How are they different? A quantitative domain comparison of information visualization and data visualization (2000–2014)

Kim, Meen Chul; Zhu, Yongjun; Chen, Chaomei

doi:10.1007/s11192-015-1830-0

Cited by 45 publications

(37 citation statements)

References 135 publications

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“…As Hjørland argued, domain analysis serves a fundamental role in information science because its goal is to understand the subject matter from a holistic view of sociological, cognitive, historical, and epistemological dimensions. Citing articles to Cluster #1 include some of the earliest attempts to integrate information visualization techniques to the methodology of a domain analysis (Börner et al, 2003;Boyack, Wylie, & Davidson, 2002;Chen et al, 2002) (Figure 16). Interestingly, some of these citing articles appear as cited references in Cluster #0.…”

Section: Expert Reviewmentioning

confidence: 99%

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Science Mapping: A Systematic Review of the Literature

Chen

2017

Journal of Data and Information Science

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1,212

934

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Purpose We present a systematic review of the literature concerning major aspects of science mapping to serve two primary purposes: First, to demonstrate the use of a science mapping approach to perform the review so that researchers may apply the procedure to the review of a scientific domain of their own interest, and second, to identify major areas of research activities concerning science mapping, intellectual milestones in the development of key specialties, evolutionary stages of major specialties involved, and the dynamics of transitions from one specialty to another. Design/methodology/approach We first introduce a theoretical framework of the evolution of a scientific specialty. Then we demonstrate a generic search strategy that can be used to construct a representative dataset of bibliographic records of a domain of research. Next, progressively synthesized co-citation networks are constructed and visualized to aid visual analytic studies of the domain’s structural and dynamic patterns and trends. Finally, trajectories of citations made by particular types of authors and articles are presented to illustrate the predictive potential of the analytic approach. Findings The evolution of the science mapping research involves the development of a number of interrelated specialties. Four major specialties are discussed in detail in terms of four evolutionary stages: conceptualization, tool construction, application, and codification. Underlying connections between major specialties are also explored. The predictive analysis demonstrates citations trajectories of potentially transformative contributions. Research limitations The systematic review is primarily guided by citation patterns in the dataset retrieved from the literature. The scope of the data is limited by the source of the retrieval, i.e. the Web of Science, and the composite query used. An iterative query refinement is possible if one would like to improve the data quality, although the current approach serves our purpose adequately. More in-depth analyses of each specialty would be more revealing by incorporating additional methods such as citation context analysis and studies of other aspects of scholarly publications. Practical implications The underlying analytic process of science mapping serves many practical needs, notably bibliometric mapping, knowledge domain visualization, and visualization of scientific literature. In order to master such a complex process of science mapping, researchers often need to develop a diverse set of skills and knowledge that may span multiple disciplines. The approach demonstrated in this article provides a generic method for conducting a systematic review. Originality/value Incorporating the evolutionary stages of a specialty into the visual analytic study of a research domain is innovative. It provides a systematic methodology for researchers to achieve a good understanding of how scientific fields evolve, to recognize potentially insightful patterns from visually encoded signs, and to synthesize various information so as to capture the state of the art of the domain.

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Section: Expert Reviewmentioning

confidence: 99%

“…The most active areas of scientific inquiries are also where the level of uncertainty is the highest (Chen, 2016;Fuchs, 1993). The evidence revealed in our study suggests that science mapping is a Stage III specialty.…”

Section: Expert Reviewmentioning

confidence: 99%

Science Mapping: A Systematic Review of the Literature

Chen

2017

Journal of Data and Information Science

Self Cite

1,212

934

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“…According to Kim et al, a highly cited article has an impact on the community; however, the influence or density of this impact cannot be identified during a specific timespan if the only measure of citations accumulation is considered. To address this issue, we have also analyzed the burstness of citations to understand the advent and decline of research trends in the domain.…”

Section: Resultsmentioning

confidence: 99%

Emerging topics in Internet technology: A complex networks approach

Khan

Niazi

2018

Internet Technology Letters

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Communication networks, in general, and Internet technology, in particular, are fast‐evolving areas of research. The literature in these domains is expanding at such a fast scale that it is very difficult to understand the underlying dynamics and emerging trends. While several citation databases are gradually indexing a large set of reliable content, currently the Web of Science represents one of the most highly valued databases. In this paper, we present a complex network‐based analytical approach to analyze recent data from the Web of Science in communication networks. Taking bibliographic records from the recent period of 2014 to 2017, we model and analyze complex scientometric networks. Using bibliometric coupling applied over complex citation data we present answers to cocitation patterns of documents, cooccurrence patterns of terms, as well as the most influential articles, among others, we also present key pivot points and intellectual turning points. Complex network analysis of the data demonstrates a considerably high level of interest in two key clusters labeled descriptively as “social networks” and “computer networks.” In addition, key themes in highly cited literature were clearly identified as “communication networks,” “social networks,” and “complex networks.”

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“…Word analysis is a broad topic, ranging from co‐citation analysis, word frequency analysis to topic analysis, but has not frequently been applied to the visualisation field. Where there is prior work it has focused on domain analysis (e.g., [JZ16, KZC16]). The closest studies to our work are on the notion of “overview” [HH11], Isenberg et al [IIS∗17] on visualisation paper keywords, and Liu et al [LGF∗14] on co‐word analysis of the human‐computer interaction literature.…”

Section: Related Workmentioning

confidence: 99%

Multiple Views: different meanings and collocated words

Roberts

Al-Maneea

Butcher

et al. 2019

Computer Graphics Forum

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We report on an in‐depth corpus linguistic study on ‘multiple views’ terminology and word collocation. We take a broad interpretation of these terms, and explore the meaning and diversity of their use in visualisation literature. First we explore senses of the term ‘multiple views’ (e.g., ‘multiple views’ can mean juxtaposition, many viewport projections or several alternative opinions). Second, we investigate term popularity and frequency of occurrences, investigating usage of ‘multiple’ and ‘view’ (e.g., multiple views, multiple visualisations, multiple sets). Third, we investigate word collocations and terms that have a similar sense (e.g., multiple views, side‐by‐side, small multiples). We built and used several corpora, including a 6‐million‐word corpus of all IEEE Visualisation conference articles published in IEEE Transactions on Visualisation and Computer Graphics 2012 to 2017. We draw on our substantial experience from early work in coordinated and multiple views, and with collocation analysis develop several lists of terms. This research provides insight into term use, a reference for novice and expert authors in visualisation, and contributes a taxonomy of ‘multiple view’ terms.

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How are they different? A quantitative domain comparison of information visualization and data visualization (2000–2014)

Cited by 45 publications

References 135 publications

Science Mapping: A Systematic Review of the Literature

Science Mapping: A Systematic Review of the Literature

Emerging topics in Internet technology: A complex networks approach

Multiple Views: different meanings and collocated words

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