Information Visualization - SAGE - Impact Factor

Information Visualization - SAGE | 2024 Impact Factor:2.0 | Cite Score:3.7 | Q3

Information Visualization Journal - SAGE

Impact Factor and Journal Rank of Information Visualization

About: Information Visualization is a peer-reviewed academic journal published by SAGE Publications. It focuses on research related to the theory, methodology, and application of information visualization. The journal provides a platform for researchers, practitioners, and educators to publish original research articles, reviews, and case studies that advance the understanding and application of visual representations of data.
Objective: The primary objective of Information Visualization is to promote research and innovation in the field of data visualization. The journal aims to explore novel methodologies, techniques, and tools for visualizing complex information to improve comprehension, insight, and decision-making. By publishing high-quality research, the journal contributes to the advancement of visualization practices and their impact on various domains such as science, business, engineering, and education.
Interdisciplinary Focus: Information Visualization adopts an interdisciplinary approach, welcoming contributions from various fields related to data visualization, including but not limited to: Computer Science Data Science Human-Computer Interaction Cognitive Science Design and Art Information Science Statistics Business Analytics Engineering Healthcare This interdisciplinary perspective fosters collaboration and innovation, leading to the development of advanced visualization techniques and solutions that address complex data representation challenges in diverse application domains.
Global Reach and Impact: With a broad international readership and authorship, Information Visualization has a global reach and impact. Its publications contribute to the dissemination of knowledge and advancements in data visualization worldwide. The journal content influences both academic research and practical applications, driving progress in areas such as data analysis, decision support, communication, and education.
High Standards and Rigorous Review: Maintaining high academic standards, Information Visualization conducts a rigorous peer-review process. Each submitted manuscript undergoes thorough evaluation by experts in the field to ensure the quality, originality, and scientific rigor of the research. This stringent review process upholds the integrity and reputation of the journal, ensuring that only high-quality and impactful research is published.
Significance: Information Visualization plays a significant role in advancing research and practice in data visualization. By providing a platform for the publication of cutting-edge research findings, the journal contributes to the growth of knowledge and innovation in visualization methodologies and applications. It serves as an essential resource for researchers, practitioners, and educators seeking to leverage visualization techniques to enhance data interpretation, communication, and decision-making across various fields.

Journal Home: Journal Homepage

Editor-in-Chief: Chaomei Chen

Scope: The journal covers a wide range of topics, including but not limited to:
Visualization Techniques: Development and evaluation of new visualization techniques and methodologies for representing complex data.
Data Representation: Innovative approaches for visualizing large-scale, multidimensional, temporal, and spatial data.
Interactive Visualization: Techniques and tools that enable interactive exploration and manipulation of visualized data.
Visual Analytics: Integration of visualization with data analysis methods to support decision-making and data understanding.
Evaluation of Visualization Techniques: Studies on the usability, effectiveness, and efficiency of different visualization methods.
Applications of Information Visualization: Case studies and applications of visualization techniques in various domains such as business, science, medicine, engineering, and social sciences.
Perception and Cognition: Research on how users perceive and interpret visual information and how it impacts their cognitive processes.
Tools and Systems: Development of software tools and systems that support information visualization.
Human-Computer Interaction: Studies on the interaction between users and visualization systems, including user interface design and user experience.
Big Data Visualization: Techniques for visualizing and making sense of large and complex data sets.