OLGAVis: On-Line Graph Analysis and Visualization for Bibliographic Information Network
Source abstract
Abstract
Real-world systems that are composed of various types of components, their interactions, and relationships, and numerous applications are often modeled as graphs or network structures to represent and analyze the presence of relationship, shape, and meaning of objects. Network-structured data are used for various exploration and in-depth analysis through visualization of information in various fields. In particular, online bibliographic databases are a service that is used for a myriad of purposes, such as simple search of research materials as well as understanding the history and flow of research, current status, and trends. A visualization tool that can intuitively perform exploration and analysis by modeling the data provided by the online bibliographic database in a network structure will be a very meaningful study for the exploration of various information using a large amount of complex bibliographic data. This study has modeled an online bibliographic database as an information network, and further developed a prototype of a visualization tool that provides an interactive interface for easily and efficiently performing visual exploration and multidimensional analysis. The visualization tool that was developed through this study will be used to conveniently perform various online analysis of the bibliographic data, and the information and knowledge acquired as a result of the analysis are expected to contribute to the research development of various researchers. Furthermore, this visualization tool can be applied to other types of data in the future, and it is expected to develop into a useful tool for various information network analysis by improving, supplementing, and expanding the functions and performance of the developed prototype.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Complex Network Analysis Techniques · Data Visualization and Analytics · Web Data Mining and Analysis
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Computer Science and Engineering, Kangwon National University, Chuncheon-si 24341, Korea
Bionsight Inc., Chuncheon-si 24341, Korea
School of Computer Science, Semyung University, Jecheon-si 27136, Korea
References (44)
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