12 July, 2014
The Vespucci initiative has been running for over a decade, bringing together participants from wide range of academic backgrounds and experiences to explore, in a ‘slow learning’ way, various aspects of geographic information science research. The Vespucci Summer Institutes are week long summer schools, most frequently held at Fiesole, a small town overlooking Florence. This year, the focus of the first summer institute was on crowdsourced geographic information and citizen science.
The workshop was supported by COST ENERGIC (a network that links researchers in the area of crowdsourced geographic information, funded by the EU research programme), the EU Joint Research Centre (JRC), Esri and our Extreme Citizen Science research group. The summer school included about 30 participants and facilitators that ranged from master students students that are about to start their PhD studies, to established professors who came to learn and share knowledge. This is a common feature of Vespucci Institute, and the funding from the COST network allowed more early career researchers to participate.
Apart from the pleasant surrounding, Vespucci Institutes are characterised by the relaxed, yet detailed discussions that can be carried over long lunches and coffee breaks, as well as team work in small groups on a task that each group present at the end of the week. Moreover, the programme is very flexible so changes and adaptation to the requests of the participants and responding to the general progression of the learning are part of the process.
This is the second time that I am participating in Vespucci Institutes as a facilitator, and in both cases it was clear that participants take the goals of the institute seriously, and make the most of the opportunities to learn about the topics that are explored, explore issues in depth with the facilitators, and work with their groups beyond the timetable.
The topics that were covered in the school were designed to provide an holistic overview of geographical crowdsourcing or citizen science projects, especially in the area where these two types of activities meet. This can be when a group of citizens want to collect and analyse data about local environmental concerns, or oceanographers want to work with divers to record water temperature, or when details that are emerging from social media are used to understand cultural differences in the understanding of border areas. These are all examples that were suggested by participants from projects that they are involved in. In addition, citizen participation in flood monitoring and water catchment management, sharing information about local food and exploring data quality of spatial information that can be used by wheelchair users also came up in the discussion. The crossover between the two areas provided a common ground for the participants to explore issues that are relevant to their research interests.
The holistic aspect that was mentioned before was a major goal for the school – so to consider the tools that are used to collect information, engaging and working with the participants, managing the data that is provided by the participants and ensuring that it is useful for other purposes. To start the process, after introducing the topics of citizen science and volunteered geographic information (VGI), the participants learned about data collection activities, including noise mapping, OpenStreetMap contribution, bird watching and balloon and kite mapping. As can be expected, the balloon mapping raised a lot of interest and excitement, and this exercise in local mapping was linked to OpenStreetMap later in the week.
The experience with data collection provided the context for discussions about data management and interoperability and design aspects of citizen science applications, as well as more detailed presentations from the participants about their work and research interests. With all these details, the participants were ready to work on their group task: to suggest a research proposal in the area of VGI or Citizen Science. Each group of 5 participants explored the issues that they agreed on – 2 groups focused on a citizen science projects, another 2 focused on data management and sustainability and finally another group explored the area of perception mapping and more social science oriented project.
Some of the most interesting discussions were initiated at the request of the participants, such as the exploration of ethical aspects of crowdsourcing and citizen science. This is possible because of the flexibility in the programme.
Now that the institute is over, it is time to build on the connections that started during the wonderful week in Fiesole, and see how the network of Vespucci alumni develop the ideas that emerged this week.
At the beginning of April, the European Citizen Science Association (ECSA) held its first Annual General Meeting in Copenhagen. In the meeting, which lasted a long afternoon and an evening many topics were covered – from membership (it’s now possible to join) to reports from the working groups. With an aim to be transparent and open ECSA has published all the material from the AGM on its website – including the slides from presentations and talks and the main points from the discussion. I have been involved in the ‘Committee Principles and standards in citizen science: sharing best practice and building capacity’ which was is led by Lucy Robinson from the UK Natural History Museum. One of the first activities that Lucy guided was the development of 10 principles of citizen science, with the aim that they can help ECSA in defining what types of projects to endorse. The tentative principles – shared between the people in the committee and now are provided on the AGM site – see her presentation. However, they are of wider interest and we are, as a group looking for comments. So the principles are:
- Citizen science projects involve citizens who actively contribute to scientific research. Citizens can act as contributors, collaborators, or as project leader and have a meaningful role in the research project (they are not simply research subjects).
- Citizen science projects have a genuine scientific question or goal, if possible resulting from discussions between citizens and professional scientists.
- Citizens are encouraged to participate in multiple stages of the scientific process, from developing the research question to co-designing the research process, gathering and analysing data, co-evaluating the research results and finally publishing the results for different audiences.
- The data gathered and/or analysed are shared and made publicly available either during or after the project, unless there are security or privacy concerns that prevent this. If the results are published academically, where possible this should be in an open access format.
- Participants receive feedback from the project lead on how their contribution adds to the project e.g. how their data will be used and what the research findings are. This adds both reward and opportunity to learn more about the science. The more communication and two-way engagement, the better!
- Citizen science activities celebrate and value the contributions of the citizen, and these are actively acknowledged in project results and publications.
- Citizen science programmes are characterised by mutual respect and acknowledgement of different skills and perspectives. Where possible, steering committees should integrate both scientists and citizen delegates. The scientists and organisers should be mindful of the power relations that exist within this social interaction.
- Citizen science projects should be inclusive. Where possible, inclusiveness should be proactive and not only reactive. Considerations of inclusiveness should include (but are not limited to) level of education, gender, age, religious belief, socio-economic factors and access to technologies.
- Being at the frontier between science and society, citizen science programmes have the opportunity to actively promote transdisciplinarity and links between natural and social sciences.
- Citizen science programmes should be evaluated for their scientific output, data quality, and the impact on participants.
The principles are open for discussion – they are not set in stone. In the discussion that followed the presentation and in a meeting of the ‘committee’ (more like sitting on the floor in a corner of the building), we explored the need for policy connection and how the aims of the project interact with these principles – for example, how applied ecological observations influence their applications. We’re still looking out for comments to develop these principles until they become part of ECSA ‘code of practice’. Comments are welcomed and will be passed to the working group.
Some ideas take long time to mature into a form that you are finally happy to share them. This is an example for such thing.
I got interested in the area of Philosophy of Technology during my PhD studies, and continue to explore it since. During this journey, I found a lot of inspiration and links to Andrew Feenberg’s work, for example, in my paper about neogeography and the delusion of democratisation. The links are mostly due to Feenberg’s attention to ‘hacking’ or appropriating technical systems to functions and activities that they are outside what the designers or producers of them thought.
In addition to Feenberg, I became interested in the work of Albert Borgmann and because he explicitly analysed GIS, dedicating a whole chapter to it in Holding on to Reality. In particular, I was intrigues by his formulation to The Device Paradigm and the notion of Focal Things and Practices which are linked to information systems in Holding on to Reality where three forms of information are presented – Natural Information, Cultural Information and Technological Information. It took me some time to see that these 5 concepts are linked, with technological information being a demonstration of the trouble with the device paradigm, while natural and cultural information being part of focal things and practices (more on these concepts below).
I first used Borgmann’s analysis as part of ‘Conversations Across the Divide‘ session in 2005, which focused on Complexity and Emergence. In a joint contribution with David O’Sullivan about ‘complexity science and Geography: understanding the limits of narratives’, I’ve used Borgmann’s classification of information. Later on, we’ve tried to turn it into a paper, but in the end David wrote a much better analysis of complexity and geography, while the attempt to focus mostly on the information concepts was not fruitful.
The next opportunity to revisit Borgmann came in 2011, for an AAG pre-conference workshop on VGI where I explored the links between The Device Paradigm, Focal Practices and VGI. By 2013, when I was invited to the ‘Thinking and Doing Digital Mapping‘ workshop that was organise by ‘Charting the Digital‘ project. I was able to articulate the link between all the five elements of Borgmann’s approach in my position paper. This week, I was able to come back to the topic in a seminar in the Department of Geography at the University of Leicester. Finally, I feel that I can link them in a coherent way.
So what is it all about?
Within the areas of VGI and Citizen Science, there is a tension between the different goals or the projects and identification of practices in terms of what they mean for the participants – are we using people as ‘platform for sensors’ or are we dealing with fuller engagement? The use of Borgmann’s ideas can help in understanding the difference. He argues that modern technologies tend to adopt the myopic ‘Device Paradigm’ in which specific interpretation of efficiency, productivity and a reductionist view of human actions are taking precedence over ‘Focal Things and Practices’ that bring people together in a way meaningful to human life. In Holding On to Reality (1999), he differentiates three types of information: natural, cultural and technological. Natural information is defined as information about reality: for example, scientific information on the movement of the earth or the functioning of a cell. This is information that was created in order to understand the functioning of reality. Cultural information is information that is being used to shape reality, such as engineering design plans. Technological information is information as reality and leads to decreased human engagement with fundamental aspects of reality. Significantly, these categories do not relate to the common usage of the words ‘natural’, ‘cultural and ‘technological’ rather to describe the changing relationship between information and reality at different stages of socio-technical development.
When we explore general geographical information, we can see that some of it is technological information, for example SatNav and the way that communicate to the people who us them, or virtual globes that try to claim to be a representation of reality with ‘current clouds’ and all. The paper map, on the other hand, provide a conduit to the experience of hiking and walking through the landscape, and is part of cultural information.
Things are especially interesting with VGI and Citizen Science. In them, information and practices need to be analysed in a more nuanced way. In some cases, the practices can become focal to the participants – for example in iSpot where the experience of identifying a species in the field is also link to the experiences of the amateurs and experts who discuss the classification. It’s an activity that brings people together. On the other hand, in crowdsourcing projects that grab information from SatNav devices, there is a demonstration of The Device Paradigm, with the potential of reducing of meaningful holiday journey to ‘getting from A to B at the shortest time’. The slides below go through the ideas and then explore the implications on GIS, VGI and Citizen Science.
Now for the next stage – turning this into a paper…
The Guardian’s Political Science blog post by Alice Bell about the Memorandum of Understanding between the UK Natural Environment Research Council and Shell, reminded me of a nagging issue that has concerned me for a while: to what degree GIS contributed to anthropocentric climate change? and more importantly, what should GIS professionals do?
I’ll say from the start that the reason it concerns me is that I don’t have easy answers to these questions, especially not to the second one. While I personally would like to live in a society that moves very rapidly to renewable energy resources, I also take flights, drive to the supermarket and benefit from the use of fossil fuels – so I’m in the Hypocrites in The Air position, as Kevin Anderson defined it. At the same time, I feel that I do have responsibility as someone who teaches future generations of GIS professionals how they should use the tools and methods of GIScience responsibly. The easy way would be to tell myself that since, for the past 20 years, I’ve been working on ‘environmental applications’ of GIS, I’m on the ‘good’ side as far as sustainability is concerned. After all, the origins of the biggest player in our industry are environmental (environmental systems research, even!), we talk regularly about ‘Design With Nature’ as a core text that led to the overlays concept in GIS, and we praise the foresight of the designers of the UNEP Global Resource Information Database in the early 1980s. Even better, Google Earth brings Climate Change information and education to anyone who want to downloaded the information from the Met Office.
But technologies are not value-free, and do encapsulate certain values in them. That’s what critical cartography and critical GIS has highlighted since the late 1990s. Nadine Schuurman’s review is still a great starting point to this literature, but most of it analysed the link of the history of cartography and GIS to military applications, or, in the case of the volume ‘Ground Truth’, the use of GIS in marketing and classification of people. To the best of my knowledge, Critical GIScience has not focused its sight on oil exploration and extraction. Of course, issues such as pollution, environmental justice or environmental impacts of oil pipes are explored, but do we need to take a closer look at the way that GIS technology was shaped by the needs of the oil industry? For example, we use, without a second thought, the EPSG (European Petroleum Survey Group) definitions of co-ordinates reference systems in many tools. There are histories of products that are used widely, such as Oracle Spatial, where some features were developed specifically for the oil & gas industry. There are secretive and proprietary projections and datums, and GIS products that are unique to this industry. One of the most common spatial analysis methods, Kriging, was developed for the extractive industry. I’m sure that there is much more to explore.
So, what is the problem with that, you would say?
Fossil fuels – oil, coal, gas – are at the centre of the process that lead to climate change. Another important thing about them is that once they’ve been extracted, they are likely to be used. That’s why there are calls to leave them in the ground. When you look at the way explorations and production work, such as the image here from ‘Well Architect‘, you realise that geographical technologies are critical to the abilities to find and extract oil and gas. They must have played a role in the abilities of the industry to identify, drill and extract in places that were not feasible few decades ago. I remember my own amazement at the first time that I saw the complexity of the information that is being used and the routes that wells take underground, such as what is shown in the image (I’ll add that this was during an MSc project sponsored by Shell). In another project (sponsored by BP), it was just as fascinating to see how paleogeography is used for oil exploration. Therefore, within the complex process of finding and extracting fossil fuels, which involves many engineering aspects, geographical technologies do have an important role, but how important? Should Critical GIScientists or the emerging Critical Physical Geographers explore it?
This brings about the more thorny issue of the role of GIS professionals today and more so with people who are entering the field, such as the students who are studying for an MSc in GIS, and similar programmes. If we accept that most of the fossil fuels should stay underground and not be extracted, than what should we say to students? If the person that involved in working to help increasing oil production does not accept the science of climate change, or doesn’t accept that there is an imperative to leave fossil fuels in the ground, I may accept and respect their personal view. After all, as Mike Hulme noted, the political discussion is more important now than the science and we can disagree about it. On the other hand, we can take the point of view that we should deal with climate change urgently and go on the path towards reducing extraction rapidly. In terms of action, we see students joining campaigns for fossil free universities, with which I do have sympathy. However, we’re hitting another difficult point. We need to consider the personal cost of higher education and the opportunity for well paid jobs, which include tackling interesting and challenging problems. With the closure of many other jobs in GIS, what is the right thing to do?
I don’t have an easy answer, nor can I say that categorically I will never work with the extractive sector. But when I was asked recently to provide a reference letter by a student in the oil and gas industry, I felt obliged to state that ‘I can completely understand why you have chosen this career, I just hope that you won’t regret it when you talk with your grandchildren one day in the future’
Following the last post, which focused on an assertion about crowdsourced geographic information and citizen science I continue with another observation. As was noted in the previous post, these can be treated as ‘laws’ as they seem to emerge as common patterns from multiple projects in different areas of activity – from citizen science to crowdsourced geographic information. The first assertion was about the relationship between the number of volunteers who can participate in an activity and the amount of time and effort that they are expect to contribute.
This time, I look at one aspect of data quality, which is about consistency and coverage. Here the following assertion applies:
‘All information sources are heterogeneous, but some are more honest about it than others’
What I mean by that is the on-going argument about authoritative and crowdsourced information sources (Flanagin and Metzger 2008 frequently come up in this context), which was also at the root of the Wikipedia vs. Britannica debate, and the mistrust in citizen science observations and the constant questioning if they can do ‘real research’.
There are many aspects for these concerns, so the assertion deals with the aspects of comprehensiveness and consistency which are used as a reason to dismiss crowdsourced information when comparing them to authoritative data. However, at a closer look we can see that all these information sources are fundamentally heterogeneous. Despite of all the effort to define precisely standards for data collection in authoritative data, heterogeneity creeps in because of budget and time limitations, decisions about what is worthy to collect and how, and the clash between reality and the specifications. Here are two examples:
Take one of the Ordnance Survey Open Data sources – the map present themselves as consistent and covering the whole country in an orderly way. However, dig in to the details for the mapping, and you discover that the Ordnance Survey uses different standards for mapping urban, rural and remote areas. Yet, the derived products that are generalised and manipulated in various ways, such as Meridian or Vector Map District, do not provide a clear indication which parts originated from which scale – so the heterogeneity of the source disappeared in the final product.
The census is also heterogeneous, and it is a good case of specifications vs. reality. Not everyone fill in the forms and even with the best effort of enumerators it is impossible to collect all the data, and therefore statistical analysis and manipulation of the results are required to produce a well reasoned assessment of the population. This is expected, even though it is not always understood.
Therefore, even the best information sources that we accept as authoritative are heterogeneous, but as I’ve stated, they just not completely honest about it. The ONS doesn’t release the full original set of data before all the manipulations, nor completely disclose all the assumptions that went into reaching the final value. The Ordnance Survey doesn’t tag every line with metadata about the date of collection and scale.
Somewhat counter-intuitively, exactly because crowdsourced information is expected to be inconsistent, we approach it as such and ask questions about its fitness for use. So in that way it is more honest about the inherent heterogeneity.
Importantly, the assertion should not be taken to be dismissive of authoritative sources, or ignoring that the heterogeneity within crowdsources information sources is likely to be much higher than in authoritative ones. Of course all the investment in making things consistent and the effort to get universal coverage is indeed worth it, and it will be foolish and counterproductive to consider that such sources of information can be replaced as is suggest for the census or that it’s not worth investing in the Ordnance Survey to update the authoritative data sets.
Moreover, when commercial interests meet crowdsourced geographic information or citizen science, the ‘honesty’ disappear. For example, even though we know that Google Map Maker is now used in many part
s of the world (see the figure), even in cases when access to vector data is provided by Google, you cannot find out about who contribute, when and where. It is also presented as an authoritative source of information.
Despite the risk of misinterpretation, the assertion can be useful as a reminder that the differences between authoritative and crowdsourced information are not as big as it may seem.
Looking across the range of crowdsourced geographic information activities, some regular patterns are emerging and it might be useful to start notice them as a way to think about what is possible or not possible to do in this area. Since I don’t like the concept of ‘laws’ – as in Tobler’s first law of geography which is stated as ‘Everything is related to everything else, but near things are more related than distant things.’ – I would call them assertions. There is also something nice about using the word ‘assertion’ in the context of crowdsourced geographic information, as it echos Mike Goodchild’s differentiation between asserted and authoritative information. So not laws, just assertions or even observations.
The first one, is rephrasing a famous quote:
‘you can be supported by a huge crowd for a very short time, or by few for a long time, but you can’t have a huge crowd all of the time (unless data collection is passive)’
So the Christmas Bird Count can have tens of thousands of participants for a short time, while the number of people who operate weather observation stations will be much smaller. Same thing is true for OpenStreetMap – for crisis mapping, which is a short term task, you can get many contributors but for the regular updating of an area under usual conditions, there will be only few.
The exception for the assertion is the case for passive data collection, where information is collected automatically through the logging of information from a sensor – for example the recording of GPS track to improve navigation information.
8 July, 2013
The term ‘Citizen Science’ is clearly gaining more recognition and use. It is now get mentioned in radio and television broadcasts, social media channels as well as conferences and workshops. Some of the clearer signs for the growing attention include discussion of citizen science in policy oriented conferences such as UNESCO’s World Summit on Information Society (WSIS+10) review meeting discussion papers (see page ), or the Eye on Earth users conference (see the talks here) or the launch of the European Citizen Science Association in the recent EU Green Week conference.
Another aspect of the expanding world of citizen science is the emerging questions from those who are involved in such projects or study them about the efficacy of the term. As is very common with general terms, some reflections on the accuracy of the term are coming to the fore – so Rick Bonney and colleagues suggest to use ‘Public Participation in Scientific Research‘ (significantly, Bonney was the first to use ‘Citizen Science’ in 1995); Francois Grey coined Citizen Cyberscience to describe projects that are dependent on the Internet; recently Chris Lintott discussed some doubts about the term in the context of Zooniverse; and Katherine Mathieson asks if Citizen Science is just a passing fad. In our own group, there are also questions about the correct terminology, with Cindy Regalado suggestions to focus on ‘Publicly Initiated Scientific Research (PIScR)‘, and discussion on the meaning of ‘Extreme Citizen Science‘.
One way to explore what is going on is to consider the evolution of the ‘hype’ around citizen science through ‘Gartner’s Hype Cycle‘ which can be seen as a way to consider the way technologies are being adopted in a world of rapid communication and inflated expectations from technologies. leaving aside Gartner own hype, the story that the model is trying to tell is that once a new approach (technology) emerges because it is possible or someone reconfigured existing elements and claim that it’s a new thing (e.g. Web 2.0), it will go through a rapid growth in terms of attention and publicity. This will go on until it reaches the ‘peak of inflated expectations’ where the expectations from the technology are unrealistic (e.g. that it will revolutionize the way we use our fridges). This must follow by a slump, as more and more failures come to light and the promises are not fulfilled. At this stage, the disillusionment is so deep that even the useful aspects of the technology are forgotten. However, if it passes this stage, then after the realisation of what is possible, the technology is integrated into everyday life and practices and being used productively.
So does the hype cycle apply to citizen science?
If we look at Gartner cycle from last September, Crowdsourcing is near the ‘peak of inflated expectations’ and some descriptions of citizen science as scientific crowdsourcing clearly match the same mindset.
There is a growing evidence of academic researchers entering citizen science out of opportunism, without paying attention to the commitment and work that is require to carry out such projects. With some, it seems like that they decided that they can also join in because someone around know how to make an app for smartphones or a website that will work like Galaxy Zoo (failing to notice the need all the social aspects that Arfon Smith highlights in his talks). When you look around at the emerging projects, you can start guessing which projects will succeed or fail by looking at the expertise and approach that the people behind it take.
Another cause of concern are the expectations that I noticed in the more policy oriented events about the ability of citizen science to solve all sort of issues – from raising awareness to behaviour change with limited professional involvement, or that it will reduce the resources that are needed for activities such as environmental monitoring, but without an understanding that significant sustained investment is required – community coordinator, technical support and other aspects are needed here just as much. This concern is heightened by statements that promote citizen science as a mechanism to reduce the costs of research, creating a source of free labour etc.
On the other hand, it can be argued that the hype cycle doesn’t apply to citizen science because of history. Citizen science existed for many years, as Caren Cooper describe in her blog posts. Therefore, conceptualising it as a new technology is wrong as there are already mechanisms, practices and institutions to support it.
In addition, and unlike the technologies that are on Gartner chart, academic projects within which citizen science happen benefit from access to what is sometime termed patient capital without expectations for quick returns on investment. Even with the increasing expectations of research funding bodies for explanations on how the research will lead to an impact on wider society, they have no expectations that the impact will be immediate (5-10 years is usually fine) and funding come in chunks that cover 3-5 years, which provides the breathing space to overcome the ‘through of disillusionment’ that is likely to happen within the technology sector regarding crowdsourcing.
And yet, I would guess that citizen science will suffer some examples of disillusionment from badly designed and executed projects – to get these projects right you need to have a combination of domain knowledge in the specific scientific discipline, science communication to tell the story in an accessible way, technical ability to build mobile and web infrastructure, understanding of user interaction and user experience to to build an engaging interfaces, community management ability to nurture and develop your communities and we can add further skills to the list (e.g. if you want gamification elements, you need experts in games and not to do it amateurishly). In short, it need to be taken seriously, with careful considerations and design. This is not a call for gatekeepers , more a realisation that the successful projects and groups are stating similar things.
Which bring us back to the issue of the definition of citizen science and terminology. I have been following terminology arguments in my own discipline for over 20 years. I have seen people arguing about a data storage format for GIS and should it be raster or vector (answer: it doesn’t matter). Or arguing if GIS is tool or science. Or unhappy with Geographic Information Science and resolutely calling it geoinformation, geoinformatics etc. Even in the minute sub-discipline that deals with participation and computerised maps that are arguments about Public Participation GIS (PPGIS) or Participatory GIS (PGIS). Most recently, we are debating the right term for mass-contribution of geographic information as volunteered geographic information (VGI), Crowdsourced geographic information or user-generated geographic information.
It’s not that terminology and precision in definition is not useful, on the contrary. However, I’ve noticed that in most cases the more inclusive and, importantly, vague and broad church definition won the day. Broad terminologies, especially when they are evocative (such as citizen science), are especially powerful. They convey a good message and are therefore useful. As long as we don’t try to force a canonical definition and allow people to decide what they include in the term and express clearly why what they are doing is falling within citizen science, it should be fine. Some broad principles are useful and will help all those that are committed to working in this area to sail through the hype cycle safely.