Science Mapping and Science Maps

Abstract

Science maps are visual representations of the structure and dynamics of scholarly knowl­edge. They aim to show how fields, disciplines, journals, scientists, publications, and scientific terms relate to each other. Science mapping is the body of methods and techniques that have been developed for generating science maps. This entry is an introduction to science maps and science mapping. It focuses on the conceptual, theoretical, and methodological issues of science mapping, rather than on the mathematical formulation of science mapping techniques. After a brief history of science mapping, we describe the general procedure for building a science map, presenting the data sources and the methods to select, clean, and pre-process the data. Next, we examine in detail how the most common types of science maps, namely the citation-based and the term-based, are generated. Both are based on networks: the former on the network of publications connected by citations, the latter on the network of terms co-occurring in publications. We review the rationale behind these mapping approaches, as well as the techniques and methods to build the maps (from the extraction of the network to the visualization and enrichment of the map). We also present less-common types of science maps, including co-authorship networks, interlocking editorship networks, maps based on patents’ data, and geographic maps of science. Moreover, we consider how time can be represented in science maps to investigate the dynamics of science. We also discuss some epistemological and sociological topics that can help in the interpretation, contextualization, and assessment of science maps. Then, we present some possible applications of science maps in science policy. In the conclusion, we point out why science mapping may be interesting for all the branches of meta-science, from knowl­edge organization to epistemology.

Smart Textiles: A Review and Bibliometric Mapping

“…The final step was the interpretation of the science maps, which required close collaboration among experts in the mapped area, with the goal of not only quantitatively counterpart the qualitative knowledge of domain experts but also providing new insights and useful knowledge for research and science policy purposes, as suggested by [82,83]. The workflow of the science mapping methodology applied in this study is shown in Figure 5.…”

Breaking waves: A bibliometric odyssey on crisis communication in tourism and hospitality (1980–2022) and paving the path for future research

“…A collaboration analysis helps to understand the social ties within a field. Co‐authorship networks are the most common indicators of social structure (Peters & Van Raan, 1991) and help to investigate scientific collaborations within a field (Petrovich, 2020). RQ3 was addressed by determining THCCR's intellectual structure that identifies the ‘most influential works in the field and traces the intellectual evolution of the field by tracking changes in citation patterns over time’ (Ramos‐Rodríguez & Ruíz‐Navarro, 2004).…”

Digital humanities at global scale

“…To carry out the present analysis we have used a specific methodological framework for science mapping, based on the approach of Petrovich (2021), who recovers from Börner, Chen, and Boyack (2005) a logical sequence appropriate for our study (data collection, pre-processing, normalization, visualization, enrichment, interpretation, and reuse).…”