Citizen Science 2017 – Filling the ‘ethics gaps’ in Citizen Science research

The workshop was organised by the ethics working group of the Citizen Science Association, and organised by Anne Bowser – Wilson Center; Lisa Rasmussen – University of North Carolina, Charlotte; Caren Cooper – North Carolina State University and North Carolina Museum of Nature Sciences. The charter for the working group was to identify what are the ethical issues in citizen science. The gap in citizen science is not just mechanisms and regulations, but also that you are likely to fall into an ethical dilemma. The goal is to identify good and inclusive mechanisms for gathering input to a conference in July 2018 on citizen science ethics with people from STS, philosophy, citizen science and other areas. People tend to fall into regulatory aspects of ethical approval, but want to separate it and navigate two systems – ethics as in what you should do and the other is what is done within regulations about human subjects. The expertise that are needed to explore ethical issues includes federal agencies (e.g. EPA), STS scholars. practitioners. Community-based researcher, students, IRB chair, a lawyer.

What are the important ethical issues in citizen science, and identify areas that need to be explored further? liability; outcomes – identify and issue through the project, and then what you do with it?; regulatory aspects of working with human subjects; Technological issues – recording people (audio, image); Non-professional and lack of shared understanding of ethics; Equity, access, and inclusivity; informed consent – how we do it; Transparency – around data ownership and use; Duty of care – to participants in safety and in wellbeing; activism vs. neutrality; organisation without traditional oversight; labour ethics – exploitation; ethics of workarounds and implications to people; Intellectual property and attribution; privacy; roles in technologies and the way that way they facilitate platforms; power relationship within technology; indigenous and traditional knowledge; communication about research integrity; Responsible practices towards the environment; authority/credentials/expertise; Democratisations; community norms; multiple epistemological and ontological approaches toward science and its outcome.

Considering potential ethical framework – can think about regulatory framework, typology framework, other possibilities – Resnik, Elliott and Miller paper on ethics for citizen science, or Vayena & Tasioulas citizen science rights paper or ECSA 10 principles.  There is a framework by Caren Cooper that maps the type of research areas in citizen science that can help in mapping the ethical issues and challenges.

There is clear value in articulating why citizen science as an area deserves special attention in terms of thinking about ethics and the reasons to think about it. There is also a potential of harming the field of citizen science by thinking about the side effect of ethical guidelines – and that can be considered within the lifetime of a project. A report about ethics and some guidelines can assist the field as it grows: there are more people entering and developing projects, and therefore there can be issues emerging that might undermine the field as a whole. It’s therefore used to have a stance about ethics to identify when these are breached. There is also a need for a toolkit with templates and guidelines that can be adapted for a specific project.

The ethics working group of the Citizen Science Association will start collecting case studies and examples of ethics documents that can be used. There is a call for papers to develop a virtual issue for Citizen Science Theory and Practice.

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).

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.

Leveraging the power of place in citizen science for effective conservation decision making – new paper

During the Citizen Science conference in 2015, a group of us, under the enthusiastic encouragement of John Gallo started talking about a paper that will discuss the power of place in citizen science. John provides a very detailed account about the way that a discussion and inspiration during the conference led to the development of the paper. Greg Newman took the lead on the process of writing, and the core analysis was based on classifying and analysing 134 citizen science projects.

My contribution to the paper is mostly in exploration of the concept of place including the interpretation within Human Geography of places as spaces of flows (so the paper cites Doreen Massey). I was also involved in various discussion about the development of the dimensions of place that were included in the analysis, while most of the work was done by Greg Newman, Bridie McGreavy  & Marc Chandler.

The paper is now out and free to read and reuse.

Place-based citizen science framework (a) before and (b) after leveraging the power of place. Note that after leveraging the power of place, the citizen science circle is enlarged to reflect a potential increase in participation, data collection, and quality of conservation decision making and that the overall influence of decision making also grew. Note also that the relative size of Zone One increased while the inherent capacity of the power of place remained the same size.
Place-based citizen science framework (a) before and (b) after leveraging the power of place. Note that after leveraging the power of place, the citizen science circle is enlarged to reflect a potential increase in participation, data collection, and quality of conservation decision making and that the overall influence of decision making also grew. Note also that the relative size of Zone One increased while the inherent capacity of the power of place remained the same size.








While it is, for me, expected that place will have an important role in citizen science, it is excellent to see that the analysis supported this observation through consistent classification of citizen science projects across three collections. The model above suggest how it can be used.

The paper development process, however, demonstrate the power of cyberspace, as the team met regularly online and shared documents, details and drafts along the way, with important regular online meeting that help it to come together. The paper started with all of us at the same place and at the same time, but this interaction was enough to sustain our team work all the way to publication.

The paper is open access and the abstract for it is:

Many citizen science projects are place-based – built on in-person participation and motivated by local conservation. When done thoughtfully, this approach to citizen science can transform humans and their environment. Despite such possibilities, many projects struggle to meet decision-maker needs, generate useful data to inform decisions, and improve social-ecological resilience. Here, we define leveraging the ‘power of place’ in citizen science, and posit that doing this improves conservation decision making, increases participation, and improves community resilience. First, we explore ‘place’ and identify five place dimensions: social-ecological, narrative and name-based, knowledge-based, emotional and affective, and performative. We then thematically analyze 134 case studies drawn from (n = 39), The Stewardship Network New England (TSN-NE; n = 39), and Earthwatch (n = 56) regarding: (1) use of place dimensions in materials (as one indication of leveraging the power of place), (2) intent for use of data in decision-making, and (3) evidence of such use. We find that 89% of projects intend for data to be used, 46% demonstrate no evidence of use, and 54% provide some evidence of use. Moreover, projects used in decision making leverage more (t = − 4.8, df = 117; p < 0.001) place dimensions (View the MathML source= 3.0; s = 1.4) than those not used in decision making (View the MathML source= 1.8; s = 1.2). Further, a Principal Components Analysis identifies three related components (aesthetic, narrative and name-based, and social-ecological). Given these findings, we present a framework for leveraging place in citizen science projects and platforms, and recommend approaches to better impart intended outcomes. We discuss place in citizen science related to relevance, participation, resilience, and scalability and conclude that effective decision making as a means towards more resilient and sustainable communities can be strengthened by leveraging the power of place in citizen science.

Patterns of contribution to citizen science biodiversity projects increase understanding of volunteers’ recording behaviour

One of the facts about academic funding and outputs (that is, academic publications), is that there isn’t a simple relationship between the amount of funding and the number, size, or quality of outputs. One of the things that I have noticed over the years is that a fairly limited amount (about £4000-£10,000) are disproportionately effective. I guess that the reason for it is that on the one hand, it allow a specific period of dedicated time, but the short period focuses the mind on a specific task.

A case in point is the funding through the UCL Grand Challenges Small Grants programme. In 2014, together with Dr Elizabeth Boakes and Gianfranco Gliozzo, I secured funding for a short project on ‘Using citizen science data to assess the impact of biodiversity on human wellbeing‘. We have enlisted other people to work with us, and this has led the analysis of citizen science contributions across London. On the basis of this work, and in collaboration with researchers in ExCiteS (Gianfranco Gliozzo, Valentine Seymour), GiGL (Chloe Smith), Biological Records Centre (David Roy), and the Open University (Martin C. Harvey), we have developed a paper that is now published in Scientific Reports. The paper experienced a rejection and subsequent improvements along the way, which have made its analysis more robust and clear. Lizzie’s perseverance with the peer reviews challenges was critical in getting the paper published.

At the core of the paper is examination of the information from citizen science projects, and using this information to understand the behaviour of the volunteers, and what we can learn from this about biodiversity citizen science projects in general.

The paper full citation is: Boakes, E., Gliozzo, G., Seymour, V., Harvey, M.C., Roy, D.B., Smith, C., and Haklay, M., 2016, Patterns of contribution to citizen science biodiversity projects increase understanding of volunteers’ recording behaviour, Scientific Reports

The abstract of the paper reads:

Citizen science has become a well-established method of biological recording but the opportunistic nature of biodiversity data gathered in this way means that they will likely contain taxonomic, spatial and temporal biases. Although many of these biases can be accounted for within statistical models, they are usually seen in a negative light since they add uncertainty to biodiversity estimates. However, they also give valuable information regarding volunteers’ recording behaviour, thus providing a way to enhance the fit between volunteers’ interests and the needs of scientific projects. Using Greater London as a case-study we examined the composition of three citizen science datasets – Greenspace Information for Greater London (GiGL), iSpot and iRecord – with respect to recorder contribution and spatial and taxonomic biases. We found each dataset to have its own taxonomic and spatial signature suggesting that volunteers’ personal motivations for recording may attract them towards particular schemes although there were also patterns common to all three recording systems. We found most volunteers contribute only a few records and are active for one day only. Our analyses indicate that species’ abundance and ease of identification of birds and flowering plants are positively associated with number of records, as was plant height. We found clear hotspots of recording activity, blue space (waterbodies) being associated with birding hotspots. We note that biases are accrued as part of the recording process (e.g. species’ detectability, media coverage) as well as from volunteer preferences.

Published: Why is Participation Inequality Important?

bookcoverI’ve mentioned the European Handbook for Crowdsourced Geographic Information in the last post, and explained how it came about. My contribution to the book is a chapter titled ‘Why is Participation Inequality Important?. The issue of participation inequality, also known as the 90:9:1 rule, or skewed contribution, has captured my interest for a while now. I have also explored it in my talk at the ECSA conference on ‘participatory [citizen] science‘ and elsewhere.

In this fairly short chapter what I am trying to communicate is that while we know that participation inequality is happening and part of crowdsourced information, we need to consider how it influences issues such as data quality, and think how it come about. I am trying to make suggest how we ended with skewed contributions – after all, at the beginnings of most projects, everyone are at the same level – zero contribution, and then participation inequality emerge.

I have used the iconic graph of contribution to OpenStreetMap that Harry Wood created, but the chapter is discussing other projects and activities where you can come across this phenomena.

Here is a direct link to the chapter, and I’ll be very happy to hear comments about it!


Algorithmic governance in environmental information (or how technophilia shape environmental democracy)

These are the slides from my talk at the Algorithmic Governance workshop (for which there are lengthy notes in the previous post). The workshop explored the many ethical, legal and conceptual issues with the transition to Big Data and algorithm based decision-making.

My contribution to the discussion is based on previous thoughts on environmental information and public use of it. Inherently, I see the relationships between environmental decision-making, information, and information systems as something that need to be examined through the prism of the long history that linked them. This way we can make sense of the current trends. This three area are deeply linked throughout the history of the modern environmental movement since the 1960s (hence the Apollo 8 earth image at the beginning),  and the Christmas message from the team with the reference to Genesis (see below) helped in making the message stronger .

To demonstrate the way this triplet evolved, I’m using texts from official documents – Stockholm 1972 declaration, Rio 1992 Agenda 21, etc. They are fairly consistent in their belief in the power of information systems in solving environmental challenges. The core aspects of environmental technophilia are summarised in slide 10.

This leads to environmental democracy principles (slide 11) and the assumptions behind them (slide 12). While information is open, it doesn’t mean that it’s useful or accessible to members of the public. This was true when raw air monitoring observations were released as open data in 1997 (before anyone knew the term), and although we have better tools (e.g. Google Earth) there are consistent challenges in making information meaningful – what do you do with Environment Agency DSM if you don’t know what it is or how to use a GIS? How do you interpret Global Forest Watch analysis about change in tree cover in your area if you are not used to interpreting remote sensing data (a big data analysis and algorithmic governance example)? I therefore return to the hierarchy of technical knowledge and ability to use information (in slide 20) that I covered in the ‘Neogeography and the delusion of democratisation‘ and look at how the opportunities and barriers changed over the years in slide 21.

The last slides show that despite of all the technical advancement, we can have situations such as the water contamination in Flint, Michigan which demonstrate that some of the problems from the 1960s that were supposed to be solved, well monitored, with clear regulations and processes came back because of negligence and lack of appropriate governance. This is not going to be solved with information systems, although citizen science have a role to play to deal with the governmental failure. This whole sorry mess and the re-emergence of air quality as a Western world environmental problem is a topic for another discussion…