Graph Visualization Tool Research Articles

Haihun Marquis Tomb in Western Han Dynasty: Social Value and Future Prospects - A Knowledge Graph Analysis with Citespace

This paper uses the CiteSpace knowledge graph visualization tool to analyze the research evolution path and trend of 583 academic papers in the CNKI database in the past ten years. The results show that the unique position of the tomb of the Haihun Marquis in the field of history and cultural heritage of the Han Dynasty, the mainstream of research in the field of Han Dynasty culture, artistic innovation and application, the evolution of cultural heritage research, and the interdisciplinary research of the deep integration of cultural heritage research and advanced technology in the future will provide strong support for promoting the cultural and museum industry and the recreation of traditional Chinese culture.

A Quantitative Relationship Analysis of Language Patterns and Cultural Identity in Southeast Asian Chinese Literature

Abstract As an important part of overseas Chinese literature, Southeast Asian Chinese literature has entered the research field of mainland scholars since the 1980s with the deepening of economic, trade, and cultural exchanges between mainland China and Southeast Asian countries. In this paper, we use the linguistic characteristics of Southeast Asian Chinese literature as the research landing point, establish the mathematical model of regression analysis, and transform the coordinate system to simplify the derivation formula. The slope is used to determine the macro change direction of the regression curve, and the slope formula is further derived to get the expression for judging the micro change trend of the curve, which completes the construction of the mathematical model of language pattern and cultural identity law. Based on the knowledge graph visualization and analysis tool CiteSpase, the data of language patterns and cultural identity samples were processed and analyzed in terms of the number of publications, author groups, research institutions, and publishing journals. 2016 was the year with the highest number of publications, and the number of publications in this year was 55. “Malay-Chinese literature” ranked first among the high-frequency keywords, with a word frequency and centrality of 173 and 0.82, respectively. The correlation coefficient between Southeast Asian Chinese’s attitude towards Chinese language and Chinese cultural identity (Spearman’s rho=865, p<0.01) shows a positive relationship.

Analysis of the Current Situation and Trends of Medical Translation Research in China

Medical translation is an interdisciplinary research direction between medicine and translation, with both theoretical and practical value. This study is based on the CNKI core paper database, utilizing the CiteSpace knowledge graph visualization tool and Excel data analysis. A systematic literature review method is used to sort out 1764 articles in Chinese medical translation related journals from 2001 to 2022, in order to clarify the research content and characteristics of medical translation. A dynamic econometric analysis was conducted on the current status and trends of medical translation research in the past two decades, and the results showed that: 1) Chinese medical translation research has shown an overall upward trend in the past two decades. 2) The research direction of influential authors in Chinese medical translation research is mostly traditional Chinese medicine translation, with research institutions mainly being universities of traditional Chinese medicine, and research achievements in Western medicine translation account for a relatively small proportion. 3) The main focus of Chinese medical translation research is the English translation of traditional Chinese medicine (TCM) terms. From the perspective of highlighted words, corpus and medical translation talent cultivation have been cutting-edge topics in recent years, and it is predicted that they will continue to grow in popularity in the future.

GeoGraphViz: Geographically constrained 3D force‐directed graph for knowledge graph visualization

AbstractKnowledge graphs are a key technique for linking and integrating cross‐domain data, concepts, tools, and knowledge to enable data‐driven analytics. As much of the world's data have become massive in size, visualizing graph entities and their interrelationships intuitively and interactively has become a crucial task for ingesting and better utilizing graph content to support semantic reasoning, discovering hidden knowledge discovering, and better scientific understanding of geophysical and social phenomena. Despite the fact that many such phenomena (e.g., disasters) have clear spatial footprints and geographic properties, their location information is considered only as a textual label in existing graph visualization tools, limiting their capability to reveal the geospatial distribution patterns of the graph nodes. In addition, most graph visualization techniques rely on 2D graph visualization, which constrains the dimensions of information that can be presented and lacks support for graph structure examination from multiple angles. To tackle the above challenges, we developed a novel 3D map‐based graph visualization algorithm to enable interactive exploration of graph content and patterns in a spatially explicit manner. The algorithm extends a 3D force directed graph by integrating a web map, an additional geolocational force, and a force balancing variable that allows for the dynamic adjustment of the 3D graph structure and layout. This mechanism helps create a balanced graph view between the semantic forces among the graph nodes and the attractive force from a geolocation to a graph node. Our solution offers a new perspective in visualizing and understanding spatial entities and events in a knowledge graph.

A Bibliometric and Visualization Analysis of Knowledge Mapping in Digital Economy Research, 1992–2022

Digital economy is a vital driving force for countries to promote economic recovery, rebuild competitive advantages and enhance governance capacity. Extensive research has been conducted in this field. In this paper, the text analysis tool of Bicomb2.04 and the knowledge graph visualization tool of CiteSpace are applied to analyze the digital economy research from 1992 to 2022, and a total of 7874 articles retrieved from the SSCI and SCI of the WOS core database are collected as the research data. The analysis provides a comprehensive overview of the research status of the digital economy, including the distribution of literature, research institutions and regions, research funds and publications, research authors, and cooperation networks. The core progress and frontier of international research are further analyzed according to the evolution of hot keywords, core system clustering, and the hot emergent words frontier. The results show that (1) the academic circle has a good overall research trend on the digital economy, which can be divided into three steadily rising research stages. The researchers take digital innovation as the core and extend it to the application of digital innovation, which has made groundbreaking theoretical contributions, but has not yet formed a team with field influence. (2) The evolution of hot keywords can be divided into four stages. Through hot clustering analysis, a basic theoretical system is constructed with digital technology and innovation as the core and digital governance, digital application, and digital path as the means. (3) The analysis of frontier areas also identified the digital platform economy, big data technology innovation, digital economy statistics, and the gig economy as potential research directions for the future. This study provides a guide for researchers to promote further research on the digital economy and is of great significance for promoting digital development level and constructing global digital ecosystem.

Visualization Analysis of Research Hotspots and Development Trends of The Integration of Medical Care in China Based on Citespace

Objective This study analyzes, summarizes and summarizes the hot spots and trends of integrated medical and nursing care in China, and provides theoretical basis for the future related scientific research. Methods The CiteSpace Knowledge Graph visualization and analysis tool was used to conduct a basic statistical analysis of the literature on the theme of “health care integration” collected in the China Knowledge Network (CNKI) database from 2005 to 2022, to understand the annual publication volume and trends, research institutions and authors, high frequency keyword co-occurrences analysis. Results A total of 3534 articles were included. The analysis shows an explosive growth in the number of articles published each year after 2013.High-frequency keywords include medical and health care integration, elderly care services and elderly care models. Conclusion In recent years, the hot research fields of the combination of medical and nursing care in China include elderly care service, smart community home care model, and research on the elderly and disabled elderly. This paper predicts that the research field of the combination of medical and nursing care will continue to expand, and the research on the combination of medical and nursing care will develop toward the trend of diversification.

A Study on the Connotation Remodeling of Science and Technology Vocabulary Based on the Application of Knowledge Graphs

Disruptive Technology is also often translated as disruptive technology or breakthrough technology, which was first proposed by Professor Christensen of Harvard Business School in 1990s. Nowadays, the competition among countries is increasingly fierce, especially in the field of science and technology, which often leads to the backwardness and impoverishment of the whole industry due to the technological gap. Today, with the rapid consumption of social resources, social and economic development urgently needs disruptive technologies to promote industrial transformation, optimize economic structure and improve people’s quality of life. Countries that master disruptive technologies can open up new industrial development paths and lay a foundation for unique technological advantages, thus bringing huge technological dividends to national economic development. Visuwords is a knowledge graph application platform, through which the meaning and semantic association of words can be visualized. This study takes the word “famished” as an example to analyze the relationship between its new connotation and original meaning to verify its feasibility at the communication level. Today’s social science knowledge in the general public needs to be disseminated from the original relatively obscure and academic to an easily acceptable form. This study applies the idea of scientific popularization to a knowledge graph visualization tool, while using the connotation of linguistic ideas to analyze and deconstruct specific wordsThe study combines the connotation concept of linguistics with the disciplinary tools in the field of knowledge graph, and specifically analyzes the role of scientific terms, especially some abbreviations, in the mass science communication.

A methodology for structured literature network meta-analysis

PurposeLittle attention has been paid to restructuring existing massive amounts of literature data such that evidence-based meaningful inferences and networks be drawn therefrom. This paper aims to structure extant literature data into a network and demonstrate by graph visualization and manipulation tool “Gephi” how to obtain an evidence-based literature review.Design/methodology/approachThe main objective of this paper is to propose a methodology to structure existing literature data into a network. This network is examined through certain graph theory metrics to uncover evidence-based research insights arising from existing huge amounts of literature data. From the list metrics, this study considers degree centrality, closeness centrality and betweenness centrality to comprehend the information available in the literature pool.FindingsThere is a significant amount of literature on any given research problem. Approaching this massive volume of literature data to find an appropriate research problem is a complicated process. The proposed methodology and metrics enable the extraction of appropriate and relevant information from huge quantities of literature data. The methodology is validated by three different scenarios of review questions, and results are reported.Research limitations/implicationsThe proposed methodology comprises of more manual hours to structure literature data.Practical implicationsThis paper enables researchers in any domain to systematically extract and visualize meaningful and evidence-based insights from existing literature.Originality/valueThe procedure for converting literature data into a network representation is not documented in the existing literature. The paper lays down the procedure to structure literature data into a network.

A Graph Theory Based Systematic Literature Network Analysis

Reviewing the existing literature is the preliminary stage of any research work. In the recent times, researchers have enormous sources to gather literature data related to their research topics, particularly from online journals, directories, and databases. The online sources such as Scopus, Google Scholar, and Web of Science facilitate the researchers to know the updates and current state of the research domains. In traditional methods, a researcher had to collect the related research works, review them, code the information and present them in a narrative manner to specify the research gap in the existing studies. Presentation of a review of earlier studies is not a mere summary of description of earlier studies; it provides critical arguments on hypotheses to be considered and suitable methodology to investigate the topic, list of variables to be investigated, and so on. However, if one considers a huge volume of earlier studies, consolidating the information available in them is not an easy task. Critically exploring the hidden information and patterns in the existing studies, developing a visual/graphical representation of information from the data, and summarizing information through suitable metrics are gray areas in reviewing the existing studies. To overcome these issues, the study attempts to use principles from Graph Theory and proposes a new methodological approach to do the review of literature. Domains such as Sociology and Psychology have recognized the usefulness of Graph Theory, a branch of Mathematics and applied the principles to social network analysis (SNA). SNA adapts metrics such as degree centrality, closeness centrality, betweenness centrality, eigenvector centrality, cluster analysis, and modularity to identify the influential actors (nodes)/persons in the social networks. In this paper, these SNA metrics are compared with analyzing literature data to identify the influential variables in the literature, relationships among variables, and strength of relationships to develop suitable research problems, prioritizing the research problem, identification of variables for the study and to develop hypotheses. The sample literature articles are organized in a structured data and the structured data are visualized through a network graph. Furthermore, the network graph is analyzed by graph visualization and manipulation tools such as Gephi, UCINET, Graphviz, and NodeXL. Gephi 0.9 is used for network graph analysis and the graph theory metrics are investigated for the collected literature data.

Supporting Vehicle Option Change Management Through a Graph-Based Visualization Tool

When implementing configuration management methods, the amount of data required can be problematic when validating changes to the database. This is especially true for rule-based configuration management techniques. This paper presents a graph visualization tool to assist in validating changes to the rule database. The development and implementation of the tool is presented, along with the execution and results of two user studies designed to test specific aspects of the support tool. The paper then presents how the visualization tool was implemented for four ongoing configuration changes at the original equipment manufacturer (OEM) to prove the effectiveness of the tool in assisting in validating configurations changes.

VisualGraphX: interactive graph visualization within Galaxy.

We developed VisualGraphX, a web-based, interactive visualization tool for large-scale graphs. Current graph visualization tools that follow the rich-internet paradigm lack an interactive and scalable visualization of graph-based data. VisualGraphX aims to provide a universal graph visualization tool that empowers the users to efficiently explore the data for themselves at a large scale. It is available as a visualization plugin for the Galaxy platform, such that VisualGraphX can be integrated into custom analysis pipelines. VisualGraphX has been released as a visualization plugin for the Galaxy platform under AFL 3.0 and is available with instructions and application data at http://gitlab.com/comptrans/VisualGraphX/ CONTACT: bjoern.voss@ibvt.uni-stuttgart.de.

BioGranat-IG: a network analysis tool to suggest mechanisms of genetic heterogeneity from exome-sequencing data

Recent exome-sequencing studies have successfully identified disease-causing sequence variants for several rare monogenic diseases by examining variants common to a group of patients. However, the current data analysis strategies are only insufficiently able to deal with confounding factors such as genetic heterogeneity, incomplete penetrance, individuals lacking data and involvement of several genes. We introduce BioGranat-IG, an analysis strategy that incorporates the information contained in biological networks to the analysis of exome-sequencing data. To identify genes that may have a disease-causing role, we label all nodes of the network according to the individuals that are carrying a sequence variant and subsequently identify small subnetworks linked to all or most individuals. Using simulated exome-sequencing data, we demonstrate that BioGranat-IG is able to recover the genes responsible for two diseases known to be caused by variants in an underlying complex. We also examine the performance of BioGranat-IG under various conditions likely to be faced by the user, and show that its network-based approach is more powerful than a set-cover-based approach.

Interactive state-transition diagrams for visualization of multimodal annotation

Multimodal Analysis is a branch of Social Semiotics that studies how different resources, such as language, gesture, music, imagery, cinematography, etc. are used in modern media, and by humans in general, to construct and communicate meaning. Though theoretical aspects of multimodal analysis are w ell developed in the literature, and there is progress in the development of annotation software, the interpretation of annotated data still rarely uses algorithmic and data visualization approaches, limiting practical research in multimodal analysis. In the current work we propose how time stamped, tier-based multimodal annotations can be seen as finite state automatons and visualized as state-transition diagrams. We propose an algorithm converting time stamped annotation into a state-transition diagram and discuss how the resulting state-transition diagram can be visualized using freely available graph visualization tools. Then, we discuss common drawbacks of the existing tools, and propose an interactive visualization software tool allowing the analyst to synchronize the annotation state-transition diagram with the original media file. Finally, a case study on how the proposed visualization tools can assist media researchers in detecting patterns in multimodal analyses of news videos is presented.

Design and Evaluation of MagnetViz—A Graph Visualization Tool

MagnetViz was designed for the interactive manipulation of force-directed graph layouts, allowing the user to obtain visualizations based on the graph topology and/or the attributes of its nodes and edges. The user can introduce virtual magnets anywhere in the graph and these can be set to attract nodes and edges that fulfill user-defined criteria. When a magnet is placed, the force-directed nature of the layout forces it to reorganize itself in order to reflect the changes in the balance of forces, consequently changing the visualization into one that is more semantically relevant to the user. This paper describes MagnetViz’s concepts, illustrating them with examples and a case study based on a usage scenario. We also describe how the MagnetViz has evolved since its original version and present the evaluation of its latest version. This evaluation consists of two user studies aiming at assessing generated layout quality and how well the concepts can be apprehended and employed, and a task taxonomy assessment focusing on establishing which graph visualization tasks the technique is able to handle.

GeneTrailExpress: a web-based pipeline for the statistical evaluation of microarray experiments

BackgroundHigh-throughput methods that allow for measuring the expression of thousands of genes or proteins simultaneously have opened new avenues for studying biochemical processes. While the noisiness of the data necessitates an extensive pre-processing of the raw data, the high dimensionality requires effective statistical analysis methods that facilitate the identification of crucial biological features and relations. For these reasons, the evaluation and interpretation of expression data is a complex, labor-intensive multi-step process. While a variety of tools for normalizing, analysing, or visualizing expression profiles has been developed in the last years, most of these tools offer only functionality for accomplishing certain steps of the evaluation pipeline.ResultsHere, we present a web-based toolbox that provides rich functionality for all steps of the evaluation pipeline. Our tool GeneTrailExpress offers besides standard normalization procedures powerful statistical analysis methods for studying a large variety of biological categories and pathways. Furthermore, an integrated graph visualization tool, BiNA, enables the user to draw the relevant biological pathways applying cutting-edge graph-layout algorithms.ConclusionOur gene expression toolbox with its interactive visualization of the pathways and the expression values projected onto the nodes will simplify the analysis and interpretation of biochemical pathways considerably.

Ontologizer 2.0—a multifunctional tool for GO term enrichment analysis and data exploration

The Ontologizer is a Java application that can be used to perform statistical analysis for overrepresentation of Gene Ontology (GO) terms in sets of genes or proteins derived from an experiment. The Ontologizer implements the standard approach to statistical analysis based on the one-sided Fisher's exact test, the novel parent-child method, as well as topology-based algorithms. A number of multiple-testing correction procedures are provided. The Ontologizer allows users to visualize data as a graph including all significantly overrepresented GO terms and to explore the data by linking GO terms to all genes/proteins annotated to the term and by linking individual terms to child terms. The Ontologizer application is available under the terms of the GNU GPL. It can be started as a WebStart application from the project homepage, where source code is also provided: http://compbio.charite.de/ontologizer. Ontologizer requires a Java SE 5.0 compliant Java runtime engine and GraphViz for the optional graph visualization tool.

JSquid: a Java applet for graphical on-line network exploration

jSquid is a graph visualization tool for exploring graphs from protein-protein interaction or functional coupling networks. The tool was designed for the FunCoup web site, but can be used for any similar network exploring purpose. The program offers various visualization and graph manipulation techniques to increase the utility for the user. jSquid is available for direct usage and download at http://jSquid.sbc.su.se including source code under the GPLv3 license, and input examples. It requires Java version 5 or higher to run properly. erik.sonnhammer@sbc.su.se Supplementary data are available at Bioinformatics online.

DAG-based visual interfaces for navigation in indexed video content

Indexing and segmenting of video content by motion, color and texture has been intensively explored leading to a commonly used representation in a storyboard. In this paper, a novel method of visualization of video content is proposed. First of all, the content is segmented into shots, and then a spatio-temporal color signature of shots, based on color distribution in the frames, is proposed. This spatio-temporal color signature serves as a basis for graph clustering and graph visualization tools. Those, integrated in a platform for visualization of huge graphs, Tulip, supply an exciting graph-based navigation interface for multimedia content. The results obtained on feature documentaries are promising.

A multi-graph approach to complexity management in interactive graph visualization

In this paper we describe a new, multi-graph approach for development of a comprehensive set of complexity management techniques for interactive graph visualization tools. This framework facilitates efficient implementation of management of multiple associated graphs with navigation links and nesting of graphs as well as ghosting, folding and hiding of unwanted graph elements. The theoretical analyses show that the involved data structures and operations on them are quite efficient, and an implementation in a graph drawing tool has proven to be successful.

A Usability Evaluation of Concentric Rings in Relationship Graphing

A usability evaluation was conducted of a prototype radial graph visualization tool, to better understand whether concentric rings are useful for navigation and comprehension. Nodes represented sales representatives and contacts, and edges represented specific types of relationships. Double-clicking a graph node caused slow-in, slow-out, animated reorganization of the network about that node. Ten sales managers completed tasks ranging from graph comprehension to strategic analysis. Eye tracking was also utilized to address specific usability questions. Tasks were generally completed in 1-3 minutes, but assists revealed significant confusion with relationship concepts and terminology. Specific difficulties were related to filtering the graph and with occlusion of specific nodes. Eye tracking confirmed that concentric rings are used while searching nodes within the same level. Subjective assessments were quite positive. compared with presently-used enterprise sales network analysis tools.