This section explains how the conceptual model for citizen science can be used in specific case studies, that is, how the different characteristics of a project – its participants, its data, etc. – can be described by using the model. The case studies represent projects with different domains, community sizes, and types of participation in order to demonstrate the breadth of citizen science applications that the model can accommodate. The first sub-section highlights four different projects. Here we demonstrate how they can be described with the help of our model in order to understand project content and metadata. The second sub-section illustrates another use for our model: the application of its concepts and structure for (1) creating project descriptions in a specific inventory and (2) structuring data collection.
Instantiation of Projects
After providing a short introduction to the four selected citizen science projects, we use our conceptual model as a skeleton for each specific project. Where applicable, the concepts (as depicted in Figs. 9.3 and 9.4) have been instantiated for each project; see Tables 9.2 and 9.3. In other words, a concept is assigned a project-specific value where possible and applicable. This means that specific projects, their activities, participants, data outputs, etc., are described with the help of the conceptual model. Using this common model allows the projects to be compared and combined, thus increasing interoperability between the projects and their elements. It should be emphasised that in the tables only a few examples are provided and that each entry in the table corresponds to a concept in the model, which is more than just a flat table. For example, a project can have multiple participation tasks, each using different tools; and a project can produce multiple, different datasets, and so on. We will now introduce our case studies.
OpenStreetMap. OpenStreetMap (OSM) is a well-known crowdsourcing project in which thousands of volunteers maintain an online map of the world. OSM has all the characteristics of participation and data handling we see in many other citizen science projects. In addition, OSM is an essential geographical reference for many citizen science projects.
Bash the Bug (Zooniverse). The objective of the Bash the Bug project is to improve tuberculosis diagnosis. The task of the volunteers is to accurately determine which antibiotics are effective for each of the collected tuberculosis samples. This is carried out by analysing pictures of plates showing the effects of several antibiotics on the tested sample.
Mars in Motion (Zooniverse). Mars in Motion was created to look for and identify geological changes on the surface of Mars over time by gathering in-depth data on the type of features that are detected. It is part of the i-Mars.eu project, which includes several European partners, and is focused on developing tools and datasets to increase the exploitation of space-based data from the US National Aeronautics and Space Administration (NASA) and the European Space Agency (ESA) Mars mission beyond the scientific community.
MICS. The MICS project provides an integrated platform of metrics and instruments to measure both the costs and the benefits of citizen science. These metrics and instruments consider the impacts of citizen science on the following domains: society, governance, the economy, the environment, and science.
Deployment of the Conceptual Model
In addition to the basic metadata provision outlined in the previous section, the conceptual model can be used as a structure for project-related activities. Two case studies are provided here.
JRC Citizen Science Project Inventory
The European Commission Joint Research Centre (JRC) has developed a multidisciplinary data infrastructure (Friis-Christensen et al. 2017) to facilitate open access to its research data, in line with the recent open data trend (Trojan et al. 2019). The JRC Data InfrastructureFootnote 14 has helped establish requirements for dataset metadata. The JRC datasets are published in the JRC Data Catalogue and are described by metadata that follow a modular metadata schema. The schema consists of (1) a core profile which defines the common elements of metadata records, based on the reference standards DCAT-AP (ISA DCAT-AP 2015) and DataCite (2016), and (2) a set of extensions, which defines elements specific to given domains (geospatial, statistical, etc.), based on existing metadata standards.
In addition, the JRC Citizen Science Project Inventory has supported the JRC in describing projects. The JRC Citizen Science Project Inventory was initially developed as one of the outcomes of the study Citizen Science for Environmental Policy: Development of an EU-wide Inventory and Analysis of Selected Practices (Bio Innovation Service 2018; Turbé et al. 2019). This project was executed by the European Commission (DG Environment), with the support of the JRC. The project also included additional contracted partners: the Bio Innovation Service (France), the Fundacion Ibercivis (Spain), and the Natural History Museum (UK). The main objective was to build an evidence base of citizen science activities to support environmental policies in the European Union (EU). Specifically, the goal was to develop an inventory of citizen science projects relevant to environmental policy and assess how these projects contribute to the United Nations Sustainable Development Goals (SDGs). To this end, a desk study and an EU-wide survey were used to identify 503 citizen science projects of relevance to environmental policy. The resulting project inventory has been published in the JRC Data CatalogueFootnote 15 and is updated on a regular basis (it also considers new entries suggested via an online survey).Footnote 16
The Citizen Science Explorer,Footnote 17 a dynamic catalogue provided as part of the JRC GitHub space, has been developed to provide more visibility to the JRC Citizen Science Project Inventory and to showcase the opportunities for knowledge sharing and management. The inventory is available in the form of comma-separated values (CSVs),Footnote 18 JSON,Footnote 19 and JSON-LD.Footnote 20 Therefore, the conceptual model described in this chapter does not allow us to represent all the information available in the inventory but does allow us to structure its core entities in a standardised way.
There are other initiatives which can be considered as case studies for identifying stakeholders needs. These include activities covered by Earthwatch (e.g. the MICS project, in which the impact of citizen science projects is measured) and COST Actions throughout Europe.
Participatory Toponym Handling Project
One application case where the citizen science conceptual model had a direct influence, and which in turn can be used to shape future developments of the conceptual model, concerns the collection and maintenance of place names (or toponyms) in Indonesia.
This particular case study was motivated by the fact that many national mapping agencies (and agencies responsible for the naming of places in databases and gazetteers) have scarce or insufficient resources. At the same time, many citizens have rich local and traditional knowledge of toponyms. Indonesia, in particular, has many regional and local languages and a varied topography. Including local and traditional knowledge is also relevant from a research point of view, because it can, for example, uncover yet unwritten histories.
The Geospatial Information Agency of Indonesia (Badan Informasi Geospasial, BIGFootnote 21) is responsible for toponyms in Indonesia. BIG conducted two pilot projects in 2015 (Yogyakarta) and 2016 (Lombok) on the involvement of citizens in toponym handling. The Indonesian approach includes many stakeholders, combining both top-down and bottom-up elements: national legislation provides regulations and procedures, while their implementation relies on local actors. However, local governments tasked with the implementation often lack the capacity to provide the required skills and resources.
The pilot projects led to the development of a participatory toponym handling framework (Perdana and Ostermann 2018). More importantly for this chapter, the framework adopted several concepts from an early version of Working Group 5’s citizen science conceptual model. Thus, although the framework has been subsequently improved and significantly expanded through collaborative learning, including focus group discussions with stakeholders and workshops (Perdana and Ostermann 2019), this example shows the utility of an early version of the conceptual model for designing a project involving citizens.
The concrete participatory toponym handling approach that was developed is also expected to influence ongoing legislation processes. Furthermore, it resulted in three experimental toponym collection projects in late 2018 (their outcomes will soon be published).
Using this chapter’s conceptual model, we can describe the participatory toponym handling. The main Activity is the collection of place names, either entirely new ones or updating existing ones. The Agents carrying out this activity are citizens, local government officials, experts from the national mapping agency, and academics/researchers. The DataCollectionMethod is field surveys using tablets, supplemented by office-based processing. The created Datasets are initially forms completed by participants (Observations) with multimedia elements (e.g. audio recordings of pronunciation) and ultimately enriched gazetteers. Therefore, the ParticipationTask is to provide place names and related information. The Motivation is to contribute toponymic data, preserve embedded knowledge on toponyms, and collect toponyms in their surrounding areas.