The last day of the BES/Sfé meeting was in the mood of celebration, so a session dedicated to celebrating citizen science was in place.  My notes from first day and the second day are in previous posts. These notes are long…

Before the session, in a symposium on tree health, Michael Pocock (CEH) presented ‘Monitoring to assess the impacts of tree diseases: integrating citizen science with professional monitoring‘. Ash die-back is important, and in the rest of Europe, (e.g. Denmark, Lithuania or Poland) there are losses of 60-90% but there was very little work done on monitoring the biodiversity impact of the disease in general. There is a clear lack of knowledge on the impacts on biodiversity in general – how suitable are existing surveys, how they can enhance? In a work that he done with Shelley Hinsley they reviewed 79 relevant studies, from volunteers to national professional survey and local studies. They tried to answer questions such as: What kind of things can be impacted? they identified all sort of impacts - trophic networks, structural, cascading, and ecosystem functions. They looked at different receptors in different contexts – from animals and plants on the receptors, to where they are located as context – woodland, or hedgerow. They found that woods are fairly well monitored, but how much professionals will continue to monitor it with budget cuts is an issue. Ecosystem function is very poorly monitored. The recommendations of the report are that current ongoing activities are suitable and maybe should be modified a bit to make them better (e.g. asking another question in a survey) – they didn’t recommend brand new surveys. The report is available here . If we want future proof monitoring that deal with the range of tree disease and other issues – we need a better ‘spine’ of monitoring work (in the report on page 5), but improve the integration of information and synthesis between survey. Co-location of monitoring site can be great, but actually, there are specific reasons for the locations of places in each scheme so it’s not easy to do so. In addition, volunteers based monitoring require investment in maintenance. He completed his talk with more general citizen science issue that we can learn from this work – the national plant monitoring scheme is to be launched in 2015, and there are some specific focused on lichens and other issues that require specialist knowledge in survey programmes like Splash. Mass participation is useful in some cases, but there is an issue how much recording effort is quantified – there is a big differentiation in ability to monitor species across the country and the ability of participants to record information. The retention of volunteers in mass projects is an issue – only 10% continue after a year. In enthusiasts recruitment you get higher numbers 20% that continue to be involved. The most exciting opportunity that he see is in  hypothesis-led citizen science, like the Concker Tree Science project.

The ‘Celebrating Citizen Science’ session was at the  final group of sessions of the conference, but was very well attended. Chaired by  Michael Pocock, who, together with Helen Roy, runs the BES Citizen Science SIG.

Romain Julliard (Muséum national d’Histoire naturelle)  provided an overview of citizen science activities in France in his talk ‘Biodiversity monitoring through citizen science: a case study from France’. The starting statement was that unskilled amateurs from the general public can provide good information. The museum have a role in monitoring biodiversity at the national – common species are good indicators, the appropriate for studying global changes and the general public is interested in ‘ordinary Nature’ – the things that we see every day. Scientists alone cannot monitor biodiversity over a big space such as a country, so citizens can help to collect data on a country scale and they are already spread across the country. The trade-offs of using citizens as observers include skills vs. numbers of participants – there are only few experts and enthusiasts. Another issue is sampling design: are you aiming for representativeness of where people are or do you send observers to specific locations to do the survey. There is a need for a simple protocol for volunteers. Much simpler than procedures in a research station professionals. They started with French Bird Breeding Survey in coordination with NGOs like LPO and others – with over 2000 squared that are being observed since 1989 and over 1000 provide long-term monitoring. Now they have skilled amateur schemes – monitoring bats, butterflies and much more. They started their programmes in 2005 with butterfly programme, pollinating insect survey from photographs (Spipoll) in 2010 and garden bird watch in 2012 among others – new programmes especially in the past 5 years . Spipoll provides a good example of the work that they are doing. Pollinators are useful to raise awareness and explain multi-factor pressures on the environment. 2014-12-12 13.14.25The are many sampling sites and thousands of flowers dwelling insects in France. They Spipoll protocol starts with 20 minutes ‘safari-photo’ which mean that you select a flower and take photos of each visiting insects. Second step is to select the best single photo for each insect that was sampled. Third step to name each insect from 630 possibilities – and they create an online tool that helps the identification. Final step – share the collection with other people. Once photos are shared, there are plenty of comments from other participants. The participants are encouraged to help each other observations and there is also expert participation in identification. By now, they have over 600 regular participants, 18,000 collections, and 155,000 photos. Many of the participants are not experts in biological recording but have interest in photography. in terms of data quality they looked for precision, repeatability (how close the process was to the protocol). The social control help in improving quality, and the representativeness can be done in explicit sampling design but also in post-study statistical analysis. Beginners tend not to follow the protocol, but other people are helping them and within 3-4 iterations, people are learning the protocol and follow it.

Helen Roy (CEH) talk (with Harding, Preston, Pocock and Roy) ‘Celebrating 50 years of the Biological Records Centre. She gave some key achievements that also appear in a booklet on the 50 years of BRC. The BRC was established in the 1960s to support volunteer recording in the UK – they have now a team of 14 permanent staff. 85 different recording schemes from flee to bees, ladybirds and many other groups. Recording schemes are running by volunteers coordinators – so support is provided by printing newsletters, publishing atlases, etc. They cover a lot of taxa – plants and animals. Over the decades, they have long-term datasets which lead to distribution atlases. Over 80m records. UK biodiversity indicators for the UK government are collected by volunteers and used in decision-making – they are now growing from 24 indicators to include pollinators and other elements. Another area of importance is biological invasions as it cost the UK over 12 billion EUR a year – and not only to look at existing species but also to look forward about the threats – and because volunteers are so knowledgeable, they contributed to horizon scanning work. Work on surveillance and monitoring extend to the general public with publicity – this way they for example got information that Raccoons are being seen in the UK. Another important aspect of BRC data is the ability to use it to understand the decline of native species – for example understanding changes in native ladybird species. Finally, the information is very important in climate change scenarios and use the information about habitats can help in interpreting data and predict future directions.

In the work of the BRC, technology is becoming an important driver – they share it through the NBN gateway, and also apps and websites such as iSpot, iRecord and other bits are helping in developing new sources of information. In summary, to deal with environmental challenges that we’re currently facing cannot be done without this information and interpretation by volunteers. She finished with a big thank you to the many volunteers recorders.

In ‘How to use data generated by general public of a citizen science program for conservation purpose’ Nathalie Machon (Muséum national d’Histoire naturelle) explored another successful French study. They see importance in preserving biodiversity in cities – regulate city climate, dealing with air pollution, contributing to public health etc. In cities, most of the biodiversity is in parks and gardens but the urban matrix is permeable to many animal species such as pollinators. The potential of connection between green spaces is important to create a network in the city. How the structure and management of cities influence biodiversity? was a research question that the programme ‘sauvages de ma rue‘ was set to explore. Since 2011 participants share information about wild-flowers in their own streets. When the programme started, they wanted people to learn to recognise species near them and collect information about the distribution of plants in their area . The protocol is fairly simple – identify street, collect data about plants in different habitats (cracks, walls) and send the information. They created  a guide to help people identify species and also created a smartphone app. Usually people start by providing data about their street, but the programme grew and now they have groups and organisations that deal with naturalist activity and they send a lot of data from many streets in the same place. The organisations can be about sustainability, schools university or nature enthusiasts. They receives 40,660 data points by 2014 which provided the basis for her analysis.

After correction, they had reliable 20,000 data points in 38 cities and 2500 pavements – they check the richness of pavements and the obvious factor is the length (of course) but in about 100m there is a levelling in terms of species. They found that the structure of the street is important – if it is only in cracks, there are less species. The richness is not correlated to population density, but in large urban area (Paris) there is a significant decline toward the centre. They also look at pollination – and found that the number of pollinators is correlated to the human density of the city but not correlated to the distance to the centre of the city, apart from the case in Paris. They also seen increase with habitat types in a pavement. In terms of cities, they discovered that Nantes, Brest and Angers are doing well. However, they are aware that there is an observer effect on the results. Observers were shown to be good as botanists. In summary, they’ve learned that insect pollinated species are easy to recognise and it’s possible to carry out such studies effectively with lightly trained volunteers.

Anne-Caroline Prévot (CESCO – Muséum nationa l’Histoire Naturelle) reviewed her research on ‘Short and long-term individual consequences of participation to citizen-science projects’ in an approach that combines environmental psychology and ecology. There is growing concern on separation between people and nature: extinction of experience (Pyle 2003, Miller 2005) or environmental generational amnesia (Kahn 2002). There is a need engagement of majority of citizens to change their approach. In the psychology field  , there is Stern influential piece from 2000 on environmentally significant behaviour, linking individual to different aspects of pro-environmental behaviour. Identifying social and personal factors . On the other hand, in citizen science programme there are multiple goals – contribute to ecological science ; educate people to acquire knowledge on biodiversity; etc. There is also potential of reconnection to nature – so the  question that she addressed “Did citizen science changed biodiversity representation and knowledge? environmental values? pratcial knowledge? skills?” (all these are based on Stern framework). She looked at the butterfly collection programme and interview 30 regular volunteers who participate every year – They found that they were confident in science, and they discovered new aspects of biodiversity through participation and change their gardening practices. This can change representation but they were environmentally concern to start with. There was no issue of group identity  with this group of volunteers. The second study looked at a programme at school (vigienature école) with 400 pupils from 29 classes in 11-13 age group. They use a questionnaire to understand environmental value and other activities outside schools. In addition, they asked the children to draw an urban garden. Each drawing was analysed for natural elements, built elements and humans. Participation in nature monitoring showed higher presence of nature in drawing but no difference in environmental values. They think that it probably changed representation, but not values, there was no assessment of skills and there was some aspect of group social identity. In summary citizen science initative may change knwoeldge and attitdue of volunteers but this require attention and more evaluation.

Rachel Pateman (SEI) presented the an MSc project carried out by Sian Lomax  under the supervision of Sarah West (SEI) on ‘A critical assessment of a citizen science project‘. It’s an assessment of the science and impact of participants from the OPAL Soil and Earthworm Survey. Aims of citizen science are to answer scientific questions, but also to provide benefit to participants – learning, fun, change behaviours, or information for lobbying on behalf of nature. The challenges are how to find inclusive methods and have good quality data. The participants aim are not simple – there is not simple link between participation and pro-environmental behaviour. The way to deal with that is to evaluate and reflect critically during the development of a citizen science project, and inform the design process (this remind me a lot of Amy Fowler’s thesis, also about OPAL). The OPAL programme is aimed to be educational, change of lifestyle and inspire new generation of environmentalists and greater understanding of the environment. Sian evaluate the soil and earthworm survey which are usually run with an instructor (community scientist) but also can be done by ordering a self obtained pack. The methods – dig a pit, identify worms, and identify properties of the soil and then submit the inforamtion. The aim is that participants wil learn about soil properties and get interested in environmental issues. Sian recruited 87 participants from ages 5 to 60 and also evaluated the observations of participants in the lab, as well as running a questionnaire with participants. She found fairly poor results  (around 40% accurate) in comparison to her own analysis. The results are that 39% identified correctly, 44% functional group, 46% identified as immature – the reliability of the data that adult observers done is better. Results – ID to species level is challenging, especially without help (she didn’t trained the participants) and therefore there is a need of an OPAL community scientist to be an instructor. There was not enough testing of the material at the beginning of the survey and it haven’t been improved since 2009. There is a need to verify records – but should be emphasised further and included in apps. However, despite these limitation, the OPAL survey did yield useful information and they managed to use the data to find abundance of information. Only in 29% of the cases she agreed with participants about the classification of soil granularity. When evaluating the pH of the soil – 63% was within the correct category of acid/alkaline but not correct on the value – the issue might be with the instrument that was provided to participants and yields wrong reading.

From @Simon_Wilcock

In terms of knowledge and experience – the questionnaire was done before, immediately after the survey and then 3 months later. Knowledge increased immediately after but drop-off after – so conclusion is that need to reinforce it after the event. In terms of interest in nature they didn’t find difference – but that because there was high level of interest to start with.

Jodey Peyton (CEH/BRC)  ‘Open Farm Sunday Pollinator Survey: Citizen science as a tool for pollinator monitoring?‘. The decline in pollinators in the UK is a cause of concern. Their estimated value is £510 m a year. The Big Bumbelebee discovery is an example for a project that focus on pollinators. However, we’re lacking abundance data about them. The Open Farm Sunday is a project to open farms to the public (run by LEAF) and about 4 years ago they contacted CEH to do some work with visitors collect information on pollinators

They ask participants to observe a 2×2 m of crop and non-crop area. They have an ecologists on site so they do the same as the participants – carry 2 min observations in both habitats. The event included teaching people the process and giving them information. The forms use to be 4 pages but turned out to be too complex so simplified a form with just 2 pages. They also reduce time from 5 min to 2 min. They run  surveys in 2012 to 2014 with different number of farms – and looked at different factors during the day. They found that public was over-recording (compare to ecologists), not by much – they also got data from other parts of the plant so not only on the flowers because they wanted to report something. Conclusions – on the broad level public data was similar to ecologists. Lots of interest and enthusiasm and understand what they’re seeing. It is great opportunity to highlight the issue of pollinator. Want to run it every second year because of the effort of the ecologists on the day. They also want to deal with challenge of ‘recording zero. Want to see more collaboration with universities and schools.

Charlotte Hall (EarhtWatch Institute) provided an overview of FreshWater Watch: lessons from a global mass Citizen Science programme. The programme focused on fresh water quality. A global programme that look at water quality in urban areas – each location they partner with local research institute, and Earthwatch bring the citizen scientists with the local researchers. The data that is collected is managed by EarthWatch on a specially designed website to allow sharing knowledge and communictation. The evolving motivation of participants, they looked at Rotman et al 2012 model. Initial involvment stemming from interest or existing knowledge, although in the case of EarthWatch they are getting employees of Shell or HSBC who sponsor them, they also work with teachers in Teach Earth and also expanding to work with local groups such as Thames 21 or Wandle Trust. They have over 20 research partners. With such a mix of researchers, participants and organisations, there are different motivations from different directions. They start with training in person and online Research and learning- EarthWatch is interested in behaviour change, so they see learning as a very important issue and include quizzes to check the knowledge of participants. They pay special attention to communication between EarthWatch and the scientists and between EarthWatch and the citizen scientists. There is a community feature on the website for citizen scientists and also for the scientists. There is also an app with automated feedback that tell them about the outcomes of the research they are doing. They have an element of gamification -points on communication, science and skills that participants gained and they can get to different levels. They try to encourage people to move to the next step so to continue their involvement through learning in webinars, refresher session, research updates, points and prizes and even facility for the participants to analyse the data themselves. Involvement in FreshWater watch is exhibiting participation inequality. 2014-12-12 14.43.10They would like to make it shallower but it is very strongly skewed. In Latin America there is better participation, and also differences in participation according to the researcher who lead the activity. This is new citizen science approach for EarthWatch, with different audience, so it’s important to re-evaluate and understand participants. EarthWatch is still learning from that and understanding motivation.

Emma Rothero (Open University) Flight of the Fritillary: a long-running citizen science project linking Snakeshead fritillaries flowers and bumblebees. The work started in 1999, this is a rare plant that is growing only in few places in the UK. The Bees are critical to the flower, and they set a 15% secondary count to evaluate the success of volunteers. They also started winter workshops for discussions. To engage volunteers, they’ve done wide advertising and also used naturalist networks. She described a comparison between three sites where monitoring was carried out this year . In Lugg Meadow the monitoring is done during guided walks and family outreach events. In North Meadow, many people come to see – so they have a gate presence and offered free lunch for volunteers. In Clattinger Farm they haven’t done any specific activity. In 2008 – 20011 only 20 volunteers, now they’ve got 90 volunteers, and about 30-40 who come to winter workshops. Level of volunteering – once 120 , 40 participated twice and 20 three times – there is some enthusiastic people who do it regularly. The volunteers survey show that 88% heard about the monitoring project by word of mouth (despite the advertising and media access), and 87.5% are already recorders – but 88% thought that they had improved their skills. and 65% said that they improve their skills. 54% would like to get involved in other aspects of the project, and 100% enjoyed the activity. In terms of comparison with recounts – they do 4000 1sq m quads using very accurate (1 cm) GPS. They see that there wasn’t difference between recounts in some sites but significantly difference in another site (because of difficulties in frame orientation so implementation of the protocol) – recognising problem in their method. There is also scientific discovery, where they found a case that plants didn’t appear one year but bounced back the next year.

There was no time for much discussion, but a question that was raised and discussed shortly is that most of the projects are ‘top-down’ and led by the scientists, so what is the scope for co-created projects in the area of ecological observations and monitoring?

 

A citizens observatory is a concept that evolved at EU policy circles, defining the combination of participatory community monitoring, technology and governance structures that are needed to monitor/observe/manage an environmental issue. About two years ago, the EU FP7 funded 5 citizens observatory projects covering areas from water management to biodiversity monitoring. A meeting at Brussels was an opportunities to review their progress and consider the wider implications of citizen science as it stand now. The meeting was organised and coordinated by the group in the Directorate General Research and Innovation that is responsible for Earth Observations (hence the observatory concept!).  The following are my notes from the meeting.

They are very long and I’m sure that they are incoherent at places! 

From Commons Lab The meeting was opened with Kurt Vandenberghe (Director Environment, DG R&I). He suggested that citizens observatories contribute to transparency in governance – for example, ensuring that monitoring is done in the correct place, and not, as done in some member states, where monitoring stations are in the places that will yield ‘useful’ or ‘acceptable’ results but not representative: “Transparency is a driver in intrinsic ethical behaviour”. There is also value in having citizens’ input complementing satellite data. It can help in engaging the public in co-design of environmental applications and addressing environmental challenges. Examples for such participation is provided in Marine LitterWatch and NoiseWatch from EEA and development of apps and technology can lead to new business opportunities. The concept of earth observations is about creating a movement of earth observers who collect information, but also allow citizens to participate in environmental decision-making. This can lead to societal innovation towards sustainable and smart society. From the point of view of the commission DG R&I, they are planning to invest political and financial capital in developing this vision of observatories. The New calls for citizens observatories demonstrators is focusing on citizens’ participation in monitoring land use and land cover in rural and remote areas. Data collected through observatories should be complementing those that are coming from other sources. The commission aim to continue the investment in future years – citizen science is seen as both business opportunities and societal values. A successful set of project that end by showing that citizen observatories are possible is not enough – they want to see the creation of mass movement. Aim to see maximising capital through the citizens observatories. Optimising framework condition to allow citizens observatories to be taken up by member states and extended, implemented and flourish. Some of the open questions include how to provide access to the data to those that collected it? How can we ensure that we reach out across society to new groups that are not currently involved in monitoring activities? How can we deal with citizens observatories security and privacy issues regarding the information? The day is an opportunity for co-creation and considering new ways to explore how to address the issue of citizens observatories from a cross-disciplinary perspective – “Citizen science as a new way to manage the global commons”.

Next, a quick set of presentations of the FP7 projects:

WeSenseIt (Fabio Ciravegna) is a project that focuses on citizens involvement in water resources – citizens have a new role in the information chain of water related decisions. Participants are expected to become part of the decision-making. In this project, citizens observatory is seen as a science method, an environment to implement collaboration and as infrastructure. They are working in Doncaster (UK), Vicenza (Italy) and Delft (The Netherlands). In WeSenseIt, they recognise that different cultures and different ways to do things are part of such systems. A major questions is – who are the citizens? In the UK : normal people and in Italy: civil protection officials and volunteers, while in the Netherlands water and flood management is highly structured and organised activity. They have used a participatory design approach and working on the issue of governance and understanding how the citizen observatories should be embedded in the existing culture and processes. They are creating a citizens’ portal and another one for decision makers. The role of citizens portal is to assist with data acquisition with areas and equipment citizens can deploy – weather, soil moisture,etc. On the decision makers portals, there is the possibility is to provide surveillance information (with low-cost cameras etc), opportunistic sensing and participatory sensing – e.g. smart umbrella while combining all this information to be used together. WeSenseIt created a hybrid network that is aimed to provide information to decision makers and citizens. After two years, they can demonstrate that their approach can work: In Vicenza they used the framework to develop action to deal with flood preparedness. They also started to work with large events to assist in the organisation and support the control room, so in Torino they are also starting to get involved in helping running an event with up to 2m people.

Omniscientis (Philippe Ledent)  – The Omniscientis project (which ended in September) focused on odour monitoring and using different sensors – human and electronic. Odour can be a strong / severe nuisance, in Wallonia and France, and there is concerns about motorways, factories, livestock and waste facilities. Odour is difficult to measure and quantify and complex to identify. Mainly because it is about human perception, not only the measurement of chemicals in the air. In too many regulations and discussions about odour, citizens were considered as passive or victims. The Omniscientis project provided an opportunity to participants be active in the monitoring. The project took a multi-stakeholders  approach (farmers, factory operators, local residents etc.). They created odour management information system with the concept of a living lab. They created a OdoMIS that combines information from sensors, industry, NGOs, experts, and citizens. They created an app OdoMap that provide opportunities for participants to provide observations, but also see what other people measured and access to further information. They created chemical sensor array (e-nose), and the citizens helped in assessing what is the concentration that they sense. This was linked to a computationally intensive dispersion model. They have done a pilot around a pig farm in Austria to validate the model, and another near pulp and paper mill. Evolution of citizens participation was important for the project, and people collected measurements for almost a year, with over 5000 measurements. The results is they would like to link odour sources, citizens and authorities to work on the area. They have used actor netowrk theory to enrol participants in the process with strong UCD element.

COBWEB (Chris Higgins) has been working a generic crowdsourcing infrastructure, with data that can supports policy formation while addressing data quality issues and using open standards. They aimed to encapsulate metadata and OGC standards to ensure that the ifnroamtion is interoperable. They would like to create a toolkit can be used in different contexts and scenarios. They focus on the biospehere reserve network across Europe. They carried out a lot of co-design activities from the start with stakeholders engagement, they are doing co-design with 7 organisations in Wales – Woodlands trusts, RSPB, Snowdonia national park, and others. This lead to different focus and interest from each organisation – from dolphins to birds. They hope to see greater buy-in because of that.

Citi-Sense (Alena Bartonova) focusing on air quality. The objectives of city sense is to explore if people can participate in environmental governance. They are doing empowerment initiatives – urban quality, schools, and public spaces. In the urban context they measure pollution, meteorological observations, noise, health, biomarkers and UV exposure – they looked at technologies from mobile sensors and also static sensors that can be compared to compliance monitoring. In schools, they engage the school children, with looking at sensors that are installed at school and also looking at indoor air quality data. There are co-design activities with students. In Public spaces they focused on acoustic sensing, and discover that phones are not suitable so went to external sensors (we discovered the problem with phones in EveryAware). They explore in 9 cities and focusing from sensors, data and services platform but also explore how to engage people in a meaningful way. The first two years focused on technical aspects. They are now moving to look at the engagement part much more but they need to consider how to put it out. They are developing apps and also considering how to improve air quality apps. They would like a sustainable infrastructure.

Citclops (Luigi Ceccaroni) originally aimed ‘to create a community participatory governance methods aided by social media streams’, but this is an unclear goal that the project partners found confusing! So they are dealing with the issue of marine environment: asking people to take pictures of marine environment and through the app facilitating  visual monitoring of marine environment (available to download by anyone) – they are helping people to assess visually the quality of water bodies. There is an official way of defining the colour of sea waters which they use in the project and also comparing ground observations with satellite information. The project included the design of DIY devices to allow the measurement of water opacity. Finally, exploring water fluorescence. They design and 3D printed a device that can be used with smartphones to measure  fluorescence as this help to understand concentration of chlorophyll and can be associated with remote sensing information. Citizen science is a way to complement official data – such as the data from the water directive.

After a break and demonstration from some of the projects, the first round-table of the day, which include executives from environment protection agencies across Europe started

From @ScotlandEuropa strategic views on Citizens Observatories

[I’ve lost my notes, so below is a summary of the session edited from Valentine Seymour notes]

The chair (Gilles Ollier) of the session highlighted that the following issues as significant for considering the role of citizen science: Are we doing something useful/usable? Valuable? And sustainable?
James Curran (Scottish Environmental Protection Agency) noted that SEPA took citizen science to the core of its business. He highlighted issues of growth, jobs and investments. The need for sustainable growth and that citizen science contributed to these goals very well as the Chinese proverb say “Involve me and I will understand”. SEPA has been promoting mobile applications to detect invasive species and environmental damages. The Riverfly project is an example of engaging people in monitoring to detect water quality and invertebrate sampling and how important it was for the Water Framework Directive (WFD) to include public participation. There is a need to provide accessible information, working with others collaboratively, measuring behavioural changes and the need for public engagement.

Laura Burke (Ireland EPA) main statement was that citizen science do not replace governmental and official scientific monitoring but that citizen science should be seen in complimentary. There are three main issues or areas to consider; terminology (spectrum of the term citizen science), the need for thinking about the long-term sustainable future of citizen science projects, and acknowledge the synergies between projects.

Hugo de Groof (DG Env) noted the importance of access to information and the Open Access Directive that has been passed.  In terms of governance, we need to follow 5 main principles: 1) Accountability, 2) transparency, 3) participation, 4) Effectiveness and efficiency and finally 5) Respect. Raymond Feron from the Dutch ministry for infrastructure and environment emphasised that there is a social change emerging. [End of Valentine’s notes]

The issues of operationalisation received attention – there are different projects, how far are we from large-scale deployment? Colin Chapman (Welsh Government) – maturity across observatory projects vary from case to case and across issues. Technologies are still maturing, there is a need to respond to issues and mobilise resources to address issues that citizens bring up. Systems approach to ecosystem management is also a factor in considering how to integrate observatories. There are too much reliance on macro modelling. A question for policy bodies is “can we incentivise citizens to collect data across policy areas?” for example invasive species, we can use the information in different areas from flood modelling to biodiversity management. David Stanners (EEA) noted that citizens observatories are vulnerable at this point in time and this lack of stability  and there are examples of projects that didn’t last. There are some inter-linkages, but not an ecology of observatories, of interconnectedness and ability to survive. Need better linkage with policy, but not across the board and no direct policy elements. The integration of citizens observatories is a fantastic opportunity at EU level – as issues of the environment suppose to be very visible. Raymond Feron noted that government might have issues in keeping pace with citizens actions. Government organisations need to learn how to integrate citizens observatories, need to learn to reuse parts. Integrate research programme with implementation strategy. James Curran also stated that working with anglers and other stakeholders can increase trust. In terms of quality and relevant, citizen science data is not different to other data. Laura Burke noted that no government have all the answers, and trust issues should be presented as such. Need to move away from concept of one organisation with a solution to any given problem. David Stanners raised the issues of truth seeking. Within the cupernicos programme, there are opportunities to support services with citizen science.

Following the point of views from the panellists, questions about trust, finding ways to include of people without access to technology were raised by the audience. The panellists agreed that from the point of view of policy makes the concept of citizens observatories is obvious but there is a need to make citizens observatories and citizen science activities sustainable and well-integrated in government activities. Interestingly, James Curran noted that the issue of data quality from citizen science is not a major obstacles, inherently because environmental authorities are used to make decisions that are risk based. There was willingness to work with intermediaries to reach out to under-represented groups. David Stanners called for  cross cutting meta-studies to understand citizens observations landscape.

The next series of presentations covered citizen science activities that are not part of the citizens observatories projects.

NoiseWatch/Marine litter watch (David Stanners, EEA) – Noisewatch was developed by the EEA and provie the modelling element, measurement, and citizen rating element. He argued that dB is not good measure, as noise is a perception issue and not about just measurement. NoiseWatch received an award in the Geospatial World Forum. It became global although it wasn’t promoted as such, with uptake in India and China and UNEP are considering to take it over and maintain it. Sustainability of NoiseWatch is a challenge for EEA and it might be more suitable in a global platform such as UNEP Live. NoiseWatch is seen as complementing existing monitoring stations because there as so few of them. When analysing the sources of the measurement, NoiseWatch get a lot of observations from roads, with 21% of industry noise – in total almost 195000 measurements. Another application is Marine LitterWatch which provides a way for people to share information about the state of beaches. The application is more complex as it embedded in protocol of data collection, and David argue that it is ‘more close to citizen science’, EEA got almost 7500 measurements with 144 events to use it, they are developing it further.

LakeWiki (Juhani Kettunen, who was not present) is an initiative that focus on motoring Finnish lakes – was launched by Syke and it is aimed to allow local communities to take care of their lakes, record information and build a long term observations. Simple platform, recording information such as ice break up but it is aimed to allow locals write about the lake, maintain observations sites, upload pictures, announce local events and write in discussion forums, 1400 sites [this project is also noted in COST Energic network]

Raymond Feron presented a programme in Netherlands called  digital Delta Initiative: partnership between research, public and government. IBM, TU Delft and government are involved. Trying to make water data available to everyone. focus of the system allow re-use of information, the government try to do things more efficiently, shorten time to market, improve quality of decisions, while also improving citizen participation. Ideas of increasing export to new places. Involving the public with dyke monitoring because they can do things locally easily.

I gave a talk about Mapping for Change air quality studies, and I hope to discuss them in a different post:

Claudia Goebel followed with a report on ECSA (see my report for ECSA meeting)

Antonoi Parodi from CIMA foundation discussed the DRIHM project. This is mostly a project focused on meteorological information. Issue of meteorology has a very long history of observations, going from 300 BC. There is plenty of reliance of observed patterns of events. Informal folklore was used by early meteorology citizen science. The middle ages, there are examples of getting information to deal with flash flood. Within the project they created a volunteer thinking platform to support classifications of thunderstorms. The Cb-TRAM monitoring observations of thunderstorms. Interestingly, a follow on question explored the link between extreme events (floods last year) and the role of the research project to provide relevant information.

The Socientize project was presented by Francisco Sanz, covering areas of digital science.

There was also a presentation from the SciCafe 2.0 project, including mentioning the European Observatory for Crowd-Sourcing . Another tool from the project is Citizens’ Say tool  

The final panel explored issues on the challenges of citizen science (I was part of this panel). The people on the panel were Jaume Piera (CITCLOPS),;Arne Berre (CITI-SENSE); Bart De Lathouwer (COBWEB); Philippe Valoggia (OMNISCIENTIS); Uta Wehn (WeSenseIt); Susanne Lützenkirchen, City of Oslo and myself.

Susanne noted that the city of Oslo developed some apps, such as safe for schools – people can experience their routes to schools and they are interested in more citizen science and citizen observatories.

Strategy for sustainability of engagement over time – Uta noted that the co-design process is very important and governance analysis to understand the processes and the local needs (in WeSenseIt). The observatories need to consider who are the partners – authorities are critical to see the value of observatories and provide feedback. Jaime suggested – identifying points in the project that give participants feeling that they are part of the process, allowing people to participate in different ways. Making people aware that they are part of the activities and they are valued. Showing the need for long-term observations. Susanne pointed that in Oslo there isn’t any simple answer – the issue of who are the citizens and in others it is a specific groups or more complex design sometime need to think who chose participants and how representative they are.

In WeSenseIT, they have privacy and consent setting – adhering to rules of social media, and it is an issue of data that came from other sources and how it is going to be reused. In general, Uta noted that WeSenseIt would like to try and make the data open as possible.

Data preservation is an issue – how data was handled, if we assume that there are probably 500 projects or more in Europe which is Max Craglia (JRC, who chaired the session) estimation. The issues of citizen observatories, we need to consider the individual data and there is sometime concern about releasing unvalidated data. Bart pointed that Cobweb is taking care of privacy and security of data and they are storing information about observers and there are privacy rules. Privacy legislation are local and need to follow the information. citizens see the benefit in what they collected and the sustainability of commitment. It is important to work with existing social structures and that provide opportunity for empowerment. Views about ownership of data were raised.

In terms of integration and synergy or interoperability of the citizen centred projects – interoperability is critical topic, the data need to be standardised and deal with the metadata (the most boring topic in the world). It should be collected at the right level. There is good foundation in GEOS and OGC, so we can consider how to do it.

What is the role of scientists? the role of scientists – there are partners who focus on dealing with the data and augment it with additional information and there is a role of managing the data. The link to policy also require an understanding of uncertainty. The discourse of science-policy is about what is considered as evidence. There is embracing of citizen science in environment agencies (which was demonstrated in the first panel), but there is a need for honest discussion about what happen to the data, and what degree citizens can participate in decision-making. Relevancy, legitimacy are critical to the understanding.

There was also call for accepting the uncertainty in the data – which is integral part of citizen science data. David Stanners emphasised the need for legitimacy of the information that is coming from citizens observatories as part of the trust that people put in contributing to them.

The final comments came from Andrea Tilche (Head of Unit Climate Actions and Earth Observation, DG R&I). The commission recognise that citizen observatories are not a replacement for institutional monitoring scheme (although he mentioned maybe in the future). The potential of engaging users is tremendous, and the conference demonstrated the energy and scale of activities that can be included in this area . The ownership of information need to be taken into account. We need to link and close the gaps with scientists and policy makers. We need to create market around the observatories – can’t only do it through project that disappear. There is a need for market of citizen observatories and business models. In the new call, they want to see the project generate and credible business processes. Citizens observatories will need demonstrate raising funding from other sources.

If you have been reading the literature on citizen science, you must have noticed that many papers that describe citizen science start with an historical narrative, something along the lines of:

As Silvertown (2009) noted, until the late 19th century, science was mainly developed by people who had additional sources of employment that allowed them to spend time on data collection and analysis. Famously, Charles Darwin joined the Beagle voyage, not as a professional naturalist but as a companion to Captain FitzRoy[*]. Thus, in that era, almost all science was citizen science albeit mostly by affluent gentlemen and gentlewomen scientists[**]. While the first professional scientist is likely to be Robert Hooke, who was paid to work on scientific studies in the 17th century, the major growth in the professionalisation of scientists was mostly in the latter part of the 19th and throughout the 20th century.
Even with the rise of the professional scientist, the role of volunteers has not disappeared, especially in areas such as archaeology, where it is common for enthusiasts to join excavations, or in natural science and ecology, where they collect and send samples and observations to national repositories. These activities include the Christmas Bird Watch that has been ongoing since 1900 and the British Trust for Ornithology Survey, which has collected over 31 million records since its establishment in 1932 (Silvertown 2009). Astronomy is another area in which amateurs and volunteers have been on a par with professionals when observation of the night sky and the identification of galaxies, comets and asteroids are considered (BBC 2006). Finally, meteorological observations have also relied on volunteers since the early start of systematic measurements of temperature, precipitation or extreme weather events (WMO 2001). (Haklay 2013 emphasis added)

The general messages of this historical narrative are: first, citizen science is a legitimate part of scientific practice as it was always there, we just ignored it for 50+ years; second, that some citizen science is exactly as it was – continuous participation in ecological monitoring or astronomical observations, only that now we use smartphones or the Met Office WOW website and not pen, paper and postcards.

The second aspect of this argument is one that I was wondering about as I was writing a version of the historical narrative for a new report. This was done within a discussion on how the educational and technological transitions over the past century reshaped citizen science. I have argued that the demographic and educational transition in many parts of the world, and especially the rapid growth in the percentage and absolute numbers of people with higher education degrees who are potential participants is highly significant in explaining the popularity of citizen science. To demonstrate that this is a large scale and consistent change, I used the evidence of Flynn effect, which is the rapid increase in IQ test scores across the world during the 20th century.

However, while looking at the issue recently, I came across Jim Flynn TED talk ‘Why our IQ levels are higher than our grandparents (below). At 3:55, he raise a very interesting point, which also appears in his 2007 What is Intelligence? on pages 24-26. Inherently, Flynn argues that the use of cognitive skills have changed dramatically over the last century, from thinking that put connections to concrete relationship with everyday life as the main way of understanding the world, to one that emphasise scientific categories and abstractions. He use an example of a study from the early 20th Century, in which participants where asked about commonalities between fish and birds. He highlights that it was not the case that in the ‘pre-scientific’ worldview people didn’t know that both are animals, but more the case that this categorisation was not helpful to deal with concrete problems and therefore not common sense. Today, with scientific world view, categorisation such as ‘these are animals’ come first.

This point of view have implications to the way we interpret and understand the historical narrative. If correct, than the people who participate in William Whewell tide measurement work (see Caren Cooper blogpost about it), cannot be expected to think about contribution to science, but could systematically observed concrete events in their area. While Whewell view of participants as ‘subordinate labourers’ is still elitist and class based, it is somewhat understandable.  Moreover, when talking about projects that can show continuity over the 20th Century – such as Christmas Bird Count or phenology projects – we have to consider the option that an the worldview of the person that done that in 1910 was ‘how many birds there are in my area?’ while in 2010 the framing is ‘in order to understand the impact of climate change, we need to watch out for bird migration patterns’. Maybe we can explore in historical material to check for this change in framing? I hope that projects such as Constructing Scientific Communities which looks at citizen science in the 19th and 21th century will shed light on such differences.


[*] Later I found that this is not such a simple fact – see van Wyhe 2013 “My appointment received the sanction of the Admiralty”: Why Charles Darwin really was the naturalist on HMS Beagle

[**] And we shouldn’t forget that this was to the exclusion of people such as Mary Anning

 

The Association of American Geographers is coordinating an effort to create an International Encyclopedia of Geography. Plans started in 2010, with an aim to see the 15 volumes project published in 2015 or 2016. Interestingly, this shows that publishers and scholars are still seeing the value in creating subject-specific encyclopedias. On the other hand, the weird decision by Wikipedians that Geographic Information Science doesn’t exist outside GIS, show that geographers need a place to define their practice by themselves. You can find more information about the AAG International Encyclopedia project in an interview with Doug Richardson from 2012.

As part of this effort, I was asked to write an entry on ‘Volunteered Geographic Information, Quality Assurance‘ as a short piece of about 3000 words. To do this, I have looked around for mechanisms that are used in VGI and in Citizen Science. This are covered in OpenStreetMap studies and similar work in GIScience, and in the area of citizen science, there are reviews such as the one by Andrea Wiggins and colleagues of mechanisms to ensure data quality in citizen science projects, which clearly demonstrated that projects are using multiple methods to ensure data quality.

Below you’ll find an abridged version of the entry (but still long). The citation for this entry will be:

Haklay, M., Forthcoming. Volunteered geographic information, quality assurance. in D. Richardson, N. Castree, M. Goodchild, W. Liu, A. Kobayashi, & R. Marston (Eds.) The International Encyclopedia of Geography: People, the Earth, Environment, and Technology. Hoboken, NJ: Wiley/AAG

In the entry, I have identified 6 types of mechanisms that are used to ensure quality assurance when the data has a geographical component, either VGI or citizen science. If I have missed a type of quality assurance mechanism, please let me know!

Here is the entry:

Volunteered geographic information, quality assurance

Volunteered Geographic Information (VGI) originate outside the realm of professional data collection by scientists, surveyors and geographers. Quality assurance of such information is important for people who want to use it, as they need to identify if it is fit-for-purpose. Goodchild and Li (2012) identified three approaches for VGI quality assurance , ‘crowdsourcing‘ and that rely on the number of people that edited the information, ‘social’ approach that is based on gatekeepers and moderators, and ‘geographic’ approach which uses broader geographic knowledge to verify that the information fit into existing understanding of the natural world. In addition to the approaches that Goodchild and li identified, there are also ‘domain’ approach that relate to the understanding of the knowledge domain of the information, ‘instrumental observation’ that rely on technology, and ‘process oriented’ approach that brings VGI closer to industrialised procedures. First we need to understand the nature of VGI and the source of concern with quality assurance.

While the term volunteered geographic information (VGI) is relatively new (Goodchild 2007), the activities that this term described are not. Another relatively recent term, citizen science (Bonney 1996), which describes the participation of volunteers in collecting, analysing and sharing scientific information, provide the historical context. While the term is relatively new, the collection of accurate information by non-professional participants turn out to be an integral part of scientific activity since the 17th century and likely before (Bonney et al 2013). Therefore, when approaching the question of quality assurance of VGI, it is critical to see it within the wider context of scientific data collection and not to fall to the trap of novelty, and to consider that it is without precedent.

Yet, this integration need to take into account the insights that emerged within geographic information science (GIScience) research over the past decades. Within GIScience, it is the body of research on spatial data quality that provide the framing for VGI quality assurance. Van Oort’s (2006) comprehensive synthesis of various quality standards identifies the following elements of spatial data quality discussions:

  • Lineage – description of the history of the dataset,
  • Positional accuracy – how well the coordinate value of an object in the database relates to the reality on the ground.
  • Attribute accuracy – as objects in a geographical database are represented not only by their geometrical shape but also by additional attributes.
  • Logical consistency – the internal consistency of the dataset,
  • Completeness – how many objects are expected to be found in the database but are missing as well as an assessment of excess data that should not be included.
  • Usage, purpose and constraints – this is a fitness-for-purpose declaration that should help potential users in deciding how the data should be used.
  • Temporal quality – this is a measure of the validity of changes in the database in relation to real-world changes and also the rate of updates.

While some of these quality elements might seem independent of a specific application, in reality they can be only be evaluated within a specific context of use. For example, when carrying out analysis of street-lighting in a specific part of town, the question of completeness become specific about the recording of all street-light objects within the bounds of the area of interest and if the data set includes does not include these features or if it is complete for another part of the settlement is irrelevant for the task at hand. The scrutiny of information quality within a specific application to ensure that it is good enough for the needs is termed ‘fitness for purpose’. As we shall see, fit-for-purpose is a central issue with respect to VGI.

To understand the reason that geographers are concerned with quality assurance of VGI, we need to recall the historical development of geographic information, and especially the historical context of geographic information systems (GIS) and GIScience development since the 1960s. For most of the 20th century, geographic information production became professionalised and institutionalised. The creation, organisation and distribution of geographic information was done by official bodies such as national mapping agencies or national geological bodies who were funded by the state. As a results, the production of geographic information became and industrial scientific process in which the aim is to produce a standardised product – commonly a map. Due to financial, skills and process limitations, products were engineered carefully so they can be used for multiple purposes. Thus, a topographic map can be used for navigation but also for urban planning and for many other purposes. Because the products were standardised, detailed specifications could be drawn, against which the quality elements can be tested and quality assurance procedures could be developed. This was the backdrop to the development of GIS, and to the conceptualisation of spatial data quality.

The practices of centralised, scientific and industrialised geographic information production lend themselves to quality assurance procedures that are deployed through organisational or professional structures, and explains the perceived challenges with VGI. Centralised practices also supported employing people with focus on quality assurance, such as going to the field with a map and testing that it complies with the specification that were used to create it. In contrast, most of the collection of VGI is done outside organisational frameworks. The people who contribute the data are not employees and seemingly cannot be put into training programmes, asked to follow quality assurance procedures, or expected to use standardised equipment that can be calibrated. The lack of coordination and top-down forms of production raise questions about ensuring the quality of the information that emerges from VGI.

To consider quality assurance within VGI require to understand some underlying principles that are common to VGI practices and differentiate it from organised and industrialised geographic information creation. For example, some VGI is collected under conditions of scarcity or abundance in terms of data sources, number of observations or the amount of data that is being used. As noted, the conceptualisation of geographic data collection before the emergence of VGI was one of scarcity where data is expensive and complex to collect. In contrast, many applications of VGI the situation is one of abundance. For example, in applications that are based on micro-volunteering, where the participant invest very little time in a fairly simple task, it is possible to give the same mapping task to several participants and statistically compare their independent outcomes as a way to ensure the quality of the data. Another form of considering abundance as a framework is in the development of software for data collection. While in previous eras, there will be inherently one application that was used for data capture and editing, in VGI there is a need to consider of multiple applications as different designs and workflows can appeal and be suitable for different groups of participants.

Another underlying principle of VGI is that since the people who collect the information are not remunerated or in contractual relationships with the organisation that coordinates data collection, a more complex relationships between the two sides are required, with consideration of incentives, motivations to contribute and the tools that will be used for data collection. Overall, VGI systems need to be understood as socio-technical systems in which the social aspect is as important as the technical part.

In addition, VGI is inherently heterogeneous. In large scale data collection activities such as the census of population, there is a clear attempt to capture all the information about the population over relatively short time and in every part of the country. In contrast, because of its distributed nature, VGI will vary across space and time, with some areas and times receiving more attention than others. An interesting example has been shown in temporal scales, where some citizen science activities exhibit ‘weekend bias’ as these are the days when volunteers are free to collect more information.

Because of the difference in the organisational settings of VGI, a different approaches to quality assurance is required, although as noted, in general such approaches have been used in many citizen science projects. Over the years, several approaches emerged and these include ‘crowdsourcing ‘, ‘social’, ‘geographic’, ‘domain’, ‘instrumental observation’ and ‘process oriented’. We now turn to describe each of these approaches.

Thecrowdsourcing approach is building on the principle of abundance. Since there are is a large number of contributors, quality assurance can emerge from repeated verification by multiple participants. Even in projects where the participants actively collect data in uncoordinated way, such as the OpenStreetMap project, it has been shown that with enough participants actively collecting data in a given area, the quality of the data can be as good as authoritative sources. The limitation of this approach is when local knowledge or verification on the ground (‘ground truth’) is required. In such situations, the ‘crowdsourcing’ approach will work well in central, highly populated or popular sites where there are many visitors and therefore the probability that several of them will be involved in data collection rise. Even so, it is possible to encourage participants to record less popular places through a range of suitable incentives.

Thesocial approach is also building on the principle of abundance in terms of the number of participants, but with a more detailed understanding of their knowledge, skills and experience. In this approach, some participants are asked to monitor and verify the information that was collected by less experienced participants. The social method is well established in citizen science programmes such as bird watching, where some participants who are more experienced in identifying bird species help to verify observations by other participants. To deploy the social approach, there is a need for a structured organisations in which some members are recognised as more experienced, and are given the appropriate tools to check and approve information.

Thegeographic approach uses known geographical knowledge to evaluate the validity of the information that is received by volunteers. For example, by using existing knowledge about the distribution of streams from a river, it is possible to assess if mapping that was contributed by volunteers of a new river is comprehensive or not. A variation of this approach is the use of recorded information, even if it is out-of-date, to verify the information by comparing how much of the information that is already known also appear in a VGI source. Geographic knowledge can be potentially encoded in software algorithms.

Thedomain approach is an extension of the geographic one, and in addition to geographical knowledge uses a specific knowledge that is relevant to the domain in which information is collected. For example, in many citizen science projects that involved collecting biological observations, there will be some body of information about species distribution both spatially and temporally. Therefore, a new observation can be tested against this knowledge, again algorithmically, and help in ensuring that new observations are accurate.

Theinstrumental observation approach remove some of the subjective aspects of data collection by a human that might made an error, and rely instead on the availability of equipment that the person is using. Because of the increased in availability of accurate-enough equipment, such as the various sensors that are integrated in smartphones, many people keep in their pockets mobile computers with ability to collect location, direction, imagery and sound. For example, images files that are captured in smartphones include in the file the GPS coordinates and time-stamp, which for a vast majority of people are beyond their ability to manipulate. Thus, the automatic instrumental recording of information provide evidence for the quality and accuracy of the information.

Finally, the ‘process oriented approach bring VGI closer to traditional industrial processes. Under this approach, the participants go through some training before collecting information, and the process of data collection or analysis is highly structured to ensure that the resulting information is of suitable quality. This can include provision of standardised equipment, online training or instruction sheets and a structured data recording process. For example, volunteers who participate in the US Community Collaborative Rain, Hail & Snow network (CoCoRaHS) receive standardised rain gauge, instructions on how to install it and an online resources to learn about data collection and reporting.

Importantly, these approach are not used in isolation and in any given project it is likely to see a combination of them in operation. Thus, an element of training and guidance to users can appear in a downloadable application that is distributed widely, and therefore the method that will be used in such a project will be a combination of the process oriented with the crowdsourcing approach. Another example is the OpenStreetMap project, which in the general do not follow limited guidance to volunteers in terms of information that they collect or the location in which they collect it. Yet, a subset of the information that is collected in OpenStreetMap database about wheelchair access is done through the highly structured process of the WheelMap application in which the participant is require to select one of four possible settings that indicate accessibility. Another subset of the information that is recorded for humanitarian efforts is following the social model in which the tasks are divided between volunteers using the Humanitarian OpenStreetMap Team (H.O.T) task manager, and the data that is collected is verified by more experienced participants.

The final, and critical point for quality assurance of VGI that was noted above is fitness-for-purpose. In some VGI activities the information has a direct and clear application, in which case it is possible to define specifications for the quality assurance element that were listed above. However, one of the core aspects that was noted above is the heterogeneity of the information that is collected by volunteers. Therefore, before using VGI for a specific application there is a need to check for its fitness for this specific use. While this is true for all geographic information, and even so called ‘authoritative’ data sources can suffer from hidden biases (e.g. luck of update of information in rural areas), the situation with VGI is that variability can change dramatically over short distances – so while the centre of a city will be mapped by many people, a deprived suburb near the centre will not be mapped and updated. There are also limitations that are caused by the instruments in use – for example, the GPS positional accuracy of the smartphones in use. Such aspects should also be taken into account, ensuring that the quality assurance is also fit-for-purpose.

References and Further Readings

Bonney, Rick. 1996. Citizen Science – a lab tradition, Living Bird, Autumn 1996.
Bonney, Rick, Shirk, Jennifer, Phillips, Tina B. 2013. Citizen Science, Encyclopaedia of science education. Berlin: Springer-Verlag.
Goodchild, Michael F. 2007. Citizens as sensors: the world of volunteered geography. GeoJournal, 69(4), 211–221.
Goodchild, Michael F., and Li, Linna. 2012, Assuring the quality of volunteered geographic information. Spatial Statistics, 1 110-120
Haklay, Mordechai. 2010. How Good is volunteered geographical information? a comparative study of OpenStreetMap and ordnance survey datasets. Environment and Planning B: Planning and Design, 37(4), 682–703.
Sui, Daniel, Elwood, Sarah and Goodchild, Michael F. (eds), 2013. Crowdsourcing Geographic Knowledge, Berlin:Springer-Verlag.
Van Oort, Pepjin .A.J. 2006. Spatial data quality: from description to application, PhD Thesis, Wageningen: Wageningen Universiteit, p. 125.

What is Science?

6 September, 2014

When you look at the discussions that are emerging around the term ‘Citizen Science‘, you can often find discussion about the ‘Citizen‘ part of the term. What about the ‘Science‘ part? This is something that once you start being involved in Citizen Science you are forced to contemplate. As Francois Grey like to note ‘Science is too important to be left out to scientists‘ and we need to find a way to make it more inclusive as a process and practice. Sometime, Citizen Science challenges ‘established’ science and protocols. This can be about small things – such as noticing that diffusion tubes are installed at 2.5m (while the area of real concern is 1-1.5m), or bigger things, such as noticing that a lot of noise measurement is about what is possible to measure (sound) and avoiding what is difficult (noise). Even more challenging is the integration of local, lay and traditional knowledge within the citizen science framework with scientific knowledge. In short, there is value in considering what we mean by ‘science’.

UCL iGEM team public biobrick

UCL iGEM team public biobrick

For me, the challenge that evolved was ‘how can we have a definition of science that recognises that it’s a powerful form of knowledge, while allowing other forms of knowledge to work with it?‘. After experimenting with different ideas in the past year, I ended with the following, directly paraphrasing from the famous quote* from Winston Churchill about democracy as the least worst form of government. So the current, work in progress, definition that I’m using is the following:

“Science is the least worst method to accumulate human knowledge about the natural world (and it need to work, in a respectful way, with other forms of knowledge)”

What I am trying to do with this definition is first to recognise that knowledge is produced collaboratively and, ideally, in a democratic process. For that, the original form of the phrase is useful. Second, I wanted to note that science is not infallible but meandering, getting into blind alleys and all the rest, which the ‘least worst’ is capturing better than ‘the best’. Third, it is allowing the recognition that it is a very effective and powerful form of human knowledge.

Does it work? Is it suitable?

 


* I always like to find the correct source, and if you look at the Hansard, you’ll see that Churchill was more forthright and said: “Many forms of Government have been tried, and will be tried in this world of sin and woe. No one pretends that democracy is perfect or all-wise. Indeed, it has been said that democracy is the worst form of Government except all those other forms that have been tried from time to time;”. Now that I know that, it’s tempting to try and replace democracy with science and government with knowledge…

As far as I can tell, Nelson et al. (2006) ‘Towards development of a high quality public domain global roads database‘ and Taylor & Caquard (2006) Cybercartography: Maps and Mapping in the Information Era are the first peer-reviewed papers that mention OpenStreetMap. Since then, OpenStreetMap has received plenty of academic attention. More ‘conservative’ search engines such as ScienceDirect or Scopus find 286 and 236 peer reviewed papers (respectively) that mention the project. The ACM digital library finds 461 papers in the areas that are relevant to computing and electronics, while Microsoft Academic Research finds only 112. Google Scholar lists over 9000 (!). Even with the most conservative version from Microsoft, we can see an impact on fields ranging from social science to engineering and physics. So lots to be proud of as a major contribution to knowledge beyond producing maps.

Michael Goodchild, in his 2007 paper that started the research into Volunteered Geographic Information (VGI), mentioned OpenStreetMap (OSM), and since then there is a lot of conflation of OSM and VGI. In some recent papers you can find statements such as ‘OpenstreetMap is considered as one of the most successful and popular VGI projects‘ or ‘the most prominent VGI project OpenStreetMap so, at some level, the boundary between the two is being blurred. I’m part of the problem – for example, with the title of my 2010 paper ‘How good is volunteered geographical information? A comparative study of OpenStreetMap and Ordnance Survey datasetsHowever, the more I think about it, the more uncomfortable I am with this equivalence. I feel that the recent line from Neis & Zielstra (2014) is more accurate: ‘One of the most utilized, analyzed and cited VGI-platforms, with an increasing popularity over the past few years, is OpenStreetMap (OSM)‘. I’ll explain why.

Let’s look at the whole area of OpenStreetMap studies. Over the past decade, several types of research paper have emerged.

First, there is a whole set of research projects that use OSM data because it’s easy to use and free to access (in computer vision or even string theory). These studies are not part of ‘OSM studies’ or VGI, as, for them, this is just data to be used.

Edward Betts. CC-By-SA 2.0 via Wikimedia Commons

Second, there are studies about OSM data: quality, evolution of objects and other aspects from researchers such as Peter Mooney, Pascal Neis, Alex Zipf  and many others.

Third, there are studies that also look at the interactions between the contribution and the data – for example, in trying to infer trustworthiness.

Fourth, there are studies that look at the wider societal aspects of OpenStreetMap, with people like Martin Dodge, Chris Perkins, and Jo Gerlach contributing in interesting discussions.

Finally, there are studies of the social practices in OpenStreetMap as a project, with the work of Yu-Wei Lin, Nama Budhathoki, Manuela Schmidt and others.

[Unfortunately, due to academic practices and publication outlets, many of these papers are locked behind paywalls, but thatis another issue… ]

In short, there is a significant body of knowledge regarding the nature of the project, the implications of what it produces, and ways to understand the information that emerges from it. Clearly, we now know that OSM produces good data and are ware of the patterns of contribution. What is also clear is that many of these patterns are specific to OSM. Because of the importance of OSM to so many application areas (including illustrative maps in string theory!) these insights are very important. Some of these insights are expected to also be present in other VGI projects (hence my suggestions for assertions about VGI) but this needs to be done carefully, only when there is evidence from other projects that this is the case. In short, we should avoid conflating VGI and OSM.

Today, OpenStreetMap celebrates 10 years of operation as counted from the date of registration. I’ve heard about the project when it was in early stages, mostly because I knew Steve Coast when I was studying for my Ph.D. at UCL.  As a result, I was also able to secured the first ever research grant that focused on OpenStreetMap (and hence Volunteered Geographic Information – VGI) from the Royal Geographical Society in 2005. A lot can be said about being in the right place at the right time!

OSM Interface, 2006 (source: Nick Black)

OSM Interface, 2006 (source: Nick Black)

Having followed the project during this decade, there is much to reflect on – such as thinking about open research questions, things that the academic literature failed to notice about OSM or the things that we do know about OSM and VGI because of the openness of the project. However, as I was preparing the talk for the INSPIRE conference, I was starting to think about the start dates of OSM (2004), TomTom Map Share (2007), Waze (2008), Google Map Maker (2008).  While there are conceptual and operational differences between these projects, in terms of ‘knowledge-based peer production systems’ they are fairly similar: all rely on large number of contributors, all use both large group of contributors who contribute little, and a much smaller group of committed contributors who do the more complex work, and all are about mapping. Yet, OSM started 3 years before these other crowdsourced mapping projects, and all of them have more contributors than OSM.

Since OSM is described  as ‘Wikipedia of maps‘, the analogy that I was starting to think of was that it’s a bit like a parallel history, in which in 2001, as Wikipedia starts, Encarta and Britannica look at the upstart and set up their own crowdsourcing operations so within 3 years they are up and running. By 2011, Wikipedia continues as a copyright free encyclopedia with sizable community, but Encarta and Britannica have more contributors and more visibility.

Knowing OSM closely, I felt that this is not a fair analogy. While there are some organisational and contribution practices that can be used to claim that ‘it’s the fault of the licence’ or ‘it’s because of the project’s culture’ and therefore justify this, not flattering, analogy to OSM, I sensed that there is something else that should be used to explain what is going on.

TripAdvisor FlorenceThen, during my holiday in Italy, I was enjoying the offline TripAdvisor app for Florence, using OSM for navigation (in contrast to Google Maps which are used in the online app) and an answer emerged. Within OSM community, from the start, there was some tension between the ‘map’ and ‘database’ view of the project. Is it about collecting the data so beautiful maps or is it about building a database that can be used for many applications?

Saying that OSM is about the map mean that the analogy is correct, as it is very similar to Wikipedia – you want to share knowledge, you put it online with a system that allow you to display it quickly with tools that support easy editing the information sharing. If, on the other hand, OSM is about a database, then OSM is about something that is used at the back-end of other applications, a lot like DBMS or Operating System. Although there are tools that help you to do things easily and quickly and check the information that you’ve entered (e.g. displaying the information as a map), the main goal is the building of the back-end.

Maybe a better analogy is to think of OSM as ‘Linux of maps’, which mean that it is an infrastructure project which is expected to have a lot of visibility among the professionals who need it (system managers in the case of Linux, GIS/Geoweb developers for OSM), with a strong community that support and contribute to it. The same way that some tech-savvy people know about Linux, but most people don’t, I suspect that TripAdvisor offline users don’t notice that they use OSM, they are just happy to have a map.

The problem with the Linux analogy is that OSM is more than software – it is indeed a database of information about geography from all over the world (and therefore the Wikipedia analogy has its place). Therefore, it is somewhere in between. In a way, it provide a demonstration for the common claim in GIS circles that ‘spatial is special‘. Geographical information is infrastructure in the same way that operating systems or DBMS are, but in this case it’s not enough to create an empty shell that can be filled-in for the specific instance, but there is a need for a significant amount of base information before you are able to start building your own application with additional information. This is also the philosophical difference that make the licensing issues more complex!

In short, both Linux or Wikipedia analogies are inadequate to capture what OSM is. It has been illuminating and fascinating to follow the project over its first decade,  and may it continue successfully for more decades to come.

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