What Is Citizen Science?--A Scientometric Meta-Analysis

Abstract

Context: 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.

Objective: 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: 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.

Fig 1. Selection procedure. Exact search strings and excluded search terms are listed in S1 Appendix.

Fig 2. Growth of CS publications compared to WoS total.

N = 1935. Search was conducted 2015-12-17 using the search string in S1 Appendix.

Fig 3. Weighted annual growth of CS publications compared to WoS total.

N = 1935. Search was conducted 2015-12-17 using the search string in S1 Appendix. Index value of 1 means that the same amount of articles was produced compared to previous year. Note: the 2015 numbers are incomplete because not all records have yet been added to the database at the time of search.

Fig 4. Conceptual structure of contemporary CS.

As described by a word co-occurrence network [32] based on keywords (original author keywords, delimited by article title) occurrence network for the search conducted on 2015-12-17 resulting in 1935 hits. To be included, each keyword needed to co-occur at least three times with the same keyword in the dataset. Proximity determined by the ForceAtlas2 algorithm [33] in the software package Gephi (version 0.8.2, http://gephi.org). The larger the node, the more frequently the keyword co-occurs (higher total degree). Colors are selected with the modularity filter for “community detection” [34]. Nodes have been moved slightly to make room for the textual labels.

Fig 5. Bibliographic coupling of sources.

Generated by VOSviewer [36]. Search conducted 2015-12-17 (S1 Appendix) in the Web of Science Core Collection resulting in 1935 hits. In these 165 sources were identified in cited references (minimum 3 documents of a source). Proximity is determined by bibliographic coupling [35].

Fig 6. Occurrence of Web of Science Categories.

N = 1935, retrieved 2015-12-17. Generated by counting the categories in the WC field of the data extracted from the WoS (S1 Appendix).