The authors have declared that no competing interests exist.
Conceived and designed the experiments: CK DK. Performed the experiments: CK. Analyzed the data: CK DK. Wrote the paper: CK DK.
The concept of citizen science (CS) is currently referred to by many actors inside and outside science and research. Several descriptions of this purportedly new approach of science are often heard in connection with large datasets and the possibilities of mobilizing crowds outside science to assists with observations and classifications. However, other accounts refer to CS as a way of democratizing science, aiding concerned communities in creating data to influence policy and as a way of promoting political decision processes involving environment and health.
In this study we analyse two datasets (N = 1935, N = 633) retrieved from the Web of Science (WoS) with the aim of giving a scientometric description of what the concept of CS entails. We account for its development over time, and what strands of research that has adopted CS and give an assessment of what scientific output has been achieved in CS-related projects. To attain this, scientometric methods have been combined with qualitative approaches to render more precise search terms.
Results indicate that there are three main focal points of CS. The largest is composed of research on biology, conservation and ecology, and utilizes CS mainly as a methodology of collecting and classifying data. A second strand of research has emerged through geographic information research, where citizens participate in the collection of geographic data. Thirdly, there is a line of research relating to the social sciences and epidemiology, which studies and facilitates public participation in relation to environmental issues and health. In terms of scientific output, the largest body of articles are to be found in biology and conservation research. In absolute numbers, the amount of publications generated by CS is low (N = 1935), but over the past decade a new and very productive line of CS based on digital platforms has emerged for the collection and classification of data.
During the past decade “citizen science” (CS) has engaged an increasing number of academic researchers. The lion’s share of these well-circulated accounts tell a very favourable story of the successful involvement of non-scientists in research [
However, there are numerous instances in which volunteer contributors have remained invisible. In a recent study by Cooper et al. [
Given the multiple descriptions of CS, the purpose of this article is to provide an insight into what CS is, with regards to the following questions:
How has CS and related terms developed over time?
What strands of research have adopted CS?
Which CS projects have a scientific output?
These questions will be answered with two datasets retrieved from the WoS Core Collection. One is based on a qualitative survey of relevant CS-related terminology combined with a set of recursive searches to find more and relevant search terms, and one is based on the names of individual citizen science projects, which have been retrieved from previous studies. This way, we create a dual approach for describing the phenomenon of CS. The paper then concludes with a discussion of the different strands of research that we have mapped out and a reflection upon the limitations of the scientometric method.
Perhaps the most elusive problem in describing CS originates from the multiple meanings of the concept itself. On a qualitative level this is evident by observing how two distinct meanings have developed in the natural- and social sciences respectively since the early to mid-1990s.
The most common conception of the meaning of CS, which in recent years has gained significant momentum in the natural sciences, originates in the type of research described by Bonney et al. who attest that “[i]n the past two decades, CLO’s [Cornell Laboratory of Ornithology] projects have engaged thousands of individuals in collecting and submitting data on bird observations” (p. 977). This practice, however, goes back at least to the 1960s and is sometimes even extended to include the National Audubon Society’s annual Christmas Bird Count, beginning in the year 1900, even if the name “citizen science” was not used until the 1990s [
On the other hand we find a very influential notion originating in the social sciences, as expressed in the account of Irwin’s 1995 book “
These two major understandings do not, however, exhaust all forms of CS that are of relevance for researchers interested in this phenomenon. There is also a plethora of concepts that have been coined to describe primarily local and activist-oriented forms of CS. These are more difficult to trace via scientometric methods because the results are not published in peer-reviewed literature. Instead the data from these studies are mainly used for direct interventions in policy-making and litigations. However, such interventions are often made visible by social scientists doing research on the phenomenon of CS. For example, there are cases of activist-oriented CS were data are scientifically validated and used for legal action against polluting industries [
A qualitative review of search terms for describing CS has clear limitations, the most obvious one being that false negatives will appear if a term is unknown to the researcher when constructing the search string. While false positives can be easily omitted if they are not too numerous, false negatives are much harder to detect. To minimize this problem we have conducted triple recursive searches (3RS) as documented in
Not exclusive to science. For example “crowdsourcing” and “public participation”.
Overlapping with existing search terms. For example “PPGIS” and “participatory GIS”.
Already included in the second dataset based on individual project names. For example “Ebird”.
Do not designate active participation of volunteers. For example “ranger-based monitoring” and “volunteers in research” were excluded because in the former case research is conducted by professionals and in the latter case volunteers are merely objects of study, not actively participating in scientific work.
On 2015-12-15 we performed three “snowball searches” to recursively include more search terms according to the above mentioned criteria. Thus we added “public engagement”, “participatory monitoring”, “participatory sensing”, “public participation in scientific research”, “locally based monitoring” and “volunteer based monitoring” to our original search string. This produced an additional 654 records, making the total N = 1935. As comparison, we used the same search string in the Scopus database, which returned 1954 records. Due to the complexity in comparing these two databases (search engine configuration, search algorithms, etc.) we decided to only use the WoS results in the present study.
Based on the qualitative survey combined with recursive searches, we retrieved 1935 articles from the Web of Science Core Collection using a search string composed of the terminology from the qualitative survey (
The second dataset attempts a different approach for mapping CS. By scanning a number of review articles that included lists of CS projects as part of their analysis [
The concept and practice of citizen science is barely visible in the WoS in the mid 1990s. Only at the turn of the millennium there is a slow increase. However, around 2010 there is a significant increase in published articles (
N = 1935. Search was conducted 2015-12-17 using the search string in
It is worth noting that the increasing visibility of CS since around 2010 coincides with several digital citizen science projects that use web-platforms for reaching a large crowd of contributors to scientific research, for example Galaxy Zoo, Ebird, FoldIT, Planet Hunters, Genographic Project et cetera (see RQ 3 below). The increase in publications for these projects is further described in the analysis of individual projects below. While the absolute numbers for CS-related publications are low, there is still reason to speak of an emerging trend in relative terms, as shown in
N = 1935. Search was conducted 2015-12-17 using the search string in
Article keywords, as defined by authors, were used to draw a map of what types of research that have adopted CS. One method of visualizing the possible connections between various fields of research, or within a research network, utilizes word co-occurences [
Keyword | Co-occurrence | |
---|---|---|
citizen science | monitoring | 19 |
citizen science | climate change | 17 |
citizen science | invasive species | 14 |
nanotechnology | public engagement | 14 |
biodiversity | citizen science | 13 |
crowdsourcing | citizen science | 13 |
citizen science | public participation | 11 |
citizen science | crowdsourcing | 10 |
citizen science | data quality | 10 |
citizen science | phenology | 10 |
public engagement | public understanding of science | 10 |
citizen science | community-based monitoring | 9 |
citizen science | distribution | 9 |
public engagement | science communication | 9 |
volunteered geographic information | crowdsourcing | 9 |
volunteered geographic information | openstreetmap | 9 |
birds | citizen science | 8 |
citizen science | conservation | 8 |
citizen science | public participation in scientific research | 8 |
locally-based monitoring | participatory monitoring | 8 |
neogeography | volunteered geographic information | 8 |
citizen science | survey | 7 |
conservation | citizen science | 7 |
openstreetmap | volunteered geographic information | 7 |
volunteered geographic information | data quality | 7 |
biodiversity monitoring | citizen science | 6 |
citizen science | ciencia ciudadana | 6 |
citizen science | volunteers | 6 |
climate change | citizen science | 6 |
climate change | phenology | 6 |
climate change | public engagement | 6 |
crowdsourcing | volunteered geographic information | 6 |
participatory gis | ppgis | 6 |
science communication | public engagement | 6 |
volunteer monitoring | citizen science | 6 |
(N = 1935, search conducted 2015-12-15). Counts every time a pair of keywords appear in the same article. For a visual representation, see
The keyword “citizen science” is the most common label of CS research. It overlaps frequently with the keywords “monitoring”, “climate change” and “invasive species”, which indicate a proximity with the biology strand of CS-based research. However, it also co-occurs with the notions of “public participation” and “public participation in scientific research”, concepts that belong more to a social science tradition. From geography we also find co-occurrences with keywords such as “crowdsourcing” and “openstreetmap”, which are not restricted to CS research.
To visualize the keywords in
As described by a word co-occurrence network [
The first and most frequent use of citizen science has been carried out under overlapping concepts, such as “community-based monitoring”, “volunteer monitoring” and “participatory monitoring” and is to be found in research on ecology, environmental science, geography and biodiversity conservation (
Generated by VOSviewer [
Furthermore, the fields of Volunteered Geographic Information, and Neogeography are related to each other, especially through various technologies such as “Web 2.0” and “crowdsourcing”. The notions of crowdsourcing and data quality are shared with the cluster around conservation and monitoring
Lastly, concerning the third category of social scientific research on CS, it is imperative to note that most of these studies are conducted by researchers interested in studying the phenomenon of CS, rather than using CS as a method. The central notion here is “public engagement”, which co-occurs frequently with “nanotechnology”. Social scientists are here concerned with the various aspects of participation and democratic involvement and inclusion in science and technology policy, on different aspects of the proliferation of nanotechnology. Moreover, this field also shares the use of the keywords “climate change” and “public participation”. However, what is meant by these terms is not necessarily the same things. When natural scientists use the term public participation, they usually refer to collection of data with the assistance of volunteers, whereas social scientists instead refer to representative engagement of stakeholders in policy processes. These double meanings are sometimes conflated on a policy level and attached with high expectations for the future of CS (see especially the European Commisson Green Paper on Citizen Science [
A number of keywords tie together these three categories. The notions of “crowdsourcing” and “data quality” are shared by the natural sciences and the geographic lines of research, while the notion of “public participation” and “climate change” connects the natural with the social sciences, in broad terms.
In terms of publication patterns, an analysis based on bibliographic coupling [
N = 1935, retrieved 2015-12-17. Generated by counting the categories in the WC field of the data extracted from the WoS (
To further describe CS, we conducted a search based on the names of individual CS projects.
Out of 490 projects found, only 78 had a scientific output in terms of publications (see
Name | Articles |
---|---|
North American Breeding Bird Survey | 178 |
Galaxy Zoo | 88 |
Common Birds Census | 48 |
Cooperative Observer Program | 34 |
Ebird | 32 |
Nest Record Scheme | 20 |
FoldIT | 20 |
Wetland Bird Survey | 17 |
Genographic Project | 16 |
Planet Hunters | 14 |
Globe at Night | 13 |
Chicago Wilderness | 11 |
North American Amphibian Monitoring Program | 9 |
Evolution Megalab | 7 |
Phytoplankton Monitoring Network | 6 |
NestWatch | 6 |
490 project names were searched in the WoS (For the entire search string and complete data, see
As
From the breakthrough of digitally-based CS in the mid 2000s, astronomy (Galaxy Zoo) and bioscience (Foldit) have emerged as fields of research that successfully employ the contributions of non-scientists. Citizen projects in the social sciences and the humanities are, however, absent from the results and not yet developed to a degree that matches those in biodiversity and conservation. This is also the case for medical research.
As our findings reveal, CS and adjacent notions have been used by different fields of research, even though the social sciences, medicine and the humanities are still areas in our data where CS is not utilized to any larger extent, in comparison with the natural sciences and geography. As a general observation, it is foremost in the biological sciences where CS has been adopted as a method with the purpose of collecting observations in the field. The reasons for this has been described as managing problems of time [
It is a fair speculation that the development of CS will spread to new fields of research in the future, as digital technologies will make large repositories of data possible. Although large data sets pose serious challenges for science, they also promise discoveries if and when resources for their analysis are available. Often the resources necessary include not only equipment, but also expensive human labor, especially if scientists are to be free to perform more demanding conceptual work than routine tasks. Enlisting the help of volunteers is an attractive way for science to expand the workforce needed to work with large data sets. A future challenge here will be to provide a standardized format for sharing meta-data between CS-projects, which will make both sharing of data and evaluation of data quality more accessible. Data quantity, spanning large spatial and time frames can also ensure that even messy data might be reconciled statistically
As
Finally, many CS-projects do not have scientific output as their primary goal. As
While the concept of CS has gained unprecedented presence in scientific literature during the past decade, the practice itself is much older. Previously, volunteer contributors have not been made visible in scientific articles to a wide extent. However, especially with the introduction of digital platforms, this has changed.
The main field of study employing CS is to be found in biology, ecology and conservation research. Moreover, the social sciences and geography have increasingly started to invite volunteer contributors to research.
In quantitative terms, the largest scientific output is to be found in the fields of ornithology, astronomy, meteorology and microbiology. However, most CS projects fall outside the scope of scientometric evaluation, since scientific output is not a main goal.
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Citizen science
Web of Science
Triple Recursive Search