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This report reviews biodiversity related citizen science in Europe, specifically the data mobilization aspect and gives an overview of citizen science related activities in the project EU BON, the European Biodiversity Observation Network. In addition, recommendations for a Pan-European citizen science gateway and data mobilization efforts will be given, with the aim of filling in existing biodiversity data gaps. Also the EU BON citizen science gateway is described, which is a part of the European Biodiversity Portal (http://biodiversity.eubon.eu) with citizen science related products. The citizen science gateway gives an overview of existing citizen science tools, initiatives and products, information about best practice examples, guidance for uploading and curating data and also make it openly accessible (e.g. via transferring the data to data publishers as GBIF).
Citizen science (CS) is a term which has been used to describe volunteer participation in research or activities which have scientific meaning. The exact meaning and context of the term can vary and sometimes it is used as general notion to describe interactions between science and society. “Public participation in scientific research” (PPSR), “crowdsourcing”, “participatory monitoring” and “citizen observatories” are examples of the terms which are used sometimes as synonyms and some other times covering specific aspects of the broader term “citizen science”. A definition which suits the scope of EU BON project regarding citizen science is offered by Roy et al (
Biodiversity is a widely used term, both in science and policy making. The meaning of the term is often context dependent. One of the policy-related definitions is provided by the Convention on Biological Diversity (CBD): " 'Biological diversity' means the variability among living organisms from all sources including, inter alia, terrestrial, marine and other aquatic ecosystems and the ecological complexes of which they are part; this includes diversity within species, between species and of ecosystems". For science communication purposes there are more accessible concepts for the general public when talking about biodiversity. Meinard and Quetier (
Europe has an active and vibrant community of citizen scientists and their organizations. CS encompasses a wide range of scientific studies, including astronomy, biology and the environmental sciences. However, research related to biodiversity monitoring is one of the most active. The EC-funded project EuMon studied EU-wide biodiversity monitoring methods and systems in 2004-2008. EuMon compiled a database (DaEuMon) of European biodiversity monitoring schemes (at the moment it counts 656 schemes) to draw a first image of biodiversity monitoring in Europe. Among other aspects the project also focused on volunteer participation (
Furthermore, the research landscape is highly heterogenous with regard to the acceptance and engagement of citizen science involvement in research (
The EU-funded project EU BON (European Biodiversity Observation Network, cf.
One of the central tasks is the development of a new open access platform (called the European Biodiversity Portal,
In general, there are a number of contributions of Biodiversity Observation Networks (BONs) towards mobilizing biodiversity information for use by policy development and decision-makers (
Citizen science is a vital element for EU BON with regards to biodiversity information sources that provide data for research and policy-making. CS data are used by many research institutes, public organisations and local data portals (see Suppl. material
With the growing interest of citizens to contribute and participate in scientific research a huge variety and number of CS initiatives emerged. In parallel, the mobilization of citizens to participate in scientific research creates a growing need for systematized, standardized creation of workflows for citizen science data in order to generate scientific knowledge.
A range of CS projects are already active or just recently started its activities and many of them want to learn from existing knowledge, experiences and best practices already gained in former projects (see an EU BON analysis of the current biodiversity data and project landscape in Suppl. material
EU BON has identified the need for a action plan for a pan-European citizen science gateway. The EU citizen science gateway for biodiversity data is in essence a CS network for biodiversity information. It offers information for CS project leaders, project members and citizen science stakeholders (environmental agencies, municipalities, educational institutions, NGOs etc) in Europe. The EU BON proposed CS gateway includes a wealth of information on CS project designs, standards in use, directories of projects and SC data providers (Suppl. material
Although the EU BON citizen science gateway builds on many extant initiatives and networks, it should also provide an overview of them and aim to provide additional important support for overcoming the problems caused by the limitations existing with current portals. One of the main data providers for biodiversity data is the Global Biodiversity Information Facility (GBIF) that also offers a quite significant amount of CS data. To make publishing in GBIF easier, EU BON offers centralized entry points for data holders - as an instance of Integrated Publishing Toolkit and PlutoF biodiversity data platform.
There are other portals that offer CS data but they have some limitations for European stakeholder: for the USA there is a portal called Scistarter (
Hence, EU BON promotes (cf. EU BON citizen science gateway) and recommends some tools and platforms for data curation and upload in order to overcome existing limitations.
In this paper we will present some of the major work and achievements of EU BON related to citizen science:
(a) experiences in linking networks and main actors of citizen science on a European scale,
(b) work on data governance and requirements: data standards, quality and intellectual property rights,
(c) EU BON citizen science gateway as a model for improving the European CS data landscape in Europe,
(d) and finally the conclusions and recommendations to the European Commission.
An important task of the citizen science gateway is, in addition to providing tools and the technical infrastructure, to establish a close cooperation between the main actors of CS on European scale. There are many projects, initiatives and networks that focus on citizen science or that involve citizen scientists, for example in data collection and monitoring of species. Best practices, experiences and tools should be shared, discussed and further developed and common approaches are needed in order to avoid duplicating efforts. Other challenges, specifically for citizen science data exist and common solutions need to be established that could be only found by a close cooperation of networks, projects and individual researchers and citizen scientists.
Citizen science is highly relevant to European biodiversity networks, not only for exchanging knowledge and actively engaging citizens in biodiversity related issues but also for obtaining valuable data that can be used for science and policy (e.g. reporting). For example, monitoring programmes rely heavily on the participation of citizen scientists. The EuMon project had documented 395 monitoring schemes for a set of taxonomic groups (plants, birds, amphibians and others). These monitoring schemes alone involved more than 46,000 persons who contributed over 148,000 person-days/year to biodiversity monitoring activities (
In a EU BON workshop it was shown that lots of data generated by citizen science projects cannot be used due to data usage restrictions. As an analysis of Nils Valland shows, of the around 570 million records of species occurrence data that were collected with the help of citizen scientists, only 100 million records are available via GBIF, which means only around 18% (see Fig.
These cases illustrate that considerably more data could be made available with the help of projects such as EU BON. To achieve this, good communication and exchange of ideas within CS networks and with other initiatives and projects are needed. The individual researchers need appropriate tools for data mobilization; they need databases where the data can be hosted and curated and where quality control can take place; finally they need help in making the data openly available, for example to GBIF or to open repositories such as Dryad or others to ensure that data will become discoverable in the GEOSS data portal (
Data mobilization is also important as many data gaps exist on a European scale with regards to biodiversity information. An EU BON analysis of data mediated by the Global Biodiversity Information Facility (GBIF), one of the most important European and global mediators for biodiversity data, shows that data are still biased, for example, there are spatial gaps in Eastern European countries (
Data quality is another important topic that needs to be focused on when dealing with citizen science projects. Generally it was shown that CS initiatives can provide an important data source for research, eBird data for example has been used in at least 90 peer-reviewed scientific articles on climate change, ecology and other types of research (
Many initiatives, projects and networks in Europe are already collecting, integrating and engaging citizen science based biodiversity data and activities. One group of stakeholders are end-users of the generated data (e.g. researchers, governments and political administration), another one are volunteers and citizen scientists and both groups have their own interests, intentions and aims they follow (
A major task for the EU BON citizen science Gateway is to improve CS data workflows from data collection to facilitate and enable data analysis and dissemination of the results. Products, capacities and tools improved, developed and implemented on the EU BON portal can serve this purpose. Exposing these tools and technological infrastructure will improve the frameworks of biodiversity related CS data workflows in Europe. In parallel, and not less important, is to verify aligning with requirements of the various stakeholders to harmonize with the activities of the other major players in citizen science. To assess researchers in particular in that regard, EU BON conducted a survey in 2014 (Suppl. material
As mentioned before, the European Citizen Science Association (ECSA) is an important player in CS networking, a non-profit organization to foster citizen science activities on a European scale. Over 150 individual and organizational members from 28 countries participate in the report with the main aim to link citizens and science (
Abovementioned GBIF became a major player and leading facilitator in providing open access to data on global scale. GBIF promotes open standards and free tools for biodiversity data management and exchange (see more for example on the GBIF Integrated Publishing Toolkit (IPT) in chapter Data governance). Among sources of GBIF-mediated citizen science data are networks and tools such as eBird (more than 150 million observations worldwide), iNaturalist and others (e.g. anymals+plants, Diveboard, Scandinavian networks).
Many European countries provide considerable amounts of citizen science-based data in GBIF (Table
One of the tasks in the data workflow is also to make data that was mobilized by EU BON available in GBIF, hence a close collaboration is key. One of the achievements of the project is the development of a spatial dataset browser and a species trends visualization tools that are part of the work of the European biodiversity portal. These tools help to visualize CS-derived observation records and also increase the discoverability of data.
Many European projects are contributing biodiversity data by involving volunteers that help in data collection and processing. Also there are sometimes similar efforts to integrate data and develop tools. A close link to ongoing projects in the field of CS is needed to avoid duplication of efforts and to find synergies among the projects. There have been specific EU-funded projects with similar intentions on building networks and harmonizing data. For example citizen science observatories - community-based environmental monitoring and information systems, in order to stimulate novel Earth observation technologies, exploiting capabilities of portable devices and collective intelligence and to enable participation of citizens in local stewardship. A closer exchange was conducted with three of the five observatory projects, moreover a more formalized cooperation was initiated with the project Socientize by signing a Memorandum of Understanding. The project Socientize had an open and collaborative approach by coordinating and linking participatory projects and actively engaging scientists and citizens that contribute with their knowledge and resources. Several projects were conducted, e.g. on urban bees, and by drafting policy recommendations based on the projects experience. Another project with a closer linkage was a Citclops (
Generally, it is interesting to put a specific light on the biodiversity data generated in citizen science projects. As a EU study shows, more than half of the projects last for more than 4 years, this indicates that these projects could potentially produce data and time-series for detecting changes over time, i.e. for producing long-term time-series (
An important way to facilitate exchanges between main actors and interest groups in EU BON were the Stakeholder Roundtables, a series of four meetings that aimed to enable discussions among relevant stakeholders (Fig.
For the citizen science related-tasks, such meetings and roundtables are needed for:
generally for connecting EU CS initiatives and networks and to allow feedback on the different approaches and exchange of ideas and strategies,
finding solutions for existing problems (filling data gaps, workflows from data collection to analysis and dissemination, development of tools for data collection and curation),
derive success factors of citizen science projects (lessons learnt, guidelines and methods to obtain adequate and high quality data),
share best-practice examples from existing projects in different levels (from the project level to policy recommendations),
facilitating new (technological) developments of portals, tools and databases by joining forces.
During the roundtables, citizen science subjects were discussed in many working groups, world cafe sessions and are part of products of EU BON, e.g. in the European Biodiversity Portal.
One of the roundtables particularly addressed this topic, i.e. the 2nd EU BON Stakeholder Roundtable that took place in Berlin in November 2014 with the title “How can a European biodiversity network support citizen science?”.
At the roundtable, various stakeholders from the field of citizen science were invited to discuss possibilities of interactions and the role of EU BON for supporting citizen science on a European scale. Addressed stakeholders were different citizen science projects, researchers and biodiversity networks.The aim of the roundtable on citizen science was to explore how and with which means EU BON can support citizen science activities and to connect the projects of EU BON consortium partners with other European initiatives. The project may act as data portal to find the right data base for the data, EU BON may provide tools to visualize and interpret data, EU BON may provide tool to assess the quality of data and link it to broader information pools such remote sensing data or modeling information. However, also the citizen science community was asked what it expects from EU BON.
The discussions and linkages at the roundtable were an important kick-off for the further work with other networks, such as ECSA and connections to other projects. In the course of the project, some important recommendations were drafted and experiences shared that helped to improve the citizen gateway approach. There are also some critical success factors for citizen science projects that aim to gather data for observation records, for example:
Data quality (Effective user interface and rich user services needed, relevance, e.g. environmental impact, cooperation of governmental institutions and NGOs),
Data quantity (Not anonymous, visibility: report first - quality control second, informal voluntarily community, quality control, validation on priority species, cooperation of governmental institutions and NGOs),
Accessability (effective data distribution, open data and clear license information).
Overall, a tight exchange with stakeholders, e.g. citizen science projects, networks and initiatives is needed in order to include feedback mechanisms to adapt the original plans that were foreseen when writing project proposals. However, particularly in the rapidly evolving field of citizen science, European projects and web-based technology, such as smartphone applications it is important to conduct such feedback loops for adaptive management and reducing the duplications of efforts with regards to theoretic frameworks, infrastructure and technology.
Biodiversity data from some regions of Central and Eastern Europe are still only partly shared to global infosystems and is often fragmented, as identified by the EU BON project (
To draw focus on the potential of CS for biodiversity data mobilization, EU BON project organized a workshop specifically aimed at Eastern and Central European countries. During the citizen science workshop in Tartu (Estonia) that took place from 27-28 June in 2016, the participants analyzed how people and institutions that work on citizen science could more effectively collaborate, how they could share their data efficiently and what useful best practices exist. Participants identified solutions for better networking. For effective collaboration there is a need for improving the knowledge base. In order to achieve this goal, it was proposed to develop a special training program that could be organized by recognized expert organizations or institutions (like the European Citizen Science Association). For local counseling a solution could be to appoint a “community manager” or middleman (facilitator) who can advise both researchers and project managers how to communicate with volunteers (participants) in the best way, and to advise which methodology and standards should be used for data handling. Training of such community managers could be supported by European central institutions and ECSA could also be involved. Although bottom-up initiatives should be encouraged and are crucial for a long-term sustainability of citizen science, the countries with only little history of community-based research initiatives would benefit from top-down approach for building up the knowledge base and assistance network for citizen science. The existing networks of knowledge like schools would be a possible solution for citizen science community hubs. Data sharing is an important part of keeping citizen science approaches sustainable to ensure a long-term availability of data and in order to close temporal gaps of data. In order to reuse and harmonize data, it will be crucial that CS projects apply standards to enable data integration and interoperability. However, the ultimate challenge for any initiative is securing the funding. Clear funding mechanisms for citizen science can help to start new projects with strong predisposition for success so there is an urgent need for enhanced funding mechanisms from national governments and the EU. The most important players in the CS network that were, identified at the workshop are policy makers, key scientists, NGOs and opinion leaders - all these need to be involved for establishing successful CS initiatives in Eastern and Central European countries.
Data governance in biodiversity research starts with the data collection and ends with the data use and data analysis. But also the visualization of data is an important part, and projects developed visualization tools which allow an easy data presentation for different stakeholders. Data collection starts with designing data forms, developing observation portals or mobile applications. Working with citizen scientists also includes the communication of data collection methods to participants. Storing data by research institutions or government agencies need substantial resources for technical equipment, software and IT specialists and also for the provision of data to data mediators, for example to GBIF, trained people are needed. This also demands resources for maintenance and development of IT systems. A common data governance system from CS observation to GBIF data repository and stakeholders is depicted in Fig.
An important aspect of data standards relates to the question of how citizens collect data and how reliable and repeatable they are. Sporadic reports of one species or another may be valuable, but any form of comprehensiveness and repeatability increases the quality of the data collected. Systematic monitoring schemes put particular effort into harvesting repeated observations, with known (or set) sampling effort, of all species at a given site. Data are much more scientifically valuable if they come from the same sites, multiple times within the year and over multiple years. Furthermore, such data can be improved with reports that include all species, preferably with an indication of abundance, because this open the route for key ecological analyses including population trends, changes in community structure and other metrics related to of populations, species and communities that form key EBVs (Essential Biodiversity Variables). Such data are illustrated in the examples of systematic monitoring of birds and butterflies.
Biodiversity data are highly heterogeneous due to the high diversity of observed taxonomic groups, the observation methods used and the different data types. Ensuring data interoperability was also one of the central aims of the EU BON citizen science gateway. There is an urget need for data standardization, and the standardization and data aggregation has to be done in such a way that it is both human and machine readable.
In the biodiversity research community the need for a common ground in terminology has created a well-known and broadly accepted standard called Darwin Core (DwC) with a set of terms with clearly defined semantics (
The Global Biodiversity Information Facility (GBIF) Integrated Publishing Toolkit (IPT) (
There are also other biodiversity data standards which are relevant for citizen science, for example Access to Biological Collections Data (ABCD).
Standardized metadata are another important aspect to achieve interoperability and to enhance the usefulness of data. The Ecological Metadata Language (EML) is a widely used metadata standard for biodiversity data. Metadata describes the underlying basic features of a dataset for its identification and helps to increase data discovery, e.g. by providing information on when data was collected, where it was collected and by whom etc.
In addition to biodiversity data standards the citizen science itself is also subject to standardization regarding its metadata. Although numerous surveys have been conducted on testing and employing the mechanisms on citizen science projects to ensure scientific quality, a recognized framework of standards for projects hasn't been formalized yet. There are quite many inherent differences among the citizen science projects with regards to their subject, structure, timespan, volunteer motivation and qualification etc. Due to the diversity of the projects, a standardized evaluation of the projects and data is quite challenging. Hence, the standard metadata for CS must include a broad range of field terms to ensure full coverage. Worth mentioning is a new initiative (PPSR_CORE where PPSR stands for “public participation in scientific research”) by the Citizen Science Association (
Public participation in scientific research and the use of volunteers helps to collect an extensive amount of data across large areas and over a long time span. However, data quality remains a primary concern for the research community as the data come from a large and often unknown population of volunteers with different levels of expertise (
A plethora of different methods, models and mechanisms exist that aim to enhance the reliability and thereby quality of community-generated data in citizen science. Most projects that have high quality standards employ multiple mechanisms to ensure data quality and appropriate levels of validation. If data collection is following standards, it is possible to apply big data methods for building species distribution models from citizen science data (
There are several error sources that negatively affect CS data quality, such error sources are for example:
Errors in the identification of species, i.e. a misidentification of many species by the data collectors,
Inaccurate measurements in the field (e.g. geolocation of observations, environmental conditions),
Inadequate sampling design.
In addition to the pure methodological errors, often there are biases in data collection, especially for sporadic data, with a well-known tendency of observers to report on rare rather than common species, and especially to report unique observations - i.e., when species are observed out of their distribution area or period of occurrence. These create “conceptual errors” that require consideration by data users.
There are also different means to improve data quality that could be categorized by measures that take place before, during and after data submission.
The non-exhaustive list of measures to increase data quality includes:
standardize sighting and monitoring protocols, designed by professionals: this is one of the key means to ensure highest data quality, and one which requires highest attention - as with good (and known) standards one can use even the simplest data,
training workshops during the recruitment of volunteers,
providing introductions and educational materials in order to improve the skills of the participants,
regular monitoring of the performance to ensure that training and sampling design remain adequate,
employing online data entry forms with automated error checking capabilities,
screening and validation of potentially erroneous observations,
developing smart filters to identify potentially erroneous observations,
employing a confirmation process by expert reviewers,
deploying query based algorithms on historical data to flag species that are reported out of its usual distribution range,
using mobile applications that allow automated entries such as of geolocated specimens associated with a species sighting.
Citizen-science projects must apply standards for all phases of the data workflow. Standards must become widely accepted as a valuable research tool also for volunteer-generated data where a large number of people participate that have a varying level of expertise. Within the context of biodiversity-related projects, standardization is needed for the taxonomic identification, for monitoring and sampling protocols, for confirmation protocols as well as data fields and formats (e.g. date, time, units) and geolocation. For a validated, confirmed dataset which is targeted for data publication, the next step of standardization would be to qualify it for publishing with a standard biodiversity publishing tool, such as the GBIF IPT. This process involves the mapping of data-fields to comply with standards such as Darwin Core (DwC) or EML. The result is the provision of interoperable data, see also the GBIF manual and guide (
Factual data, such as collected by citizen science projects, is not subject to intellectual property rights (IPR) regulation as such, since it is not a ‘creation of the intellect’. Reuse would however still require an examination of the data to ensure it does not contain copyrightable work, and a database as a whole may be assigned
GBIF summarizes its mission as that of making biodiversity information “freely and universally available for science, society and a sustainable future” (
CC0 1.0, under which data are made available for any use without restriction or particular requirements on the part of users
CC BY 4.0, under which data are made available for any use provided that attribution is appropriately given for the sources of data used
CC BY-NC 4.0, under which data are made available for any use provided that attribution is appropriately given and provided the use is not for commercial purposes.
As of August 2016, datasets that were not assigned one of these licenses were no longer distributed through GBIF. This caused a decline in GBIF mediated data of 48.7 million records (7.5 per cent of the total number of records), because several data publishers did not select one of these licenses for their data before the deadline expired (GBIF 2016).
The GBIF case illustrates the trade-off between larger amounts of data due to a liberal licensing policy towards the data provider in which usage restrictions can be applied freely, and a policy limiting the restrictions a data provider can place on the data in order to accommodate reuse of especially larger datasets. At the same time it illustrates the difficulty of altering licensing policies at a later stage, as this requires data providers to reconsider the limits they wish to impose on usage by others and communicate their choice. It is advisable to specify the objective of the citizen science project and implement a licensing policy in line with this objective from the onset of the project. Within the scope of the EU BON project the emphasis lies on making reuse of biodiversity data both easy and legal, resulting in the recommendation of the CC0 waiver and the CC BY license (
The EU BON citizen science gateway also led to the development of several products in order to obtain an enhanced knowledge on CS biodiversity data, as well as to provide useful tools and key infrastructures for citizen science projects and researchers. Firstly, the EU BON citizen science gateway provides, via the EU BON European Biodiversity Portal, an overview of existing citizen science data providers (
Biodiversity data that was collected with the help of citizen scientists come from many different initiatives and projects. To give an overview of potential CS data sources, EU BON developed an overview of CS-based datasets that not only lists valuable CS data, but also gives additional information on the data providers itself. The list of data providers include leading CS-based biodiversity observation data providers and gives information, e.g. on the origin of the data (e.g. management, collections), type of taxa included, number of records, number of rapporteurs.
The source list of the data providers is managed via the PlutoF platform (
A key task of EU BON was the development of mobile phone applications (“apps”) for the citizen science data collection, for example “I saw a butterfly” for sporadic data collection or the 'BMSapp' (“Biodiversity Monitoring Schemes”) apps for systematic monitoring of any transect-based list of taxa, e.g. butterfly of an amphibians. “I saw a butterfly” is communicates with the PlutoF-API to store observations.
There are several reasons that stress the need for the development of mobile phone applications. A survey among the Butterfly Monitoring Scheme (BMS) members reveals that a main barrier in reporting is the time-consuming insertion of data by typing. This compromises in many cases the accuracy of the reported data, both in terms of spatial accuracy and additional information such as altitude, temperature or humidity. Mobile devices equipped with high-end applications can resolve many of these barriers based on the design concept of obtaining a maximum amount of data with minimum typing while allowing volunteers to focus on observing rather than typing. The concept involves getting automatic and implied data, thus relying less on user skills. Here are some examples of these practices, currently in use for bird and butterfly monitoring:
GPS is constantly activated and provides information on the spatial location (coordinates) as well as on altitude, spatial accuracy, exact date and time for every reported specimen,
Activation of camera enables adding documented records, improves validation capacity and may further contribute to learning about host plants and habitat,
Weather data can be extracted both directly by the application and indirectly by linking to weather models or nearby meteorological stations,
Speed of advancement on terrain can provide a measure of sampling-effort (e.g. for transect monitoring),
Using a standard species list as a reference, resolves typing errors and taxon mismatch,
Enabling profiled-based species list, e.g. by country, region, season or ranking of species according to “most observed”, eases the typing and enables on-the-ground validation (e.g., feedback to observer if reporting a species out of its season or distribution range),
A simple guide (pictures, basic info) can aid identification (may also enhance the interest of volunteers in the application, and useful for learning and self-validation),
For species not easily identified by sight, the guide may include audio files (and consequently the app should allow for audio recording of the subject) or images of the spoor or other relevant information.
There are some recommended design consideration for mobile applications, that were also implemented in the EU BON CS applications (for a list of the recommended design considerations, see Table
Over the past years there have been many projects and initiatives which have produced very useful internet-based tools and guidelines for citizen science. EU BON gathered a selected list of them in the form of a directory. The tools presented in the directory are searchable by tags which cover topics such as biodiversity data management, project management, publication, taxon identification etc. The ‘Directory of CS Tools’ is administered via EU BON portal CMS (content management system). Although this directory is part of the EU BON portal and does not need special care of data integration in the future, maintaining the directory still needs special attention, such as verifying URL links or updates e.g availability, change of tool usage policies or adding new tools. If the future gateway is managed by a CS network institution as ECSA or major science infrastructure as LifeWatch, this work can be integrated with other information services.
As an EU BON survey on volunteer involvement shows, there is a huge potential for citizen science participation in many research projects. However, there are still many barriers that prevent project managers and scientists from involving citizen scientists and many projects need guidance in recruiting and training volunteers and generally in setting-up projects that enable a sound citizen participation. To make the CS project managing easier, EU BON provides a step-by-step guide on the proper design and management of citizen science projects that focus on biodiversity monitoring. With the help of this guide, users such as citizen science project leaders are pointed to a suitable PlutoF module. The guidelines will be further developed and improved until the end of EU BON project. Working with the guidelines is part of information management via the EU BON portal CMS. It is advisable to merge this job with other information services on CS gateway.
This module (see the chapter 'Best practice cases') which operates as a workbench provides users with tools and services to create, manage and share their biodiversity observation projects. However, its database is also used as the source for some content that is available on the EU BON portal. Furthermore, PlutoF is also linked with citizen science mobile telephone applications, such as the butterfly sighting app by GlueCAD and animal sound recording app by the University of Tartu).
PlutoF is a part of science infrastructure for Estonian research institutions and is being developed and maintained by the University of Tartu Natural History Museum. PlutoF workbench is open for all users worldwide. PlutoF also encourages its users to keep data open. Development to enable integration of biodiversity systematic monitoring data from mobile app (e.g. the new BMSapp from GlueCAD) is possible with PlutoF API.
To help citizen science initiatives manage bidoversity monitoring related aspects of project management, EU BON provides different best practices case descriptions on webpage. Some of these examples are presented in supplementary file (Suppl. material
Citizen science is a powerful ally to biodiversity research and conservation. Although it has its limitations and weaknesses, which are constantly being analyzed, previous findings suggest that it has the potential to deliver valuable data for science (
In 2014 the EU project Socientize published a white paper with policy recommendations for CS in general and more particularly in Europe. The work behind the white paper is thorough and results are also relevant for biodiversity research. Its main action points for European policy: integrating CS into existing funding schemes and designing new programmes specifically for CS. From the proposed support measures the data policy will greatly affect the CS gateway. Quality, interoperability and data IPR issues are aspects to consider when reviewing the policy. Open data is a recommended first choice of any CS biodiversity data. EU BON will support the proposed actions and measures of the white paper of Socientize. EU BON findings on regional biodiversity data gaps indicate the importance of supporting central and eastern European countries in their efforts to integrate citizen science in biodiversity research, monitoring and management so that data gaps in these countries could be filled in.
In addition to that, EU BON proposes the formation of a European-wide institution for CS data mobilization. EU BON has identified more than 80 current CS systems in Europe (see Suppl. material
This institution, together with GBIF, should have the task to approach and negotiate with current reluctant European system owners aiming to share data with open licenses (CC BY 4.0).
The target data owners should be institutions and organizations with systems containing large amounts of data, starting with data owners with public funding.
The geographical target areas should be countries or European regions with gaps in data availability.
The targets should cover both scientific institutions collaborating with naturalist NGOs and community based organizations with a potential for data sharing.
For identifying the targets it would be helpful to maintain the EU BON database of current European CS systems and their metadata.
Also, a financing mechanism should be provided for facilitating the CS system development and implementation in countries and regions with few, small or non-existing efficient systems for species sighting and data sharing - with particular emphasis on an urgent need to establish systematic monitoring schemes where these are not yet implemented. These implementations should be supported by governmental institutions (for sustainable funding and system operation), scientific institutions (for quality control and validation) and naturalist NGOs (for community relevance and voluntary contribution).
Citizen science initiatives are a mix of bottom-up and top-down approaches without an official agreed-upon structure to represent every stakeholder in Europe. However, a relatively new NGO is gaining momentum - European Citizen Science Association (ECSA). It has links to nearly every major CS organisation or initiative and also a very strong cooperation with US and Australian counterparts. EU BON sees ECSA as a key organization in networking role in Europe and also for future development of CS gateway for biodiversity data. There is also the Citizen Science Alliance which hosts a collection of CS projects in its “Zooniverse”.
EU BON advocates supporting citizen science projects that follow acknowledged biodiversity data standards, open data principles and publishes the data through recognized data portals such as GBIF.
While the huge data flow of community-based observations is streaming in, active measures to develop and provide standards are the key for future developments and effective usage of these CS-generated data. Standardization will pave the way to process large amounts of CS data in order to use it for scientific research and analysis. Components of such standardization should include the promotion of repeated observations in fixed sites (within and among years), communicating with citizens the value of reporting full species’ lists, and the use of known observation methods through systematic and coordinated schemes. A frame of CS-standards for biodiversity research should include: Metadata fields for a list of topics to cover for projects definitions, volunteer skills, education and training frame, protocols, data validation methods, annotation and confirmation protocols.
CS communities which actively take part and volunteer in systematic monitoring programs (e.g. on birds or butterflies) have a high awareness of their environment and are particularly interested in conservation-related questions. This has empowered them to try to influence local and regional decision makers and there are many examples where such activities have prevented or changed potentially environmentally damaging policies or projects.
However, the link between CS data and policies remains often loose due to the lack of systematic prioritization of monitoring efforts (
EU BON should consider how to encourage or even support CS initiatives, and should support the expansion of citizen engagement from “just” performing observations, to becoming partners in a broader range of activities along the process of scientific research - including study (co-)design, experimentation and joint learning - whereby the broader sense of citizen science can be achieved.
A major obstacle for almost all CS initiatives is the funding issue, partly due to the assumption that is often taken by policy-makers and other data users that “voluntary data are free”. In reality this is far from the truth: the activation, recruitment, training and coordination of CS activities; followed by data validation, extraction and analyses; all require expenses both for coordination and IT support, without which such initiatives fail to exists. In many cases, prudent collaboration with like-minded organizations, communities or governmental projects can provide a starting point, but recognition by leading institutes to the costs of operating CS activities, may serve an important step in capacity building. An EU based consultant group of advisors who are familiar with the funding application processes related to the topic could help these initiatives to come alive.
The authors would like to express their gratitude for the help on reviewing the document and giving advice on content to: Christos Arvanitidis, Kyle Braak, Anke Hoffmann, Patricia Mergen, Dirk Schmeller, Larissa Smirnova, Tim Vincent, Lauren Weatherdon.
This paper was supported by the EU BON project which is a European Union’s Seventh Programme for research, technological development and demonstration under grant agreement No 308454.
EU BON - Building the European Biodiversity Observation Network
This paper was supported by the EU BON project which is a European Union’s Seventh Programme for research, technological development and demonstration under grant agreement No 308454.
EU BON - Building the European Biodiversity Observation Network
Totally recorded occurrences in 80 European CS data portals and publicly shared in GBIF.
Break-out group discussion at the 2nd Stakeholder Roundtable (Credit: Florian Wetzel)
Peacock Butterfly
European Starling
Biodiversity observation - from observation to data usage
Citizen Science data on GBIF ranked by countries (GBIF 2016)
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Sweden | 41630932 | 1 |
United Kingdom | 21905500 | 2 |
Norway | 16564959 | 3 |
Finland | 15847030 | 4 |
Denmark | 6628842 | 5 |
Germany | 5390347 | 6 |
Ireland | 2316795 | 7 |
Belgium | 1625973 | 8 |
Netherlands | 1386167 | 9 |
Estonia | 921998 | 10 |
France | 578567 | 11 |
Spain | 561098 | 12 |
Portugal | 257531 | 13 |
Switzerland | 151680 | 14 |
Austria | 16469 | 15 |
Design consideration for mobile applications that were also implemented in the EU BON CS applications
Basically there would be two different schemes for the app, one for sporadic recording and the other for systematic monitoring. Android, iOS Observer receives User-ID upon registration plus limited access-writes to edit his/her own data. Provide users with common-names (Nomenclatural) to select from in addition to scientific names Multilanguage support Basic data validations (e.g. numeric values) predefined set of required fields according with a selected protocol, minimum typing (e.g. select from list of specimens). use standard taxonomy lists (e.g PlutoF taxonomy backbone) profile based lists e.g. by country, season etc. allow taking pictures for documentation Http-based/post (preferred) , data export per sight (no batch mode) Employ server's API for data validation, writing to database, import and save pictures network links, to be serviced by the EU BON citizen science portal (e.g. to GBIF) enable offline recording (Autosave data locally on device memory if communication fails) database platform - MySQL, PostgreSQL , MS-SQL, etc taxonomy standards of species lists - ITIS, IOC etc configuration/scheme to support publishing to GBIF (DwC metadata field names) honor licenses (data and multimedia ownership, sharing etc) User interface – enable observers to edit their own data Sighting approvals - by expert, with feedback to observer Quality Management - alert sightings which are out of distribution range, season etc. |
Citizen Science species occurrence data availability in Europe
Data type: Database references
Brief description: Species occurrence data sources metadata
A list of data providers who collect, store and share SC taxon occurrence data. The list gives information on the names of institutions, contact emails, species groups, number of records, sharing availability, number of contributors etc.
File: oo_112398.xlsx
EU BON survey on citizen science data use among researchers in biological sciences
Data type: survey
Brief description: EU BON conducted a survey to assess how willing are researchers to recruit volunteers in their work, what are the main effects, motivators and hindrances.
File: oo_112400.docx
Citizen science and biodiversity observations – EU BON best practice cases of initiatives, systems and tools.
Data type: list of best practice cases
File: oo_113205.pdf