1 Challenges in Human‐Centered Information Visualization: Introduction to the Special Issue Xia Lin, Andreas Kerren, and Jiajie Zhang Guest Editors Human-centered computing has been described as “an emerging field that aims at bridging the existing gaps between the various disciplines involved with the design and implementation of computing systems that support people’s activities” 1 . Information visualization is certainly one of the disciplines in the center of human-centered computing 2 . Or is it? Since we announced the Call for Paper for a special issue on human-centered information visualization, our authors and reviewers have been debating what should be called “Human-Centered Information Visualization” (HCIV). On one extreme, we might claim that all the research on information visualization is “human-centered” since the ultimate goal of information visualization is to let people understand and use the information presented visually. On the other extreme, we might regard the lack of “human-centered” approach as the major issue of current research in information visualization. In this special issue, through a set of excellent research papers selected by the reviewers, we seek to present the perspectives of information visualization researchers (the authors) on the issue of “human-centered” and hope to encourage more conversations on the advancement of information visualization toward “human-centered”. In the first paper, Measuring Effectiveness of Graph Visualizations: A Cognitive Load Perspective, Authors Huang et al. questioned the relationship between information visualization and human cognitive loads. They developed an interesting model to measure cognitive loads of graph visualizations and predict the regions of cognitive loads where visualization would be most effective. Their empirical results show promise of the model in revealing the relationship between visual understanding and domain complexity, data complexity, task complexity, and visual complexity. In the second paper, What does the User Want to See? What does the Data Want to Be?, authors Pretorius and van Wijk argued that information visualization needs to be designed from two perspectives: the user’s perspective and the data perspective. It is emphasized that the two perspectives are inter-related and reinforced mutually. They presented several case studies to demonstrate that it is important to consider not only user requirements but also the data to be visualized. In particular, switching from one perspective to another during the iterative design process would significantly benefit the design and the outcome. Their case studies provide some good lessons about building useful information visualization systems. The third paper is about visual information filtering in the searching environment. Titled “Adaptive Visualization of Search Results: Bring User Models to Visual Analytics,” the paper by Ahn and Brusilovsky introduces a framework that incorporates user modeling and information visualization to provide flexible and user-centered visual information filtering. In their system, retrieved documents are displayed at locations relatively to the point of interest (POI), which can be either user’s query terms or terms generated through user modeling. The user can select to enact or disable a POI to filter through the retrieved documents. In their experimental testing, they specifically tested the user model effect on three © Palgrave Macmillan, 2009. This is a post-peer-review, pre-copyedit version of an article published in Information Visualization. The definitive publisher-authenticated version [Xia Lin, Andreas Kerren, and Jiaje Zhang. Challenges in Human-Centered Information Visualization: Introduction to the Special Issue. In Information Visualization, 8(3):137-138, 2009. Palgrave Macmillan Ltd.] is available online at: http://dx.doi.org/10.1057/ivs.2009.17