citizens in five London boroughs in the Lower Lea River Basin. The results showed a subtle interaction between users, water and technology. Users are generally unaware of their own water consumption. Individual perceptions of changes in water behaviour are constrained by habit and lack of knowledge about what changes can be made and how. Knowledge of environmental information was described as the inspiration behind making any changes. The paper concludes that access to information about water resources, infrastructure and conservation measures should be enhanced because although information sources are abundant, participants claimed they were inaccessible without considerable effort. Finally, an emphasis should also be put on helping the public form a more substantial part in environmental decisions.
and the paper is accessible in the early view section of the Water and Environment Journal http://onlinelibrary.wiley.com/doi/10.1111/j.1747-6593.2011.00256.x/full
How Many Volunteers Does It Take To Map An Area Well? The validity of Linus’ law to Volunteered Geographic Information
10 January, 2011
The paper “How Many Volunteers Does It Take To Map An Area Well? The validity of Linus’ law to “ has appeared in The Cartographic Journal. The proper citation for the paper is:
Haklay, M and Basiouka, S and Antoniou, V and Ather, A (2010) How Many Volunteers Does It Take To Map An Area Well? The validity of Linus’ law to Volunteered Geographic Information. The Cartographic Journal , 47 (4) , 315 – 322.
The abstract of the paper is as follows:
In the area of volunteered geographical information (VGI), the issue of spatial data quality is a clear challenge. The data that are contributed to VGI projects do not comply with standard spatial data quality assurance procedures, and the contributors operate without central coordination and strict data collection frameworks. However, similar to the area of open source software development, it is suggested that the data hold an intrinsic quality assurance measure through the analysis of the number of contributors who have worked on a given spatial unit. The assumption that as the number of contributors increases so does the quality is known as `Linus’ Law’ within the open source community. This paper describes three studies that were carried out to evaluate this hypothesis for VGI using the OpenStreetMap dataset, showing that this rule indeed applies in the case of positional accuracy.
To access the paper on the journal’s website, you can follow the link: 10.1179/000870410X12911304958827. However, if you don’t hold a subscription to the journal, a postprint of the paper is available at the UCL Discovery repository. If you would like to get hold of the printed version, email me.