Top 10 unsolved information visualization problems

IEEE Computer Graphics and Applications, 25 (4). 12-16. Retrieved 6/21/2006 from http://www.pages.drexel.edu/~cc345/papers/cga2005.pdf.Athought-provoking panel, organized by Theresa- Marie Rhyne, at IEEE Visualization 2004 addressed the top unsolved problems of visualization.1 Two of the invited panelists, Bill Hibbard and Chris Johnson, addressed scientific visualization problems. Steve Eick and I identified information visualization problems. The following top 10 unsolved problems list is a revised and extended version of the information visualization problems I outlined on the panel. These problems are not necessarily imposed by technical barriers; rather, they are problems that might hinder the growth of information visualization as a field. The first three problems highlight issues from a user-centered perspective. The fifth, sixth, and seventh problems are technical challenges in nature. The last three are the ones that need tackling at the disciplinary level

Beyond Usability: An Alternative Usability Evaluation Method, PUT-Q2

Usability can be thought of as a measure or degree to which a system satisfies the needs of the human. Usability is a quality inherent to any given system, which assists in determining the efficiency, effectiveness and satisfaction levels of those involved in the interaction. Everyday we are bombarded with interactions and experiences that shape our thoughts, values, and judgments as well as test our limits of interaction with technology. These interactions have progressed at such an intense pace that humans have become practically slaves to technological innovation. Humans are forced to conform with needs of technology, rather then technology conforming to human needs. This fact must be rectified and becomes the primary focus of this thesis. Current models in usability evaluation methods (UEMs) analyze the quantitative data collected during testing. These statistical studies provide insight into limited aspects of usability, and most overlook human dimensions, including perception and affective responses; thus leaving a glaring pitfall in the overall analysis of system usability. By analyzing a new qualitative channel of data, this research attempts to explain these human-dimensional factors. Up to this point no evaluation model has been largely accepted which attempts to fuse both qualitative and quantitative data. This research proposes an alternative UEM, incorporating both qualitative and quantitative data, called the Perception and Usability Testing combining Qualitative and Quantitative data, or PUT-Q2. This new usability evaluation method presents complex qualitative and quantitative data in graphical visualizations and matrices that assist the usability expert in uncovering additional correlations and usability issues with their system

Co-Authorship of scientists in the energy field: a study of the ETDE World Energy Database (ETDEWEB) using social network analysis

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Gestão de InformaçãoThis thesis presents a study, using a social network analysis (SNA) approach, to examine the structure of co-authorship collaboration within the research community in Portugal in the energy field, for the period from 1995 to 2010. The domain of the study is Portuguese scientists, working either in Portugal or abroad; foreign scientists working in Portugal and scientists who have co-authored with either of these groups. The study uses the most common measures of macro (whole network) and micro (actorcentred) structures of this collaboration

Towards A Novel Unified Framework for Developing Formal, Network and Validated Agent-Based Simulation Models of Complex Adaptive Systems

Literature on the modeling and simulation of complex adaptive systems (cas) has primarily advanced vertically in different scientific domains with scientists developing a variety of domain-specific approaches and applications. However, while cas researchers are inherently interested in an interdisciplinary comparison of models, to the best of our knowledge, there is currently no single unified framework for facilitating the development, comparison, communication and validation of models across different scientific domains. In this thesis, we propose first steps towards such a unified framework using a combination of agent-based and complex network-based modeling approaches and guidelines formulated in the form of a set of four levels of usage, which allow multidisciplinary researchers to adopt a suitable framework level on the basis of available data types, their research study objectives and expected outcomes, thus allowing them to better plan and conduct their respective research case studies. Firstly, the complex network modeling level of the proposed framework entails the development of appropriate complex network models for the case where interaction data of cas components is available, with the aim of detecting emergent patterns in the cas under study. The exploratory agent-based modeling level of the proposed framework allows for the development of proof-of-concept models for the cas system, primarily for purposes of exploring feasibility of further research. Descriptive agent-based modeling level of the proposed framework allows for the use of a formal step-by-step approach for developing agent-based models coupled with a quantitative complex network and pseudocode-based specification of the model, which will, in turn, facilitate interdisciplinary cas model comparison and knowledge transfer. Finally, the validated agent-based modeling level of the proposed framework is concerned with the building of in-simulation verification and validation of agent-based models using a proposed Virtual Overlay Multiagent System approach for use in a systematic team-oriented approach to developing models. The proposed framework is evaluated and validated using seven detailed case study examples selected from various scientific domains including ecology, social sciences and a range of complex adaptive communication networks. The successful case studies demonstrate the potential of the framework in appealing to multidisciplinary researchers as a methodological approach to the modeling and simulation of cas by facilitating effective communication and knowledge transfer across scientific disciplines without the requirement of extensive learning curves

How information visualization systems change users’ understandings of complex data

User-centered evaluations of information systems often focus on the usability of the system rather its usefulness. This study examined how a using an interactive knowledge-domain visualization (KDV) system affected users’ understanding of a domain. Interactive KDVs allow users to create graphical representations of domains that depict important papers, authors, or terms. Interactive KDVs have several potential advantages over other presentation methods, such as making connections explicit, and the ability for users to see the overall structure of the domain.The project examined CiteSpace, an interactive KDV that uses article cocitation analysis and text analysis to create visualizations of important papers and terms in a domain. In this study, participants completed several tasks related to the field of artificial intelligence. Depending on the experimental condition, participants read a review article about the domain, interacted with a CiteSpace visualization containing equivalent information, or both. Participants who neither read the article nor used the KDV system served as a baseline. The participants completed three tasks in which they sorted papers and terms according to their importance and relatedness. The hypotheses predicted that participants who used the KDV, especially in conjunction with the review article, would show a more expert-like understanding of the domain compared to the baseline and to participants who used only the article.The study measured the quality of participants’ understanding by comparing their card sorting responses to benchmark responses obtained from domain experts. Participants who produced judgments of importance and relatedness that were similar to the benchmarks were considered as demonstrating a good understanding of the domain. The card sorting results were analyzed using several statistical techniques, including multidimensional scaling and cluster analysis.The results showed that while participants’ understanding of the domain was influenced by using the KDV, this influence was not in the direction of the benchmarks. The data suggest that a lack of agreement between the benchmarks and the depiction of the field presented in the KDV may have led to these findings. The study discusses several possible reasons for these results and recommends possible changes to KDVs that may increase their usefulness.Ph.D., Information Studies -- Drexel University, 200

A model for representing the motivational and cultural factors that influence mobile phone usage variety

Mobile phone usage involves the mobile phone, the telecommunications system, mobile phone users, and the adoption and use of the system. Mobile communications is a complex and rapidly changing industry consisting of the hardware, software, network and business aspects. Mobile phone users are influenced by demographic, social, cultural and contextual factors that complicate the understanding of mobile phone usage. Advances in technology and market competition drive the addition of new services and features. In contrast, human cognition and attention are more constrained and many users find it difficult to cope with the cognitive demands of mobile phone technology. The aim of this study is to develop a model for representing the influence of motivational needs and cultural factors on mobile phone usage variety. The link between motivational needs and mobile phone usage variety, the cultural factors that influence mobile phone usage variety, as well as usage spaces as an approach to representing usage variety, are researched. The research encompasses a literature study, structured interviews, a pilot study and a survey. The pilot study and survey yielded data about mobile phone usage of university students under the age of 30 in South Africa. The results from the statistical analysis were triangulated with the findings of the literature study and the observations made about mobile phone usage during this two-year period. A final survey was conducted to verify the model. The contribution of this study is a mobile phone technology usage model (MOPTUM) for representing the motivational and cultural factors that influence mobile phone usage variety in such a way that users can use the model to express their mobile phone usage needs in non-technical terms while marketers and designers can use the model to convert the expressed user needs into the features required. MOPTUM draws on concepts and models from sociology, computer-supported cooperative work, human-computer interaction and technology adoption models from the field of marketing. MOPTUM verifies some existing findings on mobile phone usage and then integrates and extends these existing models to provide a new model for understanding the motivational and cultural factors that influence mobile phone usage variety.ComputingPh. D. (Computer Science