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.


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:


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.

New book: European Handbook of Crowdsourced Geographic Information

COST EnergicCOST ENERGIC is a network of researchers across Europe (and beyond) that are interested in research crowdsourced geographic information, also known as Volunteered Geographic Information (VGI). The acronym stands for ‘Co-Operation in Science & Technology’ (COST) through ‘European Network Researching Geographic Information Crowdsourcing’ (ENREGIC). I have written about this programme before, through events such as twitter chats, meetings, summer schools and publications. We started our activities in December 2012, and now, 4 years later, the funding is coming to an end.

bookcoverOne of the major outcomes of the COST ENERGIC network is an edited book that is dedicated to the research on VGI, and we have decided that following the openness of the field, in which many researchers use open sources to analyse locations, places, and movement, we should have the publication as open access – free to download and reuse. To achieve that, we’ve approached Ubiquity Press, who specialise in open access academic publishing, and set a process of organising the writing of short and accessible chapters from across the spectrum of research interests and topics that are covered by members of the network. Dr Haosheng Huang (TU Wien) volunteered to assist with the editing and management of the process. The chapters then went through internal peer review, and another cycle of peer review following Ubiquity Press own process, so it is thoroughly checked!

The book includes 31 chapters with relevant information about application of VGI and citizen science, management of data, examples of projects, and high level concepts in this area.

The book is now available for download hereHere is the description of the book:

This book focuses on the study of the remarkable new source of geographic information that has become available in the form of user-generated content accessible over the Internet through mobile and Web applications. The exploitation, integration and application of these sources, termed volunteered geographic information (VGI) or crowdsourced geographic information (CGI), offer scientists an unprecedented opportunity to conduct research on a variety of topics at multiple scales and for diversified objectives.
The Handbook is organized in five parts, addressing the fundamental questions:

  • What motivates citizens to provide such information in the public domain, and what factors govern/predict its validity?
  • What methods might be used to validate such information?
  • Can VGI be framed within the larger domain of sensor networks, in which inert and static sensors are replaced or combined by intelligent and mobile humans equipped with sensing devices?
  • What limitations are imposed on VGI by differential access to broadband Internet, mobile phones, and other communication technologies, and by concerns over privacy?
  • How do VGI and crowdsourcing enable innovation applications to benefit human society?

Chapters examine how crowdsourcing techniques and methods, and the VGI phenomenon, have motivated a multidisciplinary research community to identify both fields of applications and quality criteria depending on the use of VGI. Besides harvesting tools and storage of these data, research has paid remarkable attention to these information resources, in an age when information and participation is one of the most important drivers of development.
The collection opens questions and points to new research directions in addition to the findings that each of the authors demonstrates. Despite rapid progress in VGI research, this Handbook also shows that there are technical, social, political and methodological challenges that require further studies and research


Esri Education User Conference talk: Citizen Science & Geographical Technologies: creativity, learning, and engagement

The slides below are from my keynote talk at the Esri Education User Conference 2016. The conference focused on creativity and its relevant to education and the utilisation of GIS (especially Esri software) at different levels of education.

My talk explored the area of citizen science and extreme citizen science and the way geographical technologies contribute to creativity and learning. As I continue to assume that many of the audience don’t know about citizen science, I start with a review of the field as a way to contextualise what we, as a group, try to do.

[The talk is similar, in parts, to other talks that are captured here on my blog (workshop on theory, practice and policy, standards and recommendation for citizen science, or the current developments in ExCiteS). I’m updating the slides with lessons on what seem to work or not in previous talks. Social media is helpful for that – I can see which points people found most useful/meaningful!]

The talk starts with an historical perspective of citizen science, continue with the societal and technical trends that are at the basis of the current growth in citizen science. Having done that, I’m using a typology that looks at domain (academic discipline), technology, and engagement as a way to introduce examples of citizen science activities. I’m using the trailer for the TV series ‘the Crowd & the Cloud’ to recap the discussions on citizen science activities. I also mention the growth of practitioners community through the Citizen Science Associations.

Next, on this basis, I’m covering the concepts and practices of Extreme Citizen Science – what we do and how. I’m using examples from the work on noise, community resource management and earthquake and fire preparedness to demonstrate the concept.

The last part of the talk focuses specifically on creativity and learning from the Citizen Cyberlab project, and I explain the next steps that we will carry out in the Doing It Together Science project. I complete the talk by giving examples for activities that the audience can do by themselves.

Throughout the talk, I’m showing how Esri technologies are being used in citizen science. It wasn’t difficult to find examples – Esri’s GIS is used in BioBlitzes, Globe at Night, links to OpenStreetMap, and support the work that the ExCiteS group is doing. Survey123 and similar tools can be used to create novel projects and experiment with them. ArcGIS Online will be linked to GeoKey, to allow analysis of community mapping efforts. In short, there is plenty of scope for GIS as an integral part of citizen science projects.

Environmental information: between scarcity/abundance and emotions/rationality

The Eye on Earth Summit, which was held in Abu Dhabi last week, allowed me to immerse myself in the topics that I’ve been researching for a long time: geographic information, public access to environmental information, participation, citizen science, and the role of all these in policy making. My notes (day 1 morning, day 1 afternoon, day 2 morning, day 2 afternoon, day 3 morning & day 3 afternoon) provide the background for this post, as well as the blog posts from Elisabeth Tyson (day 1, day 2) and the IISD reports and bulletins from the summit. The first Eye on Earth Summit provided me with plenty to think about, so I thought that it is worth reflecting on my ‘Take home’ messages.

What follows are my personal reflections from the summit and the themes that I feel are emerging in the area of environmental information today. 

wpid-wp-1444166132788.jpgWhen considering the recent ratification of the Sustainable Development Goals or SDGs by the UN Assembly, it is not surprising that they loomed large over the summit – as drivers for environmental information demand for the next 15 years, as focal points for the effort of coordination of information collection and dissemination, but also as an opportunity to make new links between environment and health, or promoting environmental democracy (access to information, participation in decision making, and access to justice). It seems that the SDGs are very much in the front of the mind of the international organisations who are part of the Eye on Earth alliance, although other organisations, companies and researchers who are coming with more technical focus (e.g. Big Data or Remote Sensing) are less aware of them – at least in terms of referring to them in their presentations during the summit.

Beyond the SDGs, two overarching tensions emerged throughout the presentations and discussions – and both are challenging. They are the tensions between abundance and scarcity, and between emotions and rationality. Let’s look at them in turn.

Abundance and scarcity came up again and agin. On the data side, the themes of ‘data revolution’, more satellite information, crowdsourcing from many thousands of weather observers and the creation of more sources of information (e.g. Environmental Democracy Index) are all examples for abundance in the amount of available data and information. At the same time, this was contrasted with the scarcity in the real world (e.g species extinction, health of mangroves), scarcity of actionable knowledge, and scarcity with ecologists with computing skills. Some speakers oscillated between these two ends within few slides or even in the same one. There wasn’t an easy resolution for this tension, and both ends were presented as challenges.


With emotions and scientific rationality, the story was different. Here the conference was packed with examples that we’re (finally!) moving away from a simplistic ‘information deficit model‘ that emphasise scientific rationality as the main way to lead a change in policy or public understanding of environmental change. Throughout the summit presenters emphasised the role of mass media communication, art (including live painting development through the summit by GRID-Arendal team), music, visualisation, and story telling as vital ingredients that make information and knowledge relevant and actionable. Instead of a ‘Two Cultures’ position, Eye on Earth offered a much more harmonious and collaborative linkage between these two ways of thinking and feeling.

Next, and linked to the issue of abundance and scarcity are costs and funding. Many talks demonstrated the value of open data and the need to provide open, free and accessible information if we want to see environmental information used effectively. Moreover, providing the information with the ability of analyse or visualise it over the web was offered as a way to make it more powerful. However, the systems are costly, and although the assessment of the IUCN demonstrated that the investment in environmental datasets is modest compared to other sources (and the same is true for citizen science), there are no sustainable, consistent and appropriate funding mechanisms, yet. Funding infrastructure or networking activities is also challenging, as funders accept the value, but are not willing to fund them in a sustainable way. More generally, there is an issue about the need to fund ecological and environmental studies – it seem that while ‘established science’ is busy with ‘Big Science’ – satellites, Big Data, complex computer modelling – the work of studying ecosystems in an holistic way is left to small group of dedicated researchers and to volunteers. The urgency ad speed of environmental change demand better funding for these areas and activities.

This lead us to the issue of Citizen Science, for which the good news are that it was mentioned throughout the summit, gaining more prominence than 4 years ago in the first summit (were it also received attention). In all plenary sessions, citizen science or corwdsourced geographic information were mentioned at least once, and frequently by several speakers. Example include Hermes project for recording ocean temperatures, Airscapes Singapore for urban air quality monitoring, the Weather Underground of sharing weather information, Humanitarian OpenStreetMap Team work in Malawi, Kathmandu Living Lab response to the earthquake in Nepal, Arab Youth Climate Movement in Bahrain use of iNaturalist to record ecological observations, Jacky Judas work with volunteers to monitor dragonflies in Wadi Wurayah National Park  – and many more. Also the summit outcomes document is clear:  “The Summit highlighted the role of citizen science groups in supporting governments to fill data gaps, particularly across the environmental and social dimensions of sustainable development. Citizen Science was a major focus area within the Summit agenda and there was general consensus that reporting against SDGs must include citizen science data. To this end, a global coalition of citizen science groups will be established by the relevant actors and the Eye on Earth Alliance will continue to engage citizen science groups so that new data can be generated in areas where gaps are evident. The importance of citizen engagement in decision-making processes was also highlighted. ”

However, there was ambivalence about it – should it be seen as an instrument, a tool to produce environmental information or as a mean to get wider awareness and engagement by informed citizens? How best to achieve the multiple goals of citizen science: raising awareness, educating, providing skills well beyond the specific topic of the project, and democratising decision making and participation? It seem to still be the case that the integration of citizen science into day to day operations is challenging for many of the international organisations that are involved in the Eye on Earth alliance.

Another area of challenging interactions emerged from the need for wide partnerships between governments, international organisations, Non-Governmental Organisations (NGOs), companies, start-ups, and even ad-hoc crowds that respond to a specific event or an issue which are afforded by digital and social network. There are very different speeds in implementation and delivery between these bodies, and in some cases there are chasms that need to be explored – for example, an undercurrent from some technology startups is that governments are irrelevant and in some forms of thinking that ‘to move fast and break things’ – including existing social contracts and practices – is OK. It was somewhat surprising to hear speakers praising Uber or AirBnB, especially when they came from people who familiar with the need for careful negotiations that take into account wider goals and objectives. I can see the wish to move things faster – but to what risks to we bring by breaking things?

With the discussions about Rio Principle 10 and the new developments in Latin America, the Environmental Democracy Index, and the rest, I became more convinced, as I’ve noted in 2011, that we need to start thinking about adding another right to the three that are included in it (access to environmental information, participation in decision-making, and access to justice), and develop a right to produce environmental information that will be taken seriously by the authorities – in other words, a right for citizen science. I was somewhat surprised by the responses when I raised this point during the discussion on Principle 10.

Final panel (source: IISD)

Finally, Eye on Earth was inclusive and collaborative, and it was a pleasure to see how open people were to discuss issues and explore new connections, points of view or new ways of thinking about issues. A special point that raised several positive responses was the gender representation in such high level international conference with a fairly technical focus (see the image of the closing panel). The composition of the speakers in the summit, and the fact that it was possible to have such level of women representation was fantastic to experience (making one of the male-only panels on the last day odd!). It is also an important lesson for many academic conferences – if Eye on Earth can, I cannot see a reason why it is not possible elsewhere.

Being philosophical about crowdsourced geographic information

This is a post by Renee Sieber and myself, providing a bit of a background on why we wrote the paper “The epistemology(s) of volunteered geographic information: a critique” – this is in addition to what I’ve written about it in this blog post

Geo: Geography and Environment

By Renée Sieber (McGill University, Canada) and Muki Haklay (University College London, UK)

Our recent paper, The epistemology(s) of volunteered geographic information: a critique, started from a discussion we had about changes within the geographic information science (GIScience) research communities over the past two decades. We’ve both been working in the area of participatory geographic information systems (GIS) and critical studies of geographic information science (GIScience) since the late 1990s, where we engaged with people from all walks of life with the information that is available in GIS. Many times we’d work together with people to create new geographic information and maps. Our goal was to help reflect their point of view of the world and their knowledge about local conditions, not always aim for universal rules and principles. For example, the image below is from a discussion with the community in Hackney Wick, London, where individuals collaborated to…

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Eye on Earth (Day 2 – Morning) – moving to data supply

Eye on Earth (Day 2 – Morning) – moving to data supply The second day of Eye on Earth moved from data demand to supply . You can find my posts from day one, with the morning and the afternoon sessions. I have only partial notes on the plenary Data Revolution-data supply side, although I’ve posted separately the slides from my talk. The description of the session stated: The purpose of the the session is to set the tone and direction for the “data supply” theme of the 2nd day of the Summit. The speakers focused on the revolution in data – the logarithmic explosion both in terms of data volume and of data sources. Most importantly, the keynote addresses will highlight the undiscovered potential of these new resources and providers to contribute to informed decision-making about environmental, social and economic challenges faced by politicians, businesses, governments, scientists and ordinary citizens.

The session was moderated by Barbara J. Ryan (GEO) the volume of data that was download in Landsat demonstrate the information revolution. From 53 scene/day to 5700 scene/day once it became open data – demonstrate the power of open. Now there are well over 25 million downloads a year. There is a similar experience in Canada, and there are also new and innovative ways to make the data accessible and useful.

The first talk was from Philemon Mjwara (GEO), the amount of data is growing and there is an increasing demand for Earth Observations, but even in the distilled form of academic publications there is an explosion and it’s impossible to read everything about your field. Therefore we need to use different tools – search engines, article recommendation systems. This is also true for EO data – users need the ability to search, then process and only then they can use the information. This is where GEO come in. It’s about comprehensive, effective and useful information. GEO works with 87 participating organisations. They promote Open Data policies across their membership, as this facilitate creation of a global system of systems (GEOSS). GEOSS is about supply, and through the GEO infrastructure it can be share with many users. We need to remember that the range of sources is varied: from satellite, to aerial imagery, to under-sea rovers. GEO works across the value chain – the producers, value added organisation and the users. An example of this working is in analysis that helps to link information about crops to information about potential vulnerability in food price.

Mary Glackin (the Weather Corporation), reviewed how weather data is making people safer and business smarter. The Weather Company is about the expression of climate in the patterns of weather. Extreme events make people notice. Weather is about what happen in the 100 km above the Earth surface, but also the 3.6 km average depth of the oceans, which we don’t properly observe yet and have an impact on weather. There are 3 Challenges: keep people safe, helping businesses by forecasting, and engage with decision makers. Measuring the atmosphere and the oceans is done by many bodies which go beyond official bodies – now it includes universities, companies, but also citizens observations which is done across the world (through Weather Underground). The participants, in return, receive a localised forecast for their area and details of nearby observations. It’s a very large citizen science project, and engagement with citizen scientists is part of their work. Forecasting require complex computer modelling – and they produce 11 Billion forecasts a day. Engaging decision makers can be individual fisherman who need to decide if to go out to sea or not. There is a need for authoritative voice that create trust when there are critical issues such as response to extreme events. Another example is the use of information about turbulence from airplanes which are then used to improve modelling and provide up to date information to airlines to decide on routes and operations. Technology is changing – for example, smartphones now produce air pressure data and other sensing abilities that can be used for better modelling. There are policies that are required to enable data sharing. While partnerships between government and private sector companies. A good example is NOAA agreeing to share all their data with cloud providers (Microsoft, Amazon, Google) on the condition that the raw data will be available to anyone to download free of charge, but the providers are free to create value added services on top of the data.

Next was my talk, for which a summary and slide are available in a separate post.

Chris Tucker (MapStory) suggested that it is possible to empower policy makers with open data. MapStory is an atlas of changes that anyone can edit, as can be seen in the development of a city, or the way enumeration district evolved over time. The system is about maps, although the motivation to overlay information and collect it can be genealogy – for example to be able to identify historical district names. History is a good driver to understand the world, for example maps that show the colonisation of Africa. The information can be administrative boundaries, imagery or environmental information. He sees MapStory as a community. Why should policy makers care? they should because ‘change is the only constant’, and history help us in understanding how we got here, and think about directions for the future. Policy need to rely on data that is coming from multiple sources – governmental sources, NGOs, or citizens’ data. There is a need for a place to hold such information and weave stories from it. Stories are a good way to work out the decisions that we need to make, and also allow ordinary citizens to give their interpretation on information. In a way, we are empowering people to tell story.

The final talk was from Mae Jemison (MD and former astronaut). She grow up during a period of radical innovations, both socially and scientifically – civil rights, new forms or dance, visions of a promising future in Start Trek, and the Apollo missions. These have led her to get to space in a Shuttle mission in 1992, during which she was most of the time busy with experiments, but from time to time looked out of the window, to see the tiny sliver of atmosphere around the Earth, within which whole life exist. Importantly, the planet doesn’t need protection – the question is: will humans be in the future of the planet? Every generation got a mission, and ours is to see us linked to the totality of Earth – life, plants and even minerals. Even if we create a way to travel through space, the vast majority of us will not get off this planet. So the question is: how do we get to the extraordinary? This lead us to look at data, and we need to be aware that while there is a lot of it, it doesn’t necessarily mean information, and information doesn’t mean wisdom. She note that in medical studies data (from test with patients) have characteristics of specificity (relevant to the issue at hand) and sensitivity (can it measure what we want to measure?). We tend to value and act upon what we can measure, but we need to consider if we are doing it right. Compelling data cause us to pay attention, and can lead to action. Data connect us across time and understanding a universe grater that ourselves, as the pictures from Hubble telescope that show the formation of stars do. These issues are coming together in her current initiative “100 years starship” – if we aim to have an interstellar ship built within the next 100 years, we will have to think about sustainability, life support and ecosystems in a way that will help us solve problems here on Earth. It is about how to have an inclusive journey to make transformation on Earth. She completed her talk by linking art, music and visualisation with the work of Bella Gaia

After the plenary, the session Data for Sustainable Development was building on the themes from the plenary. Some of the talks in the session were:

Louis Liebenberg presented cybertracker – showing how it evolved from early staged in the mid 1990s to a use across the world. The business model of cybertracker is such that people can download it for free, but it mostly used off-line in many places, with majority of the users that use it as local tool. This raise issues of data sharing – data doesn’t go beyond that the people who manage the project. Cybertracker address the need to to extend citizen science activities to a whole range of participants beyond the affluent population that usually participate in nature observations.

Gary Lawrence – discussed how with Big Data we can engage the public in deciding which problem need to be resolved – not only the technical or the scientific community. Ideas will emerge within Big Data that might be coincident or causality. Many cases are coincidental. The framing should be: who are we today? what are we trying to become? What has to be different two, five, ten years from now if we’re going to achieve it? most organisations don’t even know where they are today. There is also an issue – Big Data: is it driven by a future that people want. There are good examples of using big data in cities context that take into account the need of all groups – government, business and citizens in Helsinki and other places.

B – the Big Data in ESPA experience www.espa.ac.uk – data don’t have value until they are used. International interdisciplinary science for ecosystems services for poverty alleviation programme. Look at opportunities, then the challenges. Opportunities: SDGs are articulation of a demand to deliver benefits to societal need for new data led solution for sustainable development, with new technologies: remote sensing / UAVs, existing data sets, citizen science and mobile telephony, combined with open access to data and web-based applications. Citizen Science is also about empowering communities with access to data. We need to take commitments to take data and use it to transforming life.

Discussion: lots of people are sitting on a lots of valuable data that are considered as private and are not shared. Commitment to open data should be to help in how to solve problems in making data accessible and ensure that it is shared. We need to make projects aware that the data will be archived and have procedures in place, and also need staff and repositories. Issue is how to engage private sector actors in data sharing. In work with indigenous communities, Louis noted that the most valuable thing is that the data can be used to transfer information to future generations and explain how things are done.

Eye on Earth (Day 1 – afternoon) – policy making demand for data and knowledge for healthy living

The afternoon of the first day of Eye on Earth (see previous post for an opening ceremony and the morning sessions) had multiple tracks. I selected to attend Addressing policy making demand for data; dialogue between decision makers and providers

wpid-wp-1444139631192.jpgThe speakers were asked to address four points that address issues of data quality control and assurance, identify the major challenges facing data quality for decision-making in the context of crowd-sourcing and citizen science. Felix Dodds  who chaired the session noted that – the process of deciding on indicators for SDGs is managed through the UN Inter-agency group, and these indicators and standards of measurements need to last for 15 years.  There is now also ‘World Forum on Sustainable Development Data’ and review of the World Summit on Information Society (WSIS) is also coming. The speakers are asked to think about  coordination mechanisms and QA to ensure good quality data? How accessible is the data? Finally, what is the role of citizen science within this government information? We need to address the requirements of the data – at international, regional, and national levels.

Nawal Alhosany (MASDAR institute): Data is very important ingredient in making policy when you try to make policy on facts and hard evidence. Masdar is active throughout the sustainability chain, with a focus on energy. The question how to ensure that data is of good quality, and Masdar recognised gap in availability of data 10 years ago. For example, some prediction tools for solar power were not taking into account local conditions, as well as quality assurance that is suitable to local needed. Therefore, they developed local measurement and modelling tools (ReCREMA). In terms of capacity building, they see issues in human capacity across the region, and try to address it (e.g. lack of open source culture). In Masdar, they see a role for citizen science – and they make steps towards it through STEM initiatives such as Young Future Energy Leaders and other activities.

David Rhind (Nuffiled Foundation): many of the data sets that we want cover national boundaries – e.g. radioactive plum from Chernobyl. When we want to mix population and environment, we need to deal with mixing boundaries and complex problems with data integrity. There are also serious problem with validity – there are 21 sub-Saharan countries that haven’t done household survey sine 2006, so how can we know about levels of poverty today? There is a fundamental question of what is quality, and how can we define it in any meaningful sense. Mixing data from different sources is creating a problem of what quality mean. Some cases can rely on international agreements – e.g. N principles, or the UK regulatory authority to check statistics. Maybe we should think of international standards like in accountancy. In terms of gaps in capacity, there is a quick change due to need for analysis and data scientists are becoming available in the UK, but there is issue with policy makers who do not have the skills to understand the information. Accessible data is becoming common with the open data approach, but many countries make official data less open for security. However, data need some characteristics – need to be re-use , easy to distribute, public and with open licensing. The issue about the citizen science – there are reasons to see it as an opportunity – e.g. OpenStreetMap, but there are many factors that make its integration challenging. There is a need for proper communication – e.g. the miscommunication in L’Aquila

Kathrine Brekke (ICLEI) – perspective from local government. Local government need data for decision-making. Data also make it the city suitable for investment, insurance, and improve transparency and accountability. There are issues of capacity in terms of collecting the data, sharing it, and it is even down to language skills (if it is not available in English, international comparison is difficult). There are initiatives such as open.dataforcities.org to allow sharing of city data. There are 100 sustainability indicators that are common across cities and can be shared. In terms of data quality we can also include crowdsourcing – but then need to ensure that it the data will be systematic and comparable. The standards and consistency are key – e.g. greenhouse registry is important and therefore there is global protocol for collecting the data.

Ingrid Dillo (DANS, Netherlands) there is data deluge with a lot of potential, but there are challenges about the quality of the data and trust. Quality is about fitness for use. DANS aim is to ensure archiving of data from research projects in the Netherlands. Data quality in science – made of scientific data quality but also technical. Scientific integrity is about the values of science – standards of conduct within science. There are issues with fraud in science that require better conduct. Data management in small projects lack checks and balances, with peer pressure as major driver to ensure quality – so open science is one way to deal with that. There are also technical issues such as metadata and data management so it can be used and stored in certified trustworthy digital repository.

Robert Gurney (University of Reading) -in environmental science there is the Belmont Forum e-Infrastructures & data management. The Belmont forum is association of environmental science funders from across the world. The initiative is to deal with the huge increase in data. Scientists are early adopters of technology and some of the lessons can be used from what scientists are doing by other people in the environmental sector. The aim is to deliver knowledge that is needed for action. The infrastructure is needed to meet global environmental challenges. This require working with many supercomputers – the problems are volume, variety, veracity, velocity (Big Data) – we getting many petabytes – can reach 100 Petabytes by 2020. The problem is that data is in deep silos – even between Earth Observation archives. The need to make data open and sharable. There will be 10% of funding going towards e-infrastructure. They created data principles and want to have the principle of open by default.

Marcos Silva (CITES)  Cites is about the trade in engendered species . CITES (since mid 1970s)  regulate trade in multi-billion dollar business with 850,000 permits a year. Each permits say that it’s OK to export a specimen without harming the population. It is data driven. CITES data can help understanding outliers and noticing trends. There are issues of ontologies, schema, quality etc. between the signatories – similar to environmental information. They would like to track what happen to the species across the world. They are thinking about a standard about all the transactions with specimen which will create huge amount of data. Even dealing with illegal poaching and protection of animals, there is a need for interoperable data.

Discussion: Data Shift for citizen generated data for SDG goals. Is there data that is already used? How we are going to integrate data against other types of data? We risk filtering citizen science data out because it follow different framework. Rhind – statisticians are concerned about citizen science data, and will take traditional view, and not use the data. There is a need to have quality assurance not just at the end. The management of indicators and their standards will require inclusion of suitable data. Marcos ask what is considered citizen science data? e.g. reporting of data by citizens is used in CITES and there are things to learn – how the quality of the data can be integrated with traditional process that enforcement agencies use. Science is not just data collection and analysis, such as climateprediction.net  and multiple people can analyse information. Katherine talked about crowdsourcing – e.g. reporting of trees in certain cities  so there is also dialogue of deciding which trees to plant. Ingrid – disagree that data collection on its own is not science. Nawal – doing projects with schools about energy, which open participation in science. Rhind – raised the issue of the need for huge data repository and the question if governments are ready to invest. Gurney – need to coordinate multiple groups and organisations that are dealing with data organisations. There is a huge shortage of people in environmental science with advanced computing skills.

wpid-wp-1444166132788.jpgThe second session that I attended explored Building knowledge for healthy lives opened by Jacqueline McGlade – the context of data need to focus on the SDGs, and health is underpinning more goals then environmental issues. UNEP Live is aimed to allow access UN data – from country data, to citizen science data – so it can be found. The panel will explore many relations to health: climate change, and its impact on people’s life and health. heatwaves and issues of vulnerability to extreme events. Over 40 countries want to use the new air quality monitoring that UNEP developed, including the community in Kibera.

wpid-wp-1444166114783.jpgHayat Sindi is the CEO of i2Institute, exploring social innovations. Our ignorance about the world is profound. We are teaching children about foundation theories without questioning science heroes and theories, as if things are static. We are elevating ideas from the past and don’t question them. We ignore the evidence. The fuel for science is observation. We need to continue and create technology to improve life. Social innovation is important – and she learn it from diagnostic for all (DFA) from MIT. The DFA is low cost, portable, easy to use and safely disposable. The full potential of social innovation is not fulfilled. True scientists need to talk with people, understand their need, and work with them

Maria Neira (WHO) – all the SDGs are linked to health. A core question is what are the environmental determinants of health. Climate change, air quality – all these are part of addressing health and wellbeing. Need to provide evidence based guidelines, and the WHO also promote health impact assessment for major development projects. There are different sectors – housing, access to water, electricity – some healthcare facility lack access to reliable source of energy. Air pollution is a major issue that the WHO recognise as a challenge – killing 7m people a year. With air quality we don’t have a choice with a warning like we do with tobacco. The WHO offering indicators who offer that the access to energy require to measure exposure to air pollution. There is a call for strong collaboration with other organisation. There is a global platform on air quality and health that is being developed. Aim to enhance estimation of the impacts from air quality.

Joni Seager (GGEO coordinating lead author) talking about gender and global environmental outlook. She looks at how gender is not included in health and environmental data. First example – collect gender data and then hide it. Gender analysis can provide better information can help in decision making and policy formation.  Second method – dealing with households – they don’t have agency in education, access to car or food security, but in reality there is no evidence that food security is household level attribute – men and women have different experience of coping strategies – significant different between men or women. Household data is the view of the men and not the real information. Household data make women especially invisible. There are also cases where data is not collected. In some areas – e.g. sanitation, information is not collected. If we building knowledge for healthy life, we should ask who’s knowledge and who’s life?

Parrys Raines (Climate Girl) grown in Australia and want to protect the environment – heard about climate change as 6 years old and then seek to research and learn about the data – information is not accessible to young girls. She built close relationships with UNEP. There are different impacts on young people. She is also sharing information about air quality and pollution to allow people to include youth in the discussion and solutions. Youth need to be seen as a resource across different levels – sharing generation, global thinking. There is need for intergenerational communication – critical. knowledge of data is critical for the 21st century. Need organisations to go out and support youth – from mentoring to monetary support.

wpid-wp-1444166106561.jpgIman Nuwayhid talking about the health and ecological sustainability in the Arab world. There are many Millennium Development Goals MDGs that have been achieved, but most of the countries fell short of achieving them. In ecological sustainability, the picture is gloomy in the Arab world – many countries don’t have access to water. Demand for food is beyond the capacity of the region to produce. Population is expected to double in next 30 years. Poorer countries have high fertility – lots of displacement: war, economic and environmental. Development – there are striking inequities in the region – some of the wealthiest countries and the poorest countries in the world. Distribution of water need to consider which sector should use it. In comparison of health vs military expenditure, the Arab world spend much more on military than on health. There is interaction between environment, population and development. The region ecological footprint is highest and increasing. There are also issues of political instability that can be caused by environmental stresses. Displacement of people between countries create new stresses and question the value of state based analysis. Uncertainty is a major context for the region and science in general.

Discussion: the air quality issue – monitoring is not enough without understanding the toxicity, dispersion. Air pollution are impacted also by activities such as stone quarries. Need to balance monitoring efforts with accuracy and the costs of acting. Need to develop models and methods to think about it’s use. Some urban area of light and noise have also impacts not just on death but on quality of life and mental problems.

Two side events of interest run in parallel:

wpid-wp-1444166098477.jpgThe European Environmental Bureau presented a side event on collaborative research and activist knowledge on environmental justice. Pressure on resources mean extractive industries operate in the south with the outcomes used in the North. There is an increased level of conflicts in the south. The EJOLT project is a network of 23 partners in 23 countries. It’s collaborative research of scientists, grass roots organisations, NGOs and legal organisations. They had a whole set results. A visible result is the Atlas of environmental justice. There is plenty to say about citizen science and how important is that information come from people who are closed to the ground. They work with team in ecological economics, that created a moderated process for collecting and sharing information. The atlas allow to look at information according to different categories, and this is link to stories about the conflict and it’s history – as well as further details about it. The atlas is a tool to map conflicts but also to try and resolve them. The EEB see the atlas as an ongoing work and they want to continue and develop sources of information and reporting. Updating and maintaining the tool is a challenge that the organisation face.

At the same time, the best practice guidelines Putting Principle 10 into action was launched, building on the experience from Aarhus guide, there are plenty of case studies and information and it will be available at on the UNEP website

wpid-wp-1444166160281.jpgThe gala dinner included an award to the sensable city lab project in Singapore, demonstrating the development of personalise travel plans that can help avoiding pollution and based on 30-40 participants who collected data using cheap sensors.