19 December, 2011
As noted in the previous post, which focused on the linkage between GIS and Environmental Information Systems, the Eye on Earth Summit took place in Abu Dhabi on the 12 to 15 December 2011, and focused on ‘the crucial importance of environmental and societal information and networking to decision-making’. Throughout the summit, two aspects of public were discussed extensively. On the one hand, Principle 10 of the Rio declaration from 1992 which call for public access to information, participation in decision making and access to justice was frequently mentioned including the need to continue and extend its implementation across the world. On the other, the growing importance of citizen science and crowdsourced environmental information was highlighted as a way to engage the wider public in environmental issues and contribute to the monitoring and understanding of the environment. They were not presented or discussed as mutually exclusive approaches to public involvement in environmental decision making, and yet, they do not fit together without a snag – so it is worth minding the gap.
As I have noted in several talks over the past 3 years (e.g. at the Oxford Transport Research Unit from which the slides above were taken), it is now possible to define 3 eras of public access to environmental information. During the first era, between the first UN environmental conference, held in Stockholm in 1972, were the UN Environmental Programme (UNEP) was established, and the Earth conference in Rio in 1992, environmental information was collected by experts, to be analysed by experts, and to be accessed by experts. The public was expected to accept the authoritative conclusions of the experts. The second period, between 1990s and until the mid 2000s and the emergence of Web 2.0, the focus turned to the provision of access to the information that was collected and processed by experts. This is top-down delivery of information that is at the centre of Principle 10:
‘Environmental issues are best handled with participation of all concerned citizens, at the relevant level. At the national level, each individual shall have appropriate access to information concerning the environment that is held by public authorities, including information on hazardous materials and activities in their communities, and the opportunity to participate in decision-making processes. States shall facilitate and encourage public awareness and participation by making information widely available. Effective access to judicial and administrative proceedings, including redress and remedy, shall be provided’
Notice the two emphasised sections which focus on passive provision of information to the public – there is no expectation that the public will be involved in creating it.
With the growth of the interactive web (or Web 2.0), and the increase awareness to citizen or community science , new modes of data collection started to emerge, in which the information is being produced by the public. Air pollution monitoring, noise samples or traffic surveys – all been carried out independently by communities using available cheap sensors or in collaboration with scientists and experts. This is a third era of access to environmental information: produced by experts and the public, to be used by both.
Thus, we can identify 3 eras of access to environmental information: authoritative (1970s-1990s), top-down (1990s-2005) and collaborative (2005 onward).
The collaborative era presents new challenges. As in previous periods, the information needs to be at the required standards, reliable and valid. This can be challenging for citizen science information. It also need to be analysed, and many communities don’t have access to the required expertise (see my presentation from the Open Knowledge Foundation Conference in 2008 that deals with this issue). Merging information from citizen science studies with official information is challenging. These and other issues must be explored, and – as shown above – the language of Principle 10 might need revision to account for this new era of environmental information.
17 December, 2011
The Eye on Earth Summit took place in Abu Dhabi on the 12 to 15 December 2011, and focused on ‘the crucial importance of environmental and societal information and networking to decision-making’. The summit was an opportunity to evaluate the development of Principle 10 from Rio declaration in 1992 as well as Chapter 40 of Agenda 21 both of which focus on environmental information and decision making. The summit’s many speakers gave inspirational talks – with an impressive list including Jane Goodall highlighting the importance of information for education; Mathis Wackernagel updating on the developments in Ecological Footprint; Rob Swan on the importance of Antarctica; Sylvia Earle on how we should protect the oceans; Mark Plotkin, Rebecca Moore and Chief Almir Surui on indigenous mapping in the Amazon and man others. The white papers that accompany the summit can be found in the Working Groups section of the website, and are very helpful updates on the development of environmental information issues over the past 20 years and emerging issues.
Interestingly, Working Group 2 on Content and User Needs is mentioning the conceptual framework of Environmental Information Systems (EIS) which I started developing in 1999 and after discussing it in the GIS and Environmental Modelling conference in 2000, I have published it as the paper ‘Public access to environmental information: past, present and future’ in the journal Computers, Environment and Urban Systems in 2003.
Discussing environmental information for a week made me to revisit the framework and review the changes that occurred over the past decade.
First, I’ll present the conceptual framework, which is based on 6 assertions. The framework was developed on the basis of a lengthy review in early 1999 of the available information on environmental information systems (the review was published as CASA working paper 7). While synthesising all the information that I have found, some underlying assumptions started to emerge, and by articulating them and putting them together and showing how they were linked, I could make more sense of the information that I found. This helped in answering questions such as ‘Why do environmental information systems receive so much attention from policy makers?’ and ‘Why are GIS appearing in so many environmental information systems ?’. I have used the word ‘assertions’ as the underlying principles seem to be universally accepted and taken for granted. This is especially true for the 3 core assumptions (assertions 1-3 below).
- Sound knowledge, reliable information and accurate data are vital for good environmental decision making.
- Within the framework of sustainable development, all stakeholders should take part in the decision making processes. A direct result of this is a call for improved public participation in environmental decision making.
- Environmental information is exceptionally well suited to GIS (and vice versa). GIS development is closely related to developments in environmental research, and GIS output is considered to be highly advantageous in understanding and interpreting environmental data.
- (Notice that this is emerging from combining 1 and 2) To achieve public participation in environmental decision making, the public must gain access to environmental information, data and knowledge.
- (Based on 1 and 3) GIS use and output is essential for good environmental decision making.
- (Based on all the others) Public Environmental Information Systems should be based on GIS technologies. Such systems are vital for public participation in environmental decision making.
Intriguingly, the Eye on Earth White Paper notes ‘This is a very “Geospatial” centric view; however it does summarise the broader principles of Environmental Information and its use’. Yet, my intention was not to develop a ‘Geospatial’ centric view – I was synthesising what I have found, and the keywords that I have used in the search did not include GIS. Therefore, the framework should be seen as an attempt to explain the reason that GIS is so prominent.
With this framework in mind, I have noticed a change over the past decade. Throughout the summit, GIS and ‘Geospatial’ systems were central – and they were mentioned and demonstrated many times. I was somewhat surprised how prominent they were in Sha Zukang speech (He is the Undersecretary General, United Nations, and Secretary General Rio +20 Summit). They are much more central than they were when I carried out the survey, and I left the summit feeling that for many speakers, presenters and delegates, it is now expected that GIS will be at the centre of any EIS. The wide acceptance does mean that initiatives such as the ‘Eye on Earth Network’ that is based on geographic information sharing is now possible. In the past, because of the very differing data structures and conceptual frameworks, it was more difficult to suggest such integration. The use of GIS as a lingua franca for people who are dealing with environmental information is surely helpful in creating an integrative picture of the situation at a specific place, across multiple domains of knowledge.
However, I see a cause for concern for the equivalence of GIS with EIS. As the literature in GIScience discussed over the years, GIS is good at providing snapshots, but less effective in modelling processes, or interpolating in both time and space, and most importantly, is having a specific way of creating and processing information. For example, while GIS can be coupled with system dynamic modelling (which was used extensively in environmental studies – most notably in ‘Limits to Growth’) it is also possible to run such models and simulations in packages that don’t use geographic information – For example, in the STELLA package for system dynamics or in bespoke models that were created with dedicated data models and algorithms. Importantly, the issue is not about the technical issues of coupling different software packages such as STELLA or agent-based modelling with GIS. Some EIS and environmental challenge might benefit from different people thinking in different ways about various problems and solutions, and not always forced to consider how a GIS play a part in them.
The previous post focused on citizen science as participatory science. This post is discussing the meaning of this differentiation. It is the final part of the chapter that will appear in the book:
The typology of participation can be used across the range of citizen science activities, and one project should not be classified only in one category. For example, in volunteer computing projects most of the participants will be at the bottom level, while participants that become committed to the project might move to the second level and assist other volunteers when they encounter technical problems. Highly committed participants might move to a higher level and communicate with the scientist who coordinates the project to discuss the results of the analysis and suggest new research directions.
This typology exposes how citizen science integrates and challenges the way in which science discovers and produces knowledge. Questions about the way in which knowledge is produced and truths are discovered are part of the epistemology of science. As noted above, throughout the 20th century, as science became more specialised, it also became professionalised. While certain people were employed as scientists in government, industry and research institutes, the rest of the population – even if they graduated from a top university with top marks in a scientific discipline – were not regarded as scientists or as participants in the scientific endeavour unless they were employed professionally to do so. In rare cases, and following the tradition of ‘gentlemen/women scientists’, wealthy individuals could participate in this work by becoming an ‘honorary fellow’ or affiliated to a research institute that, inherently, brought them into the fold. This separation of ‘scientists’ and ‘public’ was justified by the need to access specialist equipment, knowledge and other privileges such as a well-stocked library. It might be the case that the need to maintain this separation is a third reason that practising scientists shy away from explicitly mentioning the contribution of citizen scientists to their work in addition to those identified by Silvertown (2009).
However, similarly to other knowledge professionals who operate in the public sphere, such as medical experts or journalists, scientists need to adjust to a new environment that is fostered by the Web. Recent changes in communication technologies, combined with the increased availability of open access information and the factors that were noted above, mean that processes of knowledge production and dissemination are opening up in many areas of social and cultural activities (Shirky 2008). Therefore, some of the elitist aspects of scientific practice are being challenged by citizen science, such as the notion that only dedicated, full-time researchers can produce scientific knowledge. For example, surely it should be professional scientists who can solve complex scientific problems such as long-standing protein-structure prediction of viruses. Yet, this exact problem was recently solved through a collaboration of scientists working with amateurs who were playing the computer game Foldit (Khatib et al. 2011). Another aspect of the elitist view of science can be witnessed in interaction between scientists and the public, where the assumption is of unidirectional ‘transfer of knowledge’ from the expert to lay people. Of course, as in the other areas mentioned above, it is a grave mistake to argue that experts are unnecessary and can be replaced by amateurs, as Keen (2007) eloquently argued. Nor is it suggested that, because of citizen science, the need for professionalised science will diminish, as, in citizen science projects, the participants accept the difference in knowledge and expertise of the scientists who are involved in these projects. At the same time, the scientists need to develop respect towards those who help them beyond the realisation that they provide free labour, which was noted above.
Given this tension, the participation hierarchy can be seen to be moving from a ‘business as usual’ scientific epistemology at the bottom, to a more egalitarian approach to scientific knowledge production at the top. The bottom level, where the participants are contributing resources without cognitive engagement, keeps the hierarchical division of scientists and the public. The public is volunteering its time or resources to help scientists while the scientists explain the work that is to be done but without expectation that any participant will contribute intellectually to the project. Arguably, even at this level, the scientists will be challenged by questions and suggestions from the participants and, if they do not respond to them in a sensitive manner, they will risk alienating participants. Intermediaries such as the IBM World Community Grid, where a dedicated team is in touch with scientists who want to run projects and a community of volunteered computing providers, are cases of ‘outsourcing’ the community management and thus allowing, to an extent, the maintenance of the separation of scientists and the public.
As we move up the ladder to a higher level of participation, the need for direct engagement between the scientist and the public increases. At the highest level, the participants are assumed to be on equal footing with the scientists in terms of scientific knowledge production. This requires a different epistemological understanding of the process, in which it is accepted that the production of scientific insights is open to any participant while maintaining scientific standards and practices such as systematic observations or rigorous statistical analysis to verify that the results are significant. The belief that, given suitable tools, many lay people are capable of such endeavours is challenging to some scientists who view their skills as unique. As the case of the computer game that helped in the discovery of new protein formations (Khatib et al. 2011) demonstrated, such collaboration can be fruitful even in cutting-edge areas of science. However, it can be expected that the more mundane and applied areas of science will lend themselves more easily to the fuller sense of collaborative science in which participants and scientists identify problems and develop solutions together. This is because the level of knowledge required in cutting-edge areas of science is so demanding.
Another aspect in which the ‘extreme’ level challenges scientific culture is that it requires scientists to become citizen scientists in the sense that Irwin (1995), Wilsdon, Wynne and Stilgoe (2005) and Stilgoe (2009) advocated (Notice Stilgoe’s title: Citizen Scientists). In this interpretation of the phrase, the emphasis is not on the citizen as a scientist, but on the scientist as a citizen. It requires the scientists to engage with the social and ethical aspects of their work at a very deep level. Stilgoe (2009, p.7) suggested that, in some cases, it will not be possible to draw the line between the professional scientific activities, the responsibilities towards society and a fuller consideration of how a scientific project integrates with wider ethical and societal concerns. However, as all these authors noted, this way of conceptualising and practising science is not widely accepted in the current culture of science.
Therefore, we can conclude that this form of participatory and collaborative science will be challenging in many areas of science. This will not be because of technical or intellectual difficulties, but mostly because of the cultural aspects. This might end up being the most important outcome of citizen science as a whole, as it might eventually catalyse the education of scientists to engage more fully with society.