InfoVis experience enhancement through mediated interaction

Information visualization is an experience in which both the aesthetic representations and interaction are part. Such an experience can be augmented through close consideration of its major components. Interaction is crucial to the experience, yet it has seldom been adequately explored in the field. We claim that direct mediated interaction can augment such an experience. This paper discusses the reasons behind such a claim and proposes a mediated interactive manipulation scheme based on the notion of directness. It also describes the ways in which such a claim will be validated. The Literature Knowledge Domain (LKD) is used as the concrete domain around which the discussions will be held

Obvious: a meta-toolkit to encapsulate information visualization toolkits. One toolkit to bind them all

This article describes “Obvious”: a meta-toolkit that abstracts and encapsulates information visualization toolkits implemented in the Java language. It intends to unify their use and postpone the choice of which concrete toolkit(s) to use later-on in the development of visual analytics applications. We also report on the lessons we have learned when wrapping popular toolkits with Obvious, namely Prefuse, the InfoVis Toolkit, partly Improvise, JUNG and other data management libraries. We show several examples on the uses of Obvious, how the different toolkits can be combined, for instance sharing their data models. We also show how Weka and RapidMiner, two popular machine-learning toolkits, have been wrapped with Obvious and can be used directly with all the other wrapped toolkits. We expect Obvious to start a co-evolution process: Obvious is meant to evolve when more components of Information Visualization systems will become consensual. It is also designed to help information visualization systems adhere to the best practices to provide a higher level of interoperability and leverage the domain of visual analytics

NodeTrix: Hybrid Representation for Analyzing Social Networks

The need to visualize large social networks is growing as hardware capabilities make analyzing large networks feasible and many new data sets become available. Unfortunately, the visualizations in existing systems do not satisfactorily answer the basic dilemma of being readable both for the global structure of the network and also for detailed analysis of local communities. To address this problem, we present NodeTrix, a hybrid representation for networks that combines the advantages of two traditional representations: node-link diagrams are used to show the global structure of a network, while arbitrary portions of the network can be shown as adjacency matrices to better support the analysis of communities. A key contribution is a set of interaction techniques. These allow analysts to create a NodeTrix visualization by dragging selections from either a node-link or a matrix, flexibly manipulate the NodeTrix representation to explore the dataset, and create meaningful summary visualizations of their findings. Finally, we present a case study applying NodeTrix to the analysis of the InfoVis 2004 coauthorship dataset to illustrate the capabilities of NodeTrix as both an exploration tool and an effective means of communicating results

Visualisation techniques for users and designers of layout algorithms

Visualisation systems consisting of a set of components through which data and interaction commands flow have been explored by a number of researchers. Such hybrid and multistage algorithms can be used to reduce overall computation time, and to provide views of the data that show intermediate results and the outputs of complementary algorithms. In this paper we present work on expanding the range and variety of such components, with two new techniques for analysing and controlling the performance of visualisation processes. While the techniques presented are quite different, they are unified within HIVE: a visualisation system based upon a data-flow model and visual programming. Embodied within this system is a framework for weaving together our visualisation components to better afford insight into data and also deepen understanding of the process of the data's visualisation. We describe the new components and offer short case studies of their application. We demonstrate that both analysts and visualisation designers can benefit from a rich set of components and integrated tools for profiling performance

Conceptual design framework for information visualization to support multidimensional datasets in higher education institutions

Information Visualization (InfoVis) enjoys diverse adoption and applicability because of its strength in solving the problem of information overload inherent in institutional data. Policy and decision makers of higher education institutions (HEIs) are also experiencing information overload while interacting with students‟ data, because of its multidimensionality. This constraints decision making processes, and therefore requires a domain-specific InfoVis conceptual design framework which will birth the domain‟s InfoVis tool. This study therefore aims to design HEI Students‟ data-focused InfoVis (HSDI) conceptual design framework which addresses the content delivery techniques and the systematic processes in actualizing the domain specific InfoVis. The study involved four phases: 1) a users‟ study to investigate, elicit and prioritize the students‟ data-related explicit knowledge preferences of HEI domain policy. The corresponding students‟ data dimensions are then categorised, 2) exploratory study through content analysis of InfoVis design literatures, and subsequent mapping with findings from the users‟ study, to propose the appropriate visualization, interaction and distortion techniques for delivering the domain‟s explicit knowledge preferences, 3) conceptual development of the design framework which integrates the techniques‟ model with its design process–as identified from adaptation of software engineering and InfoVis design models, 4) evaluation of the proposed framework through expert review, prototyping, heuristics evaluation, and users‟ experience evaluation. For an InfoVis that will appropriately present and represent the domain explicit knowledge preferences, support the students‟ data multidimensionality and the decision making processes, the study found that: 1) mouse-on, mouse-on-click, mouse on-drag, drop down menu, push button, check boxes, and dynamics cursor hinting are the appropriate interaction techniques, 2) zooming, overview with details, scrolling, and exploration are the appropriate distortion techniques, and 3) line chart, scatter plot, map view, bar chart and pie chart are the appropriate visualization techniques. The theoretical support to the proposed framework suggests that dictates of preattentive processing theory, cognitive-fit theory, and normative and descriptive theories must be followed for InfoVis to aid perception, cognition and decision making respectively. This study contributes to the area of InfoVis, data-driven decision making process, and HEI students‟ data usage process

Information visualization approach in marine fisheries landing data

This paper studied the landings statistical data in marine fisheries by the state of Terengganu for the period of time 2000 until 2009 and to discuss some of the main features on how information visualization technique can be used as a keystone technology for represent these fisheries data. Information visualization (InfoVis) represents an abstract data in graphical representation concepts in such a way that is more natural or easier for human to comprehend. InfoVis is recognized as one of the important way to help users to study, explore, and present information in fisheries data. Today, this emerging technology is important in fisheries and plays a vital role in developing integrated approaches to fishery management and assessment. It helps to convey relatively complex technical information to scientists, managers and decision makers. Since visualization technology provide a high degree of functionality in sampling design, data assimilation, exploratory data analysis and model development, they will continue to play an increasing significant strategic role in fishery management and assessment

On Regulatory and Organizational Constraints in Visualization Design and Evaluation

Problem-based visualization research provides explicit guidance toward identifying and designing for the needs of users, but absent is more concrete guidance toward factors external to a user's needs that also have implications for visualization design and evaluation. This lack of more explicit guidance can leave visualization researchers and practitioners vulnerable to unforeseen constraints beyond the user's needs that can affect the validity of evaluations, or even lead to the premature termination of a project. Here we explore two types of external constraints in depth, regulatory and organizational constraints, and describe how these constraints impact visualization design and evaluation. By borrowing from techniques in software development, project management, and visualization research we recommend strategies for identifying, mitigating, and evaluating these external constraints through a design study methodology. Finally, we present an application of those recommendations in a healthcare case study. We argue that by explicitly incorporating external constraints into visualization design and evaluation, researchers and practitioners can improve the utility and validity of their visualization solution and improve the likelihood of successful collaborations with industries where external constraints are more present.Comment: 9 pages, 2 figures, presented at BELIV workshop associated with IEEE VIS 201