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 РGreenspace Information for Greater London (GiGL), iSpot and iRecord Рwith 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.

A review of volunteered geographic information quality assessment methods

One of the joys of academic life is the opportunity to participate in summer schools Рyou get a group of researchers, from PhD students to experienced professors, to a nice place in the Italian countryside, and for a week the group focuses on a topic Рdiscussing, demonstrating and trying it out. The Vespucci Institute in 2014 that was dedicated to citizen science and Volunteered Geographic Information (VGI) is an example for that. Such activities are more than a summer retreat Рthere are tangible academic outputs that emerge from such workshops Рdemonstrating that valuable work is done!

During the summer school in 2014, Hansi Senaratne suggested to write a review of VGI data quality approaches, and together with Amin Mobasheri and Ahmed Loai Ali (all PhD students) started to developed it. I and Cristina Capineri, as summer school organisers and the vice-chair & chair of COST ENERGIC network (respectively), gave advice to the group and helped them in developing a paper, aimed at one of the leading journal of Geographic Information Science (GIScience) Рthe International Journal of GIScience (IJGIS).

Hensi presents at the Vespucci summer school
Hansi presenting at the Vespucci summer school

The paper went through the usual peer review process, and with a huge effort from Hansi, Amin & Ahmed, it gone all the way to¬†publication. It is now out. The paper is titled ‘A review of volunteered geographic information quality assessment methods‘ and is accessible through the journal’s website.¬†The abstract is provided below, and if you want the pre-print version – you can download it from here.

With the ubiquity of advanced web technologies and location-sensing hand held devices, citizens regardless of their knowledge or expertise, are able to produce spatial information. This phenomenon is known as volunteered geographic information (VGI). During the past decade VGI has been used as a data source supporting a wide range of services, such as environmental monitoring, events reporting, human movement analysis, disaster management, etc. However, these volunteer-contributed data also come with varying quality. Reasons for this are: data is produced by heterogeneous contributors, using various technologies and tools, having different level of details and precision, serving heterogeneous purposes, and a lack of gatekeepers. Crowd-sourcing, social, and geographic approaches have been proposed and later followed to develop appropriate methods to assess the quality measures and indicators of VGI. In this article, we review various quality measures and indicators for selected types of VGI and existing quality assessment methods. As an outcome, the article presents a classification of VGI with current methods utilized to assess the quality of selected types of VGI. Through these findings, we introduce data mining as an additional approach for quality handling in VGI

Citizen Science Data & Service Infrastructure

Following the ECSA meeting, the Data & tools working group workshop was dedicated to progressing the agenda on data & infrastructure.

Jaume Piera (chair, Data and Tools working group of ECSA) covered the area of citizen science data – moving from ideas, to particular solutions, to global proposals – from separate platforms (iNaturalist, iSpot, GBIF, eBird) but the creation of different citizen science associations and the evolution of ideas for interoperability, can allow us to consider the ‘Internet of People# which is about participatory sharing of data. We can work in similar way to standards development¬†in the area of the internet, and starting to consider the layers: interoperability, privacy/security, data reliability, infrastructure sustainability, data management, intellectual property rights, engagement, Human-Computer Interaction, Reference models and testing. By considering these multiple layers, we can develop a roadmap for development and consider a range of solutions at different ‘layers’. The idea is to open it to other communities – and aim to have solutions that are discussed globally.

Arne Berra explained the CITI-SENSE¬†platform. There is a paper that explains the architecture of CITI-SENSE¬†on the project site. He proposed that we use the European Interoperability Framework — legal, organisational, semantic and technical. in the technical area, we can use ISO 19119 and OGC – with 6 areas: boundary, processing/analytics, data/model management, communication, systems. We can use reference models. Also suggested considering the INSPIRE life cycle model. There is a challenge of adapting standards into the context of citizen science, so in many ways we need to look at it as conceptual framework to consider the different issues and consider points about the issues. In CITI-SENSE¬†they developed a life cycle that looked at human sensor data services, as well as the hardware sensor application platform.


Ingo Simonis (OGC) – a standardised encoding to exchange citizen science data. He describe work that OGC is doing in sensor web for citizen science, and they collected data from different projects. Through citizen science data, information come from different surveys, in different forms and structures. The requirements are to have citizens + environment + sensor. Who did particular measurement? We want to know about the environment – e.g. that it was rainy while they collected the data, and then know about the sensor. So OGC O&M citizen observatories model is conceptual. It’s an observation model – assigning a value to a property – they also look at standards for sensors – OGC SensorML. He used the ISO 19100 series of standards. The observation model is trying to address issues of observations that are happening offline and then being shared. The model also deal with stationary and mobile sensing activities, and allowing for flexibility – for example having ad-hoc record that is not following specific process.


Alex Steblin – The Citclops project includes applications such as Eye on Water ( The Citclops have a challenge of maintaining the project’s data once the project finished.

Veljo Runnel covered EU BON work ( – mobilising biodiversity ata is challenges. They want a registry of online tools for citizen science projects – tool that will allow people who work with citizen science to record information about the project as related to biodiversity – such as link to GBIF, recording DNA, use of mobile app. Finding the person that run the tool is difficult. On EU BON they have ‘data mobilization helpdesk’, the elements of the standard were discussed within the the EU BON consortium and how they are going to explore how to provide further input.

JRC is exploring the possibility of providing infrastructure for citizen science data – both metadata and the data itself.

Translation of technical information into a language that is accessible is valuable for the people who will be using it. We need to find ways to make information more accessible and digestible. The aim is to start developing reference material and building on existing experiences – sub divide the working group to specific area. There are many sub communities that are not represented within the data groups (and in ECSA) and we need to reach out to different communities and have including more groups. There are also issues about linking the US activities, and activities from the small-scale (neighbourhoods) to large organisations. As we work through information, we need to be careful about technical language, and we need to be able to share information in an accessible way.

Notes from ICCB/ECCB 2015 (Day 2) ‚Äď Citizen Science data quality

Posters session at ICCB/ECCB2015

The second day of the ICCB/ECCB 2015 started with a session that focused on the use and interpretation of citizen science data. The  Symposium Citizen Science in Conservation Science: the new paths, from data collection to data interpretation was organised by Karine Princé and included the following talks:

Bias, information, signal and noise in citizen science data –¬†Nick Isaac – information content of a dataset is question dependent on what was captured and how, as well as survey effort. Data is coming in different ways from a range of people who collect them for different purposes. Biological records are unstructured – they don’t address a specific question and need to know how they come about – information about the data collection protocols is important to make sense of the data. If you are collecting data through citizen science, remember that data will outlive the porject, so need good metadata, and data standards to ensure that it can be used by others. There are powerful statistical tools and we should use to model the bias and not try to avoid it, and little bit of metadata would go a long way so worth recording it.

Conservation management prioritization with citizen science data and species abundance models –¬†Alison Johnston (BTO/Cornell Lab of Ornithology) distribution of species are dynamic and they change by seasons. This is especially important for migratory birds – conservation at specific times (wintering, breading or migrating). The BirdReturns programme in California is a way to flood rice field to provide water-birds habitat, and is an effective and not hugely costly. However, dynamic conservation need precision in information. Citizen Science data can help in occurrence model and want to identify abundance as this will help to prioritise the activities. They used eBird data. In California there are 230,000 checklists but there are biases in the data. There are variable efforts and expertise, and bias in sites, seasons, time. There are also different relationships with habitat, it is also difficult to identify the extreme abundance. They used the Spatio-Temporal Exploratory Models (STEM) which allow modelling with random grids – averaging across cells that have different origins (Fink et al 2010 Ecological Applications). Using the model, they identified areas of high activities – especially the abundance model. Of the two models, the abundance model seem more suitable in using citizen science data for dynamic conservation. The results were used with reverse auction to maximise the use of the available funds to provide large areas of temporary wetland.

Citizen sciences for monitoring biodiversity in habitat structured spaces –¬†Camille Coron (Paris Sud) ¬†described a model estimate for several species and their abundances – they wanted to use several datasets that are at different types of protocols from citizen science projects. Some with strong protocols and some without. They assume that space is covered wtih different types of habitat, but the habitat itself is not known. They look at bird species in Aquitaine – 34 species. 2 datasets are from precise protocols and the third dataset is oportunistics. They developed a statistical model to allow to estimate the data, using a detection probability, abundance, and the intensity of the observation activity. In opportunistic dataset the effort is not known. The model have important gains when species are rare, secondly when the considered species in hardly detected in the data and when there are many species. By using the combined robust¬†protocol projects, the estimation of species distribution is improved.

Can opportunistic occurrence records improve the large-scale estimation of abundance trends? –¬†Joern Pagel – there is lack of comprehensive data large scale variation in abundance and he describe a model that deal with it. The model is based on the assumption that population density is a main driver of variation in species detectability. Using UK butterfly data they tested the model, combining the very details local transects (140 with weekly monitoring) with opportunistic presence recording (over 500K records) using 10×10 km grid. The transects were used to estimate the abundance (described in a paper in methods in ecology and evolution). They found that opportunistic occurrences records can carry a signal of population density but need to be careful about assumptions and there are high uncertainties that are associated with it.

When do occupancy models produce reliable inferences from opportunistic data?–¬†Arco Van Strien (statistics Netherlands) Statistics Netherlands are involved in butterflies and dragonflies monitoring – from transects and also opportunistic data. opportunistic data – unstandardised data, and can see artificial trends if effort varies over time – so the idea was to changes in recorder efforts derived from occupancy models. They coupled two logistic regression models – modelling the ecological process and the observation process. They wanted to explore the usefulness of opportunistic data & occupancy models, and used a Bayesian model, evaluating the results against standardised data. They looked for inferences – phenology (trying to find the pick date in detection), national trend in distribution, species richness per site, local trends in distribution. ¬†The peak date- found a 0.9 correlation between opportunistic data and standardised data. National trends – there is also strong correlation – 0.8/0.9. Species richness – also correlation of over 0.9, but in local trends, the correlation is dropping to 0.4-0.5 for both butterfly and dragonfly. the conclusion – opportunistic data is great and need to be careful about the inference from it.

Making sense of citizen science data: A review of methods –¬†Olivier Gimenez (CNRS) – interest in large terrestrial and marine mammals, they are difficult to monitor in the field and thinking of citizen science data can be used for that. Looked at all the papers with citizen science, and looked as specifically those that look at the data. Wanted to build taxonomy of methods that are used to handle citizen science data. He identified five methods. First, filtering and correction approach – so know or assume to know bias and trying to correct it – e.g. list length analysis. They are highly sensitive to specific biases. The second category – simulation approach, simulate the bias and check how your favourite method behaves given this bias. Third approach is a regression approach – use relevant variables to account for biases -e.g. ecological variables that used to build and predict models, and then use observer bias variables – e.g. distance from cities. The fourth approach is combination approach – combine citizen science data with data from standard protocol to allow to understand and correct the data. The last approach is the occupancy approach – correction for false-negatives and time/spatial variation in detection, so it can be used also extended to deal with false-positives and and also to deal with multiple species. Conclusion: we should focus more on citizens, to describe the models – we need to understand more about them (e.g. record data and the people that collected it) and social science have a major role to play.


In the session paths for the future: building conservation leadership capacity, Kirithi Karanth (Wildlife Conservation Society) looked at ‘Citizen Scientists as agents for conservation‘. In the 1980s WCS started monitoring tigers and some people who are not trained scientists wanted to join in. What draw in people was interest in tigers, and that was the start of their citizen science journey. 5000 km walked in 229 transects in the forest. It started with ecological survey across entire regions from charismatic species but also to rare species. Current project projects have 40-50 volunteer in amphibian and bird survey outside protected areas. The volunteers identify rare species. As project grown, so the challenges – e.g. around human-wildlife conflicts and that helped in having over 5000 villages and 7000 households surveyed in their area. Through the fieldwork, people understand conservation better. Another project recruited 75 volunteer to document tourism impact and the result were used by decision in the supreme court on how to regulate tourism. The have over 5000 citizen scientists, with active group of 1000 at each moment. The impact over 30 years – over 10,00 surveys in 15 states in India, with over 250 academic publications and 300 popular articles. A lot of the people who volunteers evolved into educators, film-makers, conservationists, and also share information blogs, articles, films, activists, and academics. The recognition also increase in graduate programmes – with professional masters programmes. Some of the volunteers – 10% become fully committed to conservation, but the other 90% are critical to wider engagement in society.


Citizens Observatories: Empowering European Society

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)  РThe Omniscientis project (which ended in September) focused on odour monitoring and using different sensors Рhuman 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 ‚ÄúInvolve me and I will understand‚ÄĚ. 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 L√ľtzenkirchen, 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.

International Encyclopedia of Geography – Quality Assurance of VGI

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 , ‚Äėcrowdsourcing‚Äė and that rely on the number of people that edited the information, ‚Äėsocial‚Äô approach that is based on gatekeepers and moderators, and ‚Äėgeographic‚Äô 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 ‚Äėdomain‚Äô approach that relate to the understanding of the knowledge domain of the information, ‚Äėinstrumental observation‚Äô that rely on technology, and ‚Äėprocess oriented‚Äô 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 ‚Äď description of the history of the dataset,
  • Positional accuracy ‚Äď how well the coordinate value of an object in the database relates to the reality on the ground.
  • Attribute accuracy ‚Äď as objects in a geographical database are represented not only by their geometrical shape but also by additional attributes.
  • Logical consistency ‚Äď the internal consistency of the dataset,
  • Completeness ‚Äď 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 ‚Äď this is a fitness-for-purpose declaration that should help potential users in deciding how the data should be used.
  • Temporal quality ‚Äď 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 ‚Äėfitness for purpose‚Äô. 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 ‚Äď 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 ‚Äėweekend bias‚Äô 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 ‚Äėcrowdsourcing ‚Äė, ‚Äėsocial‚Äô, ‚Äėgeographic‚Äô, ‚Äėdomain‚Äô, ‚Äėinstrumental observation‚Äô and ‚Äėprocess oriented‚Äô. We now turn to describe each of these approaches.

The ‚Äėcrowdsourcing‚Äô 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 (‚Äėground truth‚Äô) is required. In such situations, the ‚Äėcrowdsourcing‚Äô 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.

The ‚Äėsocial‚Äô 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.

The ‚Äėgeographic‚Äô 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.

The ‚Äėdomain‚Äô 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.

The ‚Äėinstrumental observation‚Äô 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¬†‚Äėprocess oriented‚Äô 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 ‚Äėauthoritative‚Äô 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 ‚Äď 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 ‚Äď 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 ‚Äď 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‚Äď221.
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‚Äď703.
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.

Third day of INSPIRE 2014 – any space for civil society and citizens?

At the last day of INSPIRE conference, I’ve attended a session about ¬†apps and applications and the final plenary¬†which focused on knowledge based economy and the role of inspire within it. Some notes from the talks including my interpretations and comments.

Dabbie Wilson from the Ordnance Survey highlighted the issues that the OS is facing in designing next generation products from an information architect point of view. She noted that the core large scale product, MasterMap has been around for 14 years and been provided in GML all the way through. She noted that now the client base in the UK is used to it and happy with (and when it was introduced, there was a short period of adjustment that I recall, but I assume that by now everything is routine). Lots of small scale products are becoming open and also provided as linked data. The user community is more savvy – they want the Ordnance Survey to push data to them, and access the data through existing or new services and not just given the datasets without further interaction. They want to see ease of access and use across multiple platforms. The OS is considering moving away from provision of data to online services as the main way for people to get access to the data. The OS is investing heavily in Mobile apps for leisure but also helping the commercial sector in developing apps that are based on OS data and tools. For example,¬†OS locate¬†app¬†provide mechanisms to work worldwide so it’s not only UK. They also put effort to create APIs and SDKs – such as OS OnDemands – and also allowing local authorities to update their address data. There is also focus on cloud-based application – such as applications to support government activities during emergencies. The information architecture side moving from product to content. The OS will continue to maintain content that is product agnostic and running the internal systems for a long period of 10 to 20 years so they need to decouple outward facing services from the internal representation. The OS need to be flexible to respond to different needs – e.g. in file formats it will be GML, RDF and ontology but also CSV and GeoJSON. Managing the rules between the various formats is a challenging task. Different representations of the same thing is another challenge – for example 3D representation and 2D representation.

Didier Leibovici presented a work that is based on Cobweb project and discussing quality assurance to crowdsourcing data. In crowdsourcing there are issues with quality of both the authoritative and the crowdsourcing data. The COBWEB project is part of a set of 5 citizen observatories, exploring air quality, noise, water quality, water management, flooding and land cover, odour perception and nuisance and they can be seen at¬†COBWEB is focusing on the infrastructure and management of the data. The pilot studies in COBWEB look at landuse/land cover, species and habitat observations and flooding. They are mixing sensors in the environment, then they get the data in different formats and the way to managed it is to validate the data, approve its quality and make sure that it’s compliant with needs. The project involve designing an app, then encouraging people to collect the data and there can be lack of connection to other sources of data. The issues that they are highlighting are quality/uncertainty, accuracy, trust and relevance. One of the core¬†questions is ‘is crowd-sourcing data need to different to any other QA/QC?’¬†(my view: yes, but depending on the trade offs in terms of engagement and process) they see a role of crowdsourcing in NSDI, with real time data capture QA and post dataset collection QA (they do both) and there are also re-using and conflating data sources. QA is aimed to know what is collected ¬†– there are multiple ways to define the participants which mean different ways of involving people and this have implications to QA. They are suggesting a stakeholder quality model with principles such as vaueness, ambiguity, judgement, reliability, validity, and trust. There is a paper in AGILE 2014 about their framework. ¬†The framework suggests that the people who build the application need to develop the QA/QC process and do that with workflow authoring tool, which is supported with ontology and then running it as web processing service. Temporality of data need to be consider in the metadata, and how to update the metadata on data quality.

Patrick Bell considered the use of smartphone apps Рin a project of the BGS and the EU JRC they review existing applications. The purpose of the survey to explore what national geological organisations can learn from the shared experience with development of smartphone apps Рespecially in the geological sector. Who is doing the development work and which partnerships are created? What barriers are perceived and what the role of INSPIRE directive within the development of these apps? They also try to understand who are the users?  There are 33 geological survey organisations in the EU and they received responses from 16 of them. They found 23 different apps Рfrom BGS РiGeology and provide access to geological amps and give access to subsidence and radon risk with in-app payment. They have soil information in the MySoil app which allow people to get some data for free and there is also ability to add information and do citizen science. iGeology 3D is adding AR to display a view of the geological map locally. aFieldWork is a way to capture information in harsh environment of Greenland.  GeoTreat is providing information of sites with special value that is relevant to tourists or geology enthusiasts. BRGM Рi-infoTerre provide geological information to a range of users with emphasis on professional one, while i-infoNappe tell you about ground water level. The Italian organisation developed Maps4You with hiking route and combining geology with this information in Emilia-Romagna region. The Czech Geologcial survey provide data in ArcGIS online.

The apps deal with a wide range of topics, among them geohazards, coastline, fossils, shipwrecks … The apps mostly provide map data and 3D, data collection and tourism. Many organisation that are not developing anything stated no interest or a priority to do so, and also lack of skills. They see Android as the most important – all apps are free but then do in app purchase. The apps are updated on a yearly basis. about 50% develop the app in house and mostly work in partnerships in developing apps. Some focus on webapps that work on mobile platform, to cross platform frameworks but they are not as good as native apps, though the later are more difficult to develop and maintain. Many people use ESRI SDK and they use open licenses. Mostly there is lack of promotion of reusing the tools – most people serve data. Barriers – supporting multiple platform, software development skills, lack of reusable software and limited support to reuse across communities – heavy focus on data delivery, OGC and REST services are used to deliver data to an app. Most suggesting no direct link to INSPIRE by respondents but principles of INSPIRE are at the basis of these applications.

Timo Aarmio Рpresented the OSKARI platform to release open data to end users ( They offer role-based security layers with authenticates users and four levels of permissions Рviewing, viewing on embedded maps, publishing and downloading. The development of Oskari started in 2011 and is used by 16 member organisations and the core team is running from National Land Survey of Finland. It is used in Arctic SDI, ELF and Finish Geoportal Рand lots of embedded maps. The end-users features allow search of metadata, searching map layers by data providers or INSPIRE themes. they have drag and drop layers and customisation of features in WFS.  Sharing is also possible with uploading shapefiles by users.  They also have printing functionality which allow PNG or PDF and provide also embedded maps so you can create a map and then embed  it in your web page.  The data sources that they support are OGC web services РWMS, WMTS, WFS, CSW and also ArcGIS REST, data import for Shapefiles and KML, and JSON for thematic maps . Spatial analysis is provided with OGC Web Processing Service Рproviding basic analysis of 6 methods Рbuffer, aggregate, union, intersect, union of analysed layres and area and sector. They are planning to add thematic maps, more advanced spatial analysis methods, and improve mobile device support. 20-30 people work on Oskari with 6 people at the core of it.

The final session focused on knowledge based economy and the link to INSPIRE.

Andrew Trigg provide the perspective of HMLR on fueling the knowledge based economy with open data. The Land registry dealing with 24 million titles with 5 million property transaction a year. They provided open access to individual titles since 1990 and INSPIRE and the open data agenda are important to the transition that they went through in the last 10 years. Their mission is now include an explicit reference to the management and reuse of land and property data and this is important in terms of how the organisation defines itself. From the UK context there is shift to open data through initiatives such as INSPIRE, Open Government Partnership, the G8 Open Data Charter (open by default) and national implementation plans. For HMLR, there is the need to be INSPIRE Compliance, but in addition, they have to deal with public data group, the outcomes of the Shakespeare review and commitment to a national information infrastructure. As a result, HMLR now list 150 datasets but some are not open due to need to protect against fraud and other factors. INSPIRE was the first catalyst to indicate that HMLR need to change practices and allowed the people in the organisation to drive changes in the organisation, secure resources and invest in infrastructure for it. It was also important to highlight to the board of the organisation that data will become important. Also a driver to improving quality before releasing data. The parcel data is available for use without registration. They have 30,000 downloads of the index polygon of people that can potentially use it. They aim to release everything that they can by 2018.

The challenges that HMLR experienced include data identification, infrastructure, governance, data formats and others. But the most important to knowledge based economy are awareness, customer insight, benefit measurement and sustainable finance. HMLR invested effort in promoting the reuse of their data however, because there is no registration, their is not customer insight but no relationships are being developed with end users – voluntary registration process might be an opportunity to develop such relations. Evidence is growing that few people are using the data because they have low confidence in commitment of providing the data and guarantee stability in format and build applications on top of it, and that will require building trust. knowing who got the data is critical here, too. Finally, sustainable finance is a major thing – HMLR is not allowed to cross finance from other areas of activities so they have to charge for some of their data.

Henning Sten Hansen from Aalborg University talked about the role of education. The talk was somewhat critical of the corporatisation of higher education, but also accepting some of it’s aspects, so what follows might be misrepresenting his¬†views though I think he tried to mostly raise questions. Henning started by noting¬†that knowledge workers are defined by OECD as people who work autonomously and reflectively, use tools effectively and interactively, and work in heterogeneous groups well (so capable of communicating and sharing knowledge). The Danish government current paradigm is to move from ‘welfare society’ to the ‘competitive society’ so economic aspects of education are seen as important, as well as contribution to enterprise sector with expectations that students will learn to be creative and entrepreneurial. The government require more efficiency and performance from higher education and as a result¬† reduce the autonomy of individual academics. There is also expectation of certain impacts from academic research and emphasis on STEM ¬†for economic growth, governance support from social science and the humanities need to contribute to creativity and social relationships. The comercialisation is highlighted and pushing patenting, research parks and commercial spin-offs. There is also a lot of corporate style behaviour in the university sector – sometime managed as firms and thought as consumer product. He see a problem that today that is strange focus and opinion that you can measure everything with numbers only. Also the ‘Google dream’ dream is invoked – assuming that anyone from any country can create global companies. However, researchers that need time to develop their ideas more deeply – such as Niels Bohr who didn’t published and secure funding – wouldn’t survive in the current system. But is there a link between education and success? LEGO founder didn’t have any formal education [though with this example as with Bill Gates and Steve Jobs, strangely their business is employing lots of PhDs – so a confusion between a person that start a business and the realisation of it]. He then moved from this general context to INSPIRE, Geoinformation plays a strong role in e-Governance and in the private sector with the increase importance in location based services. In this context, projects such as GI-N2K¬†(Geographic Information Need to Know) are important. This is a¬†pan European project to develop the body of knowledge that was formed in the US and adapting it to current need. They already identified major gaps between the supply side (what people are being taught) and the demand side – there are 4 areas that are cover in the supply side but the demand side want wider areas to be covered. They aim to develop a new BoK for Europe and facilitating knowledge exchange between institutions. He concluded that Higher education is prerequisite ¬†for the knowledge economy – without doubt but the link to innovation is unclear . Challenges – highly educated people crowd out the job market and they do routine work which are not matching their skills, there are unclear the relationship to entrepreneurship and innovation and the needed knowledge to implement ideas. What is the impact on control universities reducing innovation and education – and how to respond quickly to market demands in skills when there are differences in time scale.

Giacomo Martirano provided a perspective of a¬†micro-enterprise ( in southern Italy. They are involved in INSPIRE across different projects – GeoSmartCities, Smart-Islands and SmeSpire – so lots of R&D funding from the EU. They are also involved in providing GIS services in their very local environment. From a perspective of SME, he see barriers that are orgnaisational, technical and financial. They have seen many cases of¬†misalignment of technical competencies of different organisations that mean that they can’t participate fully in projects. Also misalignment of technical ability of clients and suppliers, heterogeneity in client organisation culture that add challenges. Financial management of projects and payment to organisations create problems to SME to join in because of sensitivity to cash-flow. They experience cases were awarded contracts won offering a price which is sometime 40% below the reference one. There is a need to invest more and more time with less aware partners and¬†clients. When moving to the next generation of INSPIRE – there is a need to engage with micro-SMEs in the discussion ‘don’t leave us alone’ as the market is unfair. There is also a risk that member states, once the push for implementation reduced and without the EU driver will not continue to invest. His suggestion is to progress and think of INSPIRE as a Serivce – SDI as a Service can allow SMEs to join in. There is a need for cooperation between small and big players in the market.

Andrea Halmos (public services unit, DG CONNECT) – covering e-government, she noted her realisation that INSPIRE is more than ‘just environmental information’. From DG CONNECT view, ICT enabled open government, and the aim of the digital agenda for Europe is to empowering citizen and businesses, strengthening the internal market, highlighting efficiency and effectiveness and recognised pre-conditions. One of the focus is the effort to put public services in digital format and providing them in cross border way. The principles are to try to be user centred, with transparency and cross border support – they have used life events for the design. There are specific activities in sharing identity details, procurement, patient prescriptions, business, and justice. ¬†They see these projects as the building blocks for new services that work in different areas. They are seeing challenges such financial crisis, but there is challenge of new technologies and social media as well as more opening data. So what is next to public administration? They need to deal with customer – open data, open process and open services – with importance to transparency, collaboration and participation ( The services are open to other to join in and allow third party to create different public services. We look at analogies of opening decision making processes and support collaboration with people – it might increase trust and accountability of government. The public service need to collaborative with third parties to create better or new services. ICT is only an enablers – you need to deal with human capital, organisational issue, cultural issues, processes and business models – it even question the role of government and what it need to do in the future. What is the governance issue – what is the public value that is created at the end? will government can be become a platform that others use to create value? They are focusing on Societal Challenge ¬†¬†Comments on their framework proposals are welcomed – it’s available at¬†¬†

After these presentations, and when Alessandro Annoni (who was charring the panel) completed the first round of questions, I was bothered that in all these talks about knowledge-based economy only the government and the private sector were mentioned as actors, and even when discussing development of new services on top of the open data and services, the expectation is only for the private sector to act in it. I therefore asked about the role of the third-sector and civil-society within INSPIRE and the visions that the different speakers presented. I even provided the example of mySociety – mainly to demonstrate that third-sector organisations have a role to play.

To my astonishment, Henning, Giacomo, Andrea and Alessandro answered this question by first not treating much of civil-society as organisations but mostly as individual citizens, so a framing that allow commercial bodies, large and small, to act but citizens do not have a clear role in coming together and acting. Secondly, the four of them seen the role of citizens only as providers of data and information Рsuch as the reporting in FixMyStreet. Moreover, each one repeated that despite the fact that this is low quality data it is useful in some ways. For example, Alessandro highlighted that OSM mapping in Africa is an example for a case where you accept it, because there is nothing else (really?!?) but in other places it should be used only when it is needed because of the quality issue Рfor example, in emergency situation when it is timely.

Apart from yet another repetition of dismissing citizen generated environmental information on the false argument of data quality (see Caren Cooper post on this issue), the views that presented in the talks helped me in crystallising some of the thoughts about the conference.

As one would expect, because the participants are civil servants, on stage and in presentations they follow the main line of the decision makers for which they work, and therefore you could hear the official line that is about efficiency, managing to do more with reduced budgets and investment, emphasising economic growth and very narrow definition of the economy that matters. Different views were expressed during breaks.

The level in which the citizens are not included in the picture was unsurprising under the mode of thinking that was express in the conference about the aims of information as ‘economic fuel’. While the tokenism of improving transparency, or even empowering citizens appeared on some slides and discussions, citizens¬†are not explicitly included in a meaningful and significant way in the consideration of the services or in the visions of ‘government as platform’. They are reprieved as customers or service users. ¬†The lesson that were learned in environmental policy areas in the 1980s and 1990s, which are to provide an explicit role for civil society, NGOs and social-enterprises within the process of governance and decision making are missing. Maybe this is because for a thriving civil society, there is a need for active government investment (community centres need to built, someone need to be employed to run them), so it doesn’t match the goals of those who are using austerity as a political tool.

Connected to that is the fact that although, again at the tokenism level, INSPIRE is about environmental applications, the implementation now is all driven by narrow economic argument. As with citizenship issues, environmental aspects are marginalised at best, or ignored.

The comment about data quality and some responses to my talk remind me of Ed Parsons commentary from 2008 about the UK GIS community reaction to Web Mapping 2.0/Neogeography/GeoWeb. 6 years on from that , the people that are doing the most important geographic information infrastructure project that is currently going, and it is progressing well by the look of it, seem somewhat resistant to trends that are happening around them. Within the core area that INSPIRE is supposed to handle (environmental applications), citizen science has the longest history and it is already used extensively. VGI is no longer new, and crowdsourcing as a source of actionable information is now with a decade of history and more behind it. Yet, at least in the presentations and the talks, citizens and civil-society organisations have very little role unless they are controlled and marshaled.

Despite all this critique, I have to end with a positive note. It has been a while since I’ve been in a GIS conference that include the people that work in government and other large organisations, so I did found the conference very interesting to reconnect and learn about the nature of geographic information management at this scale. It was also good to see how individuals champion use of GeoWeb tools, or the degree in which people are doing user-centred design.