The Rightful Place of Science: Citizen Science

‘The Rightful Place of Science: Citizen Science’ is a fairly slim and small format book. Darlene Cavalier and Eric B. Kennedy edited this short collection of papers that cadsc_0117me out earlier in 2016. The book is part of a series, from the Consortium for Science, Policy, and Outcomes (CSPO) at Arizona State University. The series aims are for ‘These books are brief, clear, and to-the-point, while at the same time tackling urgent topics across a range of complex techno-scientific subjects. The overall aim is to deliver thought-provoking contributions that explore the complex interactions among science, technology, politics, and society.and Citizen Science is clearly successful in doing this.

The book’s 6 chapters provide an excellent, and indeed, thought provoking, introduction to the field of citizen science. Darlene Cavalier introduce the topic with her personal journey into citizen science, and how local interest, career opportunities, and useful suggestions that led her to come up with initiatives such as Science Cheerleaders and SciStarter.

Eric Kennedy’s chapter provides an overview of citizen science, and importantly, addressing the all too often common question about the quality of the information, emphasising that it’s fitness-for-use that matter. The chapter is written from a perspective of science and policy studies and pays particular attention to the use of citizen science for policy – including the challenges that it faces, the multiple goals that a project might be expected to fulfil, as well as unintended outcome (e.g. undermining government led monitoring). He also highlights the need for policy to support citizen science – from a national level to the institution ethics committee level. This chapter is fairly dense with potential ‘hyperlinks’ and issues that you would want to explore more (including conceptualisation of science in society) and is doing this introduction mostly well.

In an excellent chapter by Caren Cooper and Bruce Lewenstein, the two meanings of citizen science are explored. The one that originate from the Alan Irwin (1995) book, emphasising the responsibility of science to society, which they call ‘democratic’ citizen science, while at the other end of the spectrum they position ‘participatory’ citizen science as practice in which people mostly contribute observations or efforts to the scientific enterprise, which originated with Rick Bonney (1996) work at Cornell Lab of Ornithology. While I’m not 100% convinced that ‘participatory’ is the correct word for the more top down citizen science that is closer to crowdsourcing, citizen science, the chapter is doing a very good job by providing concrete examples for each type of citizen science as well as demonstrating that this is not a dichotomy, and things are more mixed.

Robert Dunn and Holly Menninger chapter on turning learning the life sciences into research through citizen science, as well as David Coil on Citizen Microbiology, provide a vivid demonstration of the potential of citizen science to change existing processes, as well as making the complex process of taking samples and ensuring their quality, more transparent and open. Both chapters provide a lot to consider on how processes of teaching can be enhanced through active participation – such as Dunn and Menninger provocation to turn dissections into outlier detection in physiological studies.

In another outstanding chapter, Lili Bui discusses the important aspects of communicating a project, and what are the necessary ways by which project owners need to consider how their project will be promoted. She is pointing to public service broadcasting as a natural ally of citizen science, and show how such collaboration might work. This is something to watch as the Crowd and the Cloud series is getting ready to be broadcast. The chapter is providing the practical information, but also the first stages of conceptualising how people are going to hear about a given project.

Gwen Ottinger is also providing an excellent summary of social movement based citizen science. These are projects that are sometimes named civic science, and surely fall into either action research or cases of community led project. Ottinger shows the special characteristics of this specific version of citizen science, including the need to allow methods to be ‘hacked’, legitimacy, the consulting role of scientists, and other critical issues. She also demonstrates how tensions between doing the science right, and achieving results with good enough science can, and will, emerge in these situations.

In the final chapter, Cavalier and Kennedy are developing the themes of the book and suggesting the places where citizen science can play a role in decision-making processes.

Overall, the book provides a light introduction to citizen science – not all citizen science is captured, but by reading it you can find what is citizen science and how it can play a role in policy decision. Its chapters are the perfect length to serve in teaching or discussion about citizen science, and the book itself is inexpensive (about £7).

Crowdsourcing the Future?

About a month ago, on 7th December 2016, DR Kingsley Purdam (Manchester) organised a one day workshop on citizen science, and in particular on citizen science from a social science methodological perspective. The day organised with the support of the National Centre for Research Methods (NCRM).

The purpose of the workshop/conference was to explore the future of citizen science and citizen social science methods as research tools. In particular, understanding the different types of applications, methods, the data and the challenges posed. Because the point of view was based on methodologies in social sciences, issues about expertise, divisions of labour, different ways of seeing, data quality, questions about what might still be going undocumented and the ethical issues raised were all discussed.

The workshop was structured around two blocks of discussion – the morning around methods, data and ethics, while the after looked at issues of participation and working in the area of policy, as well as a discussion of the specific issues that need to be discussed for a citizen social science project.

As an introduction, both natural science and social science projects were presented. You can find a summary on twitter of some of the points that came up during the day with the hashtag #crowdfutures.

Some of the important tweets are captured here with comments (bit storify style).

Chris Lintott started the day with a discussion of large-scale, online citizen science projects, with the story of Zooniverse.

People participate in Zooniverse because they want to do something useful, and he pointed to the complexities of combining machine learning with citizen science effort while maintaining motivation and interest.

While I presented after Chris, and mostly talked about a more social theory explanation of what Extreme Citizen Science is – in particular, the creation of technologies that are embedded with a social participatory process. Many of the processes that I described were small-scale, and local. I have also pointed to the growth of citizen science and the Doing It Together Science project that we currently run.

However, in the discussion that followed we agreed that the nature of participation and many of the issues that come in these projects are similar across the scales even if the mechanisms for engagement are different.

Ben Rich (BBC), covered issues of engagement in weather observation that the BBC implemented successfully, with million observations and report in the first year

Hilary Geoghegan (Reading) & Alison Dyke (SEI)  talked about the UK EOF study on the motivation of participants and the ethics of participation, as well as the tensions between contributory and co-created citizen science in environmental research.

Will Dixon (Manchester) described the Cloudy with Pain project which engaged 12,000 participants and receives substantial information. The project also experiments with some access to data and opportunity for analysis by the participants themselves.

Kingsley Purdam (Manchester) talked about the complexity of citizen social science about begging, when the beggars are involved in data collection. Another Manchester-based project looked at linguistic diversity in street signs

The next set of talks raised some important point, including by Erinma Ochu on the process of creating the Robot Orchestra as a participatory DIY electronic and creative process, raising issues about expertise and success (the orchestra is in very high demand); Monika Buscher (Lancaster) emphasising that citizen social science is not about bigger torch to understand reality, but critique science & social science; and Alex Albert (Manchester), who run  project to encourage citizen reporting of empty houses and consider what should be done with them, highlighted the challenges of starting a project and recruiting participants. Liz Richardson (Manchester), talked about the interface between participatory action research and citizen science, and described her work with a community who collected data and asked for guidance on how to analyse it. The three talks by Monika, Alex, and Liz raised many issues about the participation of people in different stages of the research process, and the role of established researchers in such projects.

The last set of talks focused back on ecological and medical projects: Rachel Webster of Manchester Museum explained the museum digitising effort, and how they are making progress one MSc in computing student at a time – the integration of citizen science with small museum activities is a resource challenge, so the work with students require some compromises. There was also a demonstration of setting systems for citizen science and then discovering how they are used:

Lamiece pointed that a challenge with such approach is to get the app downloaded and to see continued use, although so far there are 1500 participants, 800,000 observations. There is also Data challenge of presence/absence reporting to make sense of what the data means.

Ian Thornhill fro mEarthWatch who coordinates the FreshWater Watch project demonstrate how simple data collection tools open up space for participant’s innovations in tools and in data collection. He also provided different models of how projects are run – corporate sponsorship, or by payment from interested communities.

Some of the points in the discussion include the need to balance scientific data collection and activism (especially for projects such as those that Liz Richardson described). Also balancing small scale, deep engagement or large datasets, wide engagement – e.g. for 3 years as researchers on projects that got limited funding and a goal. The need to consider what participation is doing to citizen science, and what science is doing to it? How to balance between the two? and in general, the wider societal impacts of projects cannot be ignored. There are also people that coming from a policy perspective, and try to push for procedural aspects, not interested in engagement issues.

There are also ethical issues such as those that relate to volunteer management – what should be done with contributors that are not doing good work? exclude them? train? ignore them? There is a constant need to think of useful roles and how making people valued for their contribution.

Another set of questions explored what citizen social science does to science? How are issues about ownership,  responsibilities to ensuring data quality integrated into project planning and management?

The Potential of Volunteered Geographic Information (VGI) in Future Transport Systems

dsc01541An aspect of collaborative projects is that they start slowly, and as they become effective and productive, they reached their end! The COST Energic (European Network for Research into Geographic Information Crowdsourcing) led to many useful activities, with some of them leading to academic papers. From COST Energic, we’ve got the European Handbook on Crowdsourced Geographic Information, a paper on VGI quality assessment methods, and more.

One outcome came out from the close collaboration around the summer schools that were organised by the network. Prof Cristina Capineri was the chair of the COST network, and also the organiser of summer schools in Fiesole, near Florence. Prof Maria Attard organised the other summer school of the action, at the University of Malta. Based on our close working relationships (though Maria and I know each other since our PhD studies in CASA) we started working on a joint paper. Maria specialises in transport geography, so the support from COST Energic was a reason to consider how VGI will play out in future transport systems. The paper was published in the journal Urban Planning and the abstract reads:

“As transport systems are pushed to the limits in many cities, governments have tried to resolve problems of traffic and congestion by increasing capacity. Miller (2013) contends the need to identify new capabilities (instead of capacity) of the transport infrastructure in order to increase efficiency without extending the physical infrastructure. Kenyon and Lyons (2003) identified integrated traveller information as a facilitator for better transport decisions. Today, with further developments in the use of geographic information systems (GIS) and a greater disposition by the public to provide volunteered geographic information (VGI), the potential of information is not only integrated across modes but also user-generated, real-time and available on smartphones anywhere. This geographic information plays today an important role in sectors such as politics, businesses and entertainment, and presumably this would extend to transport in revealing people’s preferences for mobility and therefore be useful for decision-making. The widespread availability of networks and smartphones offer new opportunities supported by apps and crowdsourcing through social media such as the successful traffic and navigation app Waze, car sharing programmes such as Zipcar, and ride sharing systems such as Uber. This study aims to develop insights into the potential of governments to use voluntary (crowdsourced) geographic information effectively to achieve sustainable mobility. A review of the literature and existing technology informs this article. Further research into this area is identified and presented at the end of the paper.”

The paper is open, and can be found here

New paper: Associations for Citizen Science: Regional Knowledge, Global Collaboration

When the new journal about Citizen Science established, one of the articles that the editorial team thought should be included is a paper that describe the development of associations dedicated to the practice of citizen science. There are now several of these: the Citizen Science Association (CSA), the European Citizen Science Association (ECSA), and the Australian Citizen Science Association (ACSA).

Following the Citizen Science 2015 conference, under the guidance of Martin Storksdieck, a Professor at the College of Education and School of Public Policy in 
Oregon State University, we set out to write the paper. The end results is a paper that discusses the need for organisations that deal with citizen science and the specific directions that each organisation adopted in order to address the local social, political, and scientific situation in which it evolved.

The abstract read: “Since 2012, three organizations advancing the work of citizen science practitioners have arisen in different regions: The primarily US-based but globally open Citizen Science Association (CSA), the European Citizen Science Association (ECSA), and the Australian Citizen Science Association (ACSA). These associations are moving rapidly to establish themselves and to develop inter-association collaborations. We consider the factors driving this emergence and the significance of this trend for citizen science as a field of practice, as an area of scholarship, and for the culture of scientific research itself.”

Here is the paper itself Storksdieck, M. et al., (2016). Associations for Citizen Science: Regional Knowledge, Global Collaboration. Citizen Science: Theory and Practice.. 1(2), p.10. DOI: http://doi.org/10.5334/cstp.55

UCL Synergies podcast – Congo Citizen Science

The “UCL Synergies podcasts” is series of interviews with researchers who are working on a shared problem from two disciplinary perspective. It is part of the activities to demonstrate how UCL addresses the grand challenges. The series itself is an excellent  demonstration of the issues that come up in interdisciplinary research and you can find it here

As part of this series, Jerome Lewis and I had a conversation with Sue Nelson on our work. The podcast is about 10 minutes,  and you can listen to it here.

GIScience 2016 notes

The bi-annual Geographic Information Science conference is one of the focal point on the field. This year, it was held in Montreal. You can find my talk in a long and separate post. Here are some notes of talks that I took during the meeting.

The conference started with reasons for the location, and a tribute to Roger Tomlinson

Monica Wachwicz, which open the conference with the first keynote, explored her experience in managing a complex set of projects that deal with sensing the environment using geospatial technologies. She summarised her insights:

She aslo described the challenges of recruiting computer scientists, mathematicians, & social scientists to multidisciplinary team.

In the poster session, the work of Daniel Bégin stood out (and he later won an award for it)

Dennis Hlynsky gave the keynote on the second day. As an artist, he is using digital technologies to see the world around him, focusing on the individual and the group. We live in worlds and there are other ‘worlds’ around us – some of too fast, some too slow, some you can’t sense – from gravity to chemistry. He views the creative process as something that is based on guidelines (e.g. Warhol daily procedures), opportunity, being a resident (living in a place and taking it in). Making a playful mess. Critique (is it working, is it not? What my artwork communicate? does it need more or less?). Make sense (we are sense making creatures, telling stories, making sense of things we don’t understand). However, many times he does not know what he is doing and explore things. To witness in a place, what you are witnessing and conveying is important: verbal storytelling, narrative, science and experiments, drawing and painting, photography and film, text, maps, data analysis. We’ve tried to mechanise witness – for example perspective, which force understanding the world from a single point of view. Photography is also a form of mechanisation. There is also the issue of mechanisation in emphasising efficiency which part of industrialisation. The technology changes in photography is important. Until the 1970s, the cost of photographic equipment was limited the opportunity of what is recorded. Since then, the acceleration of sharing photos and evidence change things, with the affordability of cameras in phones. The process of taking photos with phones (which are cameras) make the recording of moments in life much more common, but also the need to switch them off in order to be at the moment. There are many opportunities to do creativity with cameras – for example, providing them to all the students in class, and created a system that allow people to share images, but explicit human intuition to link things, not an automatic tags analysis. There are subsets of the world that communicate with each other, even if they can’t understand it fully.  Interestingly, YouTube is focusing on data driven relationships, while Vimeo is about human led curation. There are different was of organising and understanding the world. The claim that an image is worth a thousand words can be turned on its head – you need to understand the context and meaning of the world, and this is not possible without it.

Helen Couclelis talked about ‘Encyclopedia Gallica of (improbable) event and the why GIScience is not like physics’. The informational standpoint, events, processes, endurance, non-event, do not have a user independent definition. Road networks look different from a perspective of a tourist and biologist, so we need to find a way to create information that support their use. Events are more complex: flood – flood can be an event, process to those in charge of evacuation, occurrences for disaster statistics, noise to everyone else. As metascience – GISCience is a framework for optimising the relation between the interests of information seekers and data in any spatio-temporal domain. She suggest a user-centred GIS with the notion of R-Events to help in search process. The empirical and informational aspects in information systems as distinct epistemic layers.

Genevieve Reid & Renee Sieber compared indigenous ontologies of time. It provide a case for inclusive semantic interoperability, and ensure representation and accessibility for indigenous knowledge. SNAP/SPAN frameworks for ontologies have a very basic notion of time in a Newtonian way and as always progressing and unilinear. In contrast, in TEK, time can be spiral, branch, triangle, cyclical, or double spiral – future that incorporate the future (in Maori culture). Eastern Cree culture see part and present leading to the future. In TEK time is not temporal but social. There are no fix – creation stories include notions of creating a river through a specific story. Time also has an agency. On the basis of these different concepts, she progress to suggest an inclusive model of relationship trough ontological representation. Time is not a simple model but into spatial temporal relations. GIScience can’t ignore the different social constructions of time – excluding indigenous concepts is ontological violence and risk of loss of indigenous knowledge.

Lex Comber et al. talked about “A Moan, a Discursion into the Visualisation of Very Large Spatial Data and Some Rubrics for Identifying Big Questions”, while looking at trends in anti-depressant. Databating meaning manipulation of database. There is an increasing amount of data, and demands (experiences of changing title from GIScience to Data Analytics, create challenges). There is a lack of asking serious questions or knowing what is it for, and ‘letting the data talk for itself’. There is opening of data – for example, GP practice prescription: the practice, the drug, the postcode of the patient. The Postcode can be linked to geography. Demonstrate that it’s possible to producing stupid results by only going data fishing. If we have a plan, on the other hand, we can see urban/rural areas. Need to use: view, refine, and zoom. If you are looking for a needle in a haystack, then making the stack bigger is not making it easier.

Jim Tatcher et al. (delivered by David O’Sullivan) ‘Searching for a common ground (again). Mentioning Golledge et al. 1988 A ground for Common Research. Need to identify common terms and how they are used.  The model of seeing the world as layer cake, is still significant. Harvey Miller mentioned it in 2003 that Euclidean space can be problematic, and it is associated with the quantitative geography. However, in old books that are all sort of representations that look different. From Bunge to Haggett, there are representations that are not Euclidean. The paradigm of GIS caused the adoption of this model. Tobler’s first law actually appeared as ‘throwaway remark’ and travelled through geography in different ways. Need to consider why Euclidean is accepted for granted when in earlier period there were many experimentation.

Has GIScience Lost its Interdisciplinary Mojo?

The GIScience conference is being held every two years since 2000, and it is one of the main conferences in the field of Geographic Information Science (GIScience). It is a special honour to be invited to give a keynote talk, and so I was (naturally) very pleased to get an invitation to deliver such a talk in the conference this year. The title of my talk is ‘Has GIScience Lost its Interdisciplinary Mojo?’ and I’m providing here the synopsis of the talk, with the slides.

My own career is associated with GIScience very strongly. In 1992, as I was studying for my undergraduate studies with a determination to specialise in Geographic Information Systems (GIS) by combining computer science and geography degrees, I was delighted to discover that such studies fall within a new field called GIScience. The paper by Mike Goodchild that announced the birth of the field was a clear signal that this was an area that was not only really interesting, but also one with potential for growth and prospects for an academic career, which was very encouraging. This led to me to a Masters degree which combined environmental policy, computer science, and GIS. During my PhD, I started discovering another emerging area – citizen science, with two main pieces of work – by Alan Irwin and Rick Bonney marking the beginning of the field in 1995 (I came across Irwin’s book while looking into public understanding of science, and learn about Bonney’s work much later). According to OED research, the use of citizen science can be traced to 1989. In short, GIScience and citizen science as a recognised terms for research areas have been around for about the same time – 25 years.

Over this period, I have experienced an inside track view of these two interdisciplinary research fields. I would not claim that I’ve been at the centres of influence of either fields, or that I’ve analysed the history of these areas in details, but I followed them close enough to draw parallels, and also to think – what does it mean to be involved in an interdisciplinary field and what make such a field successful? 

The use of terms in publications is a good indication to the interest in various academic fields. Here are two charts that tell you how GIScience grown until it stalled around 2010, and how citizen science have been quiet for a while but enjoying a very rapid growth now.

First, from Egenhofer et al. 2016 Contributions of GIScience over the Past Twenty Years, showing the total number of publications with the keywords GIS or GIScience, based on a Scopus query for the years 1991 through 2015, executed in July 2015. Notice the peak around 2009-2010.

gisciencepublications

And here is Google Trends graph for comparing GIScience and Citizen Science, showing that in the past 8 years citizen science has taken off and increased significantly more than GIScience:

gisciencecitizenscience

I think that it’s fair to say that these two fields as inherently interdisciplinary.

In GIScience, as Traynor a Williams identify already in 1995: “Off-the-shelf geographic information system software is hard to use unless you have sufficient knowledge of geography, cartography, and database management systems; are computer-literate” and to these observations we need to add statistics, algorithms development, and domain knowledge (ecology, hydrology, transport).

Citizen Science also includes merging knowledge from public engagement, education, science outreach, computer science, Human-Computer Interaction, statistics, algorithms and domain knowledge (e.g. ecology, astrophysics, life science, digital humanities, archaeology).

Both fields are more than a methodology – they are contributing to scientific research on different problems in the world, and only a very reductionist view about what they are will see them as ‘a tool’. They are more complex than that – which is why we have specific scholarship about them, periods of training, dedicated courses and books, conferences and all the rest.

A very shallow comparison will note that GIScience was born as an interdisciplinary field of study, and experience consolidation and focus early on with research agendas, core curriculum which was supposed to lead to stability and growth. This did not happen (see Patrick Rickles comments, from an interdisciplinary research perspective, on this). Take any measure that you like: size of conferences, papers. Something didn’t work. Consider the Esri UC, with its 15,000 participants who are working with GIS, yet only a handful of them seem to be happy with the identity of a GIScientists.

In contrast, Citizen Science is already attracting to its conferences audience in the many hundreds – the Citizen Science Association have 4000 (free) members, The European Citizen Science Association 180 (paid) – and that is in the first 2 years since they’ve been established. It doesn’t have an explicit research agenda, and have an emerging journal, but the field also benefits from multiple special issues – there is almost a competition among them.

As a GIScientist this is a complex, and somewhat unhappy picture. What can I offer to explain it? What are the differences between the two fields that led to the changes and what we can learn from them? It is worth exploring these questions if we want the field to flourish

Engaging with Interdisciplinary research

The wider engagement with these fields is also linked to my personal and direct engagement in GIScience research that goes beyond disciplinary boundaries. Over the years, I was also involved in about 20 multidisciplinary, cross-disciplinary, interdisciplinary, and transdisciplinary projects. I also found myself evaluating and funding x-disciplinary projects (where cross, inter, multi or trans  stand for x). The main observations from all these is that many times, projects that started under the interdisciplinary flag (integrating knowledge from multiple areas), ended with mostly multidisciplinary results (each discipline addressing the issue from its own point of view). However, here are nine lessons that I’ve learned, which can also help evaluating the wider fields of GIScience and citizen science.

First, Get them young & hungry – when established professors are joining an interdisciplinary project, usually they have a clear personal research agenda, and the likelihood that they will be open to radically new ideas about their area is low. You can get excellent multidisciplinary projects with experienced researchers, but it is much harder and rarer to have interdisciplinary or transdisciplinary project – there is too much to lose. That mean that early career researchers are the most suitable collaborators who can develop new directions. At the same time, in terms of job potential and publications, it is very risky for PhD students to get into interdisciplinary research as this can reduce their chances of securing an academic job. With appropriate funding (as we done in Bridging the Gaps) and specific support to people at the more secured stage of early career (after securing a lectureship/assistant professor position), we’ve seen interdisciplinary collaboration evolve.

Second, in x-disciplinary projects, you’ll find yourself being undermined, unintentionally which will hurt. Disciplines have different notion of ‘truth’ and how to get to it (in philosophy: epistemology and ontology). What is considered as an appropriate methodology (e.g. fixation with randomised control trials), how many people need to participate, how they are selected and more. When people from another discipline use these concepts to question your practice it can feel as undermining the expertise, and the disciplinary knowledge that you are offering to the project…

logo-ercThird, there are also cases of being undermined, intentionally. Interdisciplinary proposal are evaluated by experts from different fields, and no matter how much they are told to focus their comments on their discipline, they will comment on other aspects. Moreover, proposal evaluators can assess the novelty in their area, not the overall innovation, reducing the likelihood of ‘outstanding’ mark that make it more likely to get funded. For example, in an early version of what was now funded by both EPSRC and ERC, a Research Challenges Board rejected the proposal because it “seemed so high risk to us is that there are many links in the chain… is it clear that even if everything works there would be real value from these sorts of devices? You use the example that the forest people might be able to tell if there were poachers in the area. Yet can that really be shown? Do forest people understanding probabilistic reasoning? If there any evidence that illiterate people can use maps, digital or otherwise?“. It’s important to note that both ERC and the EPSRC programmes were aimed at risky, interdisciplinary projects, but in more standard programmes, it is difficult to get funded.

Fourth, look out for the disciplinary scrounger. They might not be aware that they are disciplinary scrounger, but this is how it happens: Interdisciplinary research open up new tools and methodologies and people who know how to use them for the research team as a whole. While there is a supposed shared goals that will provide benefits to all sides, a savvy researcher will identify that there is an opportunity for using resources to advance their own research in their discipline, and find ways to do that, even if there are no apparent benefits to the side that give the resources. This act is not necessarily malicious – from the researcher perspective, it is exactly a demonstration of interdisciplinary contribution.

Fifth, in an interdisciplinary research it is critical to develop a common narrative, early. As the project progresses, it will shift and change. Because of the disciplinary differences, it is very easy to diverge and work on different issues, with some relationship to the original proposal. Especially in case where the funder evaluate the project against the proposal (e.g. in Horizon 2020), it’s critical to have a common story. The project can be harmonious and show good progression, but without a common narrative that is shared across the team, there can be troubles when it come to evaluation by external people as the outputs do not all fit neatly to their idea of what the project is about. In another project, Adaptable Suburbs, we deliberately shared reading lists between teams to help understanding each other, which bring us to…

Sixth, highstreetconsider the in-built misunderstanding. Terminology is an obvious one. For Anthropology, scale, from small to large is individual, household, community – and for cartography city is small scale, while house is large scale. However, these are easy – it can take time, and long discussions to discover that you’re looking at the same thing but seeing something completely different. As Kate Jones suggested when she worked on the Successful Suburban Town Centres project. In the image above urban designers see the streets, but not the people, while human geographers who look at census data will tend to see the people, but not the urban structure that they inhibit. There are many other examples of subtle, complex and frustrating misunderstanding that happen in such projects.

Seven, there will be challenges with publications – those that are written. Publications are critical academic outputs, and important for the individuals, teams, and the project as a whole. Yet, they are never easy – different disciplines have very different practices. In some, the first position in the author list is the most important, in another, the last. Some value single author monograph (Anthropology), other conference paper with multiple authors (Computer Science). This creates tensions and a need for delicate discussions and agreement. Moreover, and linked to Six – writing joint publications is an opportunity to expose interdisciplinary misunderstanding, but that make the writing process longer.

Eight, it is important to realise that many times interdisciplinary publications will never be written  – because academic careers, promotion criteria, visibility, and recognition depends on disciplinary practices, within projects disciplinary papers and outputs are written first. The interdisciplinary outputs left to a later stage – and then the project end and they never get written. They are actually dependent on voluntary investment of multiple contributors, which make it very difficult to get them done!

Finally, nine, is the importance of coffee and lunch breaks (and going out together). Team members in interdisciplinary projects are usually coming from different departments, and it is challenging to organise a shared space. However, by putting people together – computer scientists sitting next to a geographer, designer, anthropologists – it is possible to achieve the level of trust, relationship and the development of new ideas that are needed in such projects. In ExCiteS, we have a designated ‘social officer’ for the group.

On the basis of these experiences, I’d argue that Interdisciplinarity is always hard, risky, require compromises, accommodations, listening, and making mistakes. The excitement from the outputs and outcomes does not always justify the price. Frequently, there is no follow-on project – it’s been too exhausting. The analysis that Patrick Rickles done across the literature can provide you with further information on challenges and solutions.

From projects to research fields

Considering the project level challenges, viewing interdisciplinary areas of studies emerging is especially interesting. You can notice how concepts are being argued and agreed on. You can see what is inside and what is outside, and where the boundary is drawn. You can see how methodologies, jargon, acceptable behaviour, and modes of operations get accepted or rejected – and from the inside, you can nudge the field and sometimes see the impact of your actions. Here are some observations about GIScience and citizen science evolution.

First, citizen science seem to be growing organically, without a deliberate attempt to set a research agenda, define core curriculum, or start with nationally focused research centres, in contrast to GIScience, who had all of these. There is an emergent research agenda: data quality, motivations & incentives, interaction design, management of volunteers, and more. These are created according to views of different people who join the research area, opening opportunities for new collaborations. It is noted that GIScience, in practice, allowed for many other areas to emerge – for example crowdsourcing, which was not in the last version of the research priorities that are listed on UCGIS website, and also seemed to stop doing these exercises.

Second, there is an interesting difference in inclusiveness. Although there are different variants of citizen science, across events, conferences and projects, there is an attempt to be inclusive to the different variants (e.g. volunteer computing or ecological observations) though tensions remain and need maintenance. In GIScience, there have been inclusive activities, of workshops that brought together people from Human-Computer Interaction in the late 1980s, or the excellent series of meetings about GIS and Environmental Modelling. There is clear separation, for example in spatial analysis, where different methods are now appearing in ecology, but they are not shared back with the general GIScience. It is worth considering how to make such events and consider active inclusiveness, where researchers from different areas will find their place and reasons to participate.

It might be that citizen science is also more inclusive because of the interaction with people outside academia (participants) and the need to focus on things that matter to them, whereas GIScience has largely been for/by scientists. However, citizen science gets backlash for “not doing REAL science”, but it’s still grown. Maybe, in the process of GIScience trying to validate itself, it’s cut itself off from other research areas (even though GIS use continues to grow)?

Third, there is a sharp difference in the relationship with practitioners – GIScience decided to focus on fundamental questions and laws, while citizen science is a deliberate integration between researchers (the science of citizen science) and practitioners who are running volunteering programmes. The interaction between practice and science is bringing research questions to light and provide a motivation for addressing them with interdisciplinary teams. It might be that separation between science and systems in GIScience need to be blurred a bit to open up new opportunities.
bookcoverFinally, GIScience benefited from having a disciplinary name, and attention by a growing group of researchers who are committed to the field – job titles, positions, journals and conference do matter in terms of visibility and recognition. Citizen science, on the other hand, is only now starting to have a proper home and networks. There are ongoing discussions about what it is, and not everyone in the field is using the term ‘citizen science’ or happy with it. The actual conference that led to the creation of the Citizen Science Association was titled ‘Public Participation in Scientific Research'(!). The coherence and focus on understanding how important key phrases are, more than dislike of their potential meaning is valuable for the coherence of a field and stating that you have knowledge that can be shared with others.

New areas for Interdisciplinary research

To complete this discussion, I point to the opportunities that citizen science open for interdisciplinary collaborations with GIScience – It provides examples for longevity of VGI data sources, that can be used to address different research questions. There are new questions about scales of operations and use of data from the hyper local to the global. Citizen science offer challenging datasets (complexity, ontology, heterogeneity), and also a way to address critical issues (climate change, biodiversity loss). There are also usability challenges and societal aspects.

In final account, GIScience got plenty of interdisciplinary activity in it. There are actually plenty of examples for it. In terms of ‘mojo’ as being attractive for researchers from other area to join in, there are plenty of opportunities – especially if the practice of using GIS within different research and practice problems is included in the framework of GIScience.


This post benefited from discussions and comments from Patrick Rickles, who is our local expert in GIS use in an interdisciplinary settings. You should check his work.