Showing papers in "Information Visualization in 2008"
TL;DR: The possibilities to collect and store data increase at a faster rate than the ability to use it for making decisions, and in most applications, raw data has no value in itself; instead the authors want to extract the information contained in it.
Abstract: We are living in a world which faces a rapidly increasing amount of data to be dealt with on a daily basis. In the last decade, the steady improvement of data storage devices and means to create and collect data along the way influenced our way of dealing with information: Most of the time, data is stored without filtering and refinement for later use. Virtually every branch of industry or business, and any political or personal activity nowadays generate vast amounts of data. Making matters worse, the possibilities to collect and store data increase at a faster rate than our ability to use it for making decisions. However, in most applications, raw data has no value in itself; instead we want to extract the information contained in it.
1,047 citations
TL;DR: Jigsaw is a visual analytic system that represents documents and their entities visually in order to help analysts examine them more efficiently and develop theories about potential actions more quickly.
Abstract: Investigative analysts who work with collections of text documents connect embedded threads of evidence in order to formulate hypotheses about plans and activities of potential interest. As the number of documents and the corresponding number of concepts and entities within the documents grow larger, sense-making processes become more and more difficult for the analysts. We have developed a visual analytic system called Jigsaw that represents documents and their entities visually in order to help analysts examine them more efficiently and develop theories about potential actions more quickly. Jigsaw provides multiple coordinated views of document entities with a special emphasis on visually illustrating connections between entities across the different documents.
377 citations
TL;DR: The purpose of this chapter is to increase awareness of empirical research in general, of its relationship to information visualization in particular, and to emphasize its importance to encourage thoughtful application of a greater variety of evaluative research methodologies in information visualization.
Abstract: Information visualization research is becoming more established, and as a result, it is becoming increasingly important that research in this field is validated. With the general increase in information visualization research there has also been an increase, albeit disproportionately small, in the amount of empirical work directly focused on information visualization. The purpose of this chapter is to increase awareness of empirical research in general, of its relationship to information visualization in particular; to emphasize its importance; and to encourage thoughtful application of a greater variety of evaluative research methodologies in information visualization.
368 citations
TL;DR: This paper proposes a comprehensive classification and review of movement patterns and argues that this is indispensable as a basis for the development of pattern recognition and information visualization algorithms that are required to be efficient, effective, and as generic as possible.
Abstract: Areview of research that has been carried out on data mining and visual analysis of movement patterns suggests that there is little agreement on the relevant types of movement patterns and only few, isolated definitions of these exist. Since the research interest in this area has recently started to soar. we believe that this is a good time to approach the definition of movement patterns in a more systematic and comprehensive way. This paper intends to contribute to the development of a toolbox of data mining algorithms and visual analytic techniques for movement analysis by developing firstly a conceptual framework for movement behavior of different moving objects and secondly a comprehensive classification and review of movement patterns. We argue that this is indispensable as a basis for the development of pattern recognition and information visualization algorithms that are required to be efficient (i.e. usable on massive data sets), effective (i.e. capable of accurately detecting patterns not artifacts), and as generic as possible (i.e. potentially applicable to different types of movement data). We demonstrate the utilization of our classification by answering the question as to what extent eye tracking data can be seen as a proxy of other types of movement data. We have set up a moderated discussion platform in order to facilitate the further evolution of our proposed classification towards a consolidated taxonomy in a consensus process.
351 citations
TL;DR: This paper considers information visualization from different points of view, and gathers arguments to explain the value of the field.
Abstract: Researchers and users of Information Visualization are convinced that it has value. This value can easily be communicated to others in a face-to-face setting, such that this value is experienced in practice. To convince broader audiences, and also, to understand the intrinsic qualities of visualization is more difficult, however. In this paper we consider information visualization from different points of view, and gather arguments to explain the value of our field.
248 citations
TL;DR: The paper investigates the possibilities of using clustering techniques in visual exploration and analysis of large numbers of trajectories, that is, sequences of time-stamped locations of some moving entities, and suggests the procedure of progressive clustering where a simple distance function with a clear meaning is applied on each step which leads to easily interpretable outcomes.
Abstract: The paper investigates the possibilities of using clustering techniques in visual exploration and analysis of large numbers of trajectories, that is, sequences of time-stamped locations of some moving entities. Trajectories are complex spatio-temporal constructs characterized by diverse non-trivial properties. To assess the degree of (dis)similarity between traiectories, specific methods (distance functions) are required. A single distance function accounting for all properties of trajectories, (1) is difficult to build, (2) would require much time to compute, and (3) might be difficult to understand and to use. We suggest the procedure of progressive clustering where a simple distance function with a clear meaning is applied on each step, which leads to easily interpretable outcomes. Successive application of several different functions enables sophisticated analyses through gradual refinement of earlier obtained results. Besides the advantages from the sense-making perspective, progressive clustering enables a rational work organization where time-consuming computations are applied to relatively small potentially interesting subsets obtained by means of 'cheap' distance functions producing quick results. We introduce the concept of progressive clustering by an example of analyzing a large real data set. We also review the existing clustering methods, describe the method OPTICS suitable for progressive clustering of trajectories, and briefly present several distance functions for trajectories.
208 citations
TL;DR: Theoretical and methodological approaches for exploring and analyzing large datasets with spatial and temporal components were presented, discussed and developed at the meeting in Girona, Catalunya which was held on 5 May 2008 one day before AGILE's 11th International Conference on Geographic Information Science.
Abstract: The work presented here represents a selection of the contributions made to a workshop coordinated by the International Cartographic Association (ICA) Commission on Geovisualization and the Association of Geographic Information Laboratories in Europe (AGILE) on the Geovisualization of Dynamics, Movement and Change. Theoretical and methodological approaches for exploring and analyzing large datasets with spatial and temporal components were presented, discussed and developed at the meeting in Girona, Catalunya which was held on 5 May 2008 one day before AGILE’s 11th International Conference on Geographic Information Science.
166 citations
TL;DR: The goal of this chapter is to help authors recognize and avoid a set of pitfalls that recur in many rejected information visualization papers, using a chronological model of the research process.
Abstract: The goal of this chapter is to help authors recognize and avoid a set of pitfalls that recur in many rejected information visualization papers, using a chronological model of the research process. Selecting a target paper type in the initial stage can avert an inappropriate choice of validation methods. Pitfalls involving the design of a visual encoding may occur during the middle stages of a project. In a later stage when the bulk of the research is finished and the paper writeup begins, the possible pitfalls are strategic choices for the content and structure of the paper as a whole, tactical problems localized to specific sections, and unconvincing ways to present the results. Final-stage pitfalls of writing style can be checked after a full paper draft exists, and the last set of problems pertain to submission.
121 citations
TL;DR: The adoption of information visualization technologies by lay users --- as opposed to the traditional information visualization audience of scientists and analysts --- has important implications for visualization research, design and development.
Abstract: In recent years we have seen information visualization technology move from an advanced research topic to mainstream adoption in both commercial and personal use. This move is in part due to many businesses recognizing the need for more effective tools for extracting knowledge from the data warehouses they are gathering. Increased mainstream interest is also a result of more exposure to advanced interfaces in contemporary online media. The adoption of information visualization technologies by lay users --- as opposed to the traditional information visualization audience of scientists and analysts --- has important implications for visualization research, design and development. Since we cannot expect each of these lay users to design their own visualizations, we have to provide them tools that make it easy to create and deploy visualizations of their datasets.
110 citations
TL;DR: Drawing on theories within associated disciplines, three different approaches to theoretical foundations of Information Visualization are presented: data-centric predictive theory, information theory, and scientific modeling.
Abstract: The field of Information Visualization, being related to many other diverse disciplines (for example, engineering, graphics, statistical modeling) suffers from not being based on a clear underlying theory. The absence of a framework for Information Visualization makes the significance of achievements in this area difficult to describe, validate and defend. Drawing on theories within associated disciplines, three different approaches to theoretical foundations of Information Visualization are presented here: data-centric predictive theory, information theory, and scientific modeling. Definitions from linguistic theory are used to provide an over-arching framework for these three approaches.
104 citations
TL;DR: The fundamental tenet for this approach is that activity drives movement, and logically it is the key to comprehending pattern, which is illustrated with specific example visualizations and invites critiques of the progress to date.
Abstract: The timeline or track of any individual, mobile, sentient organism, whether animal or human being, represents a fundamental building block in understanding the interactions of such entities with their environment and with each other. New technologies have emerged to capture the (x, y, t) dimension of such timelines in large volumes and at relatively low cost, with various degrees of precision and with different sampling properties. This has proved a catalyst to research on data mining and visualizing such movement fields. However, a good proportion of this research can only infer, implicitly or explicitly, the activity of the individual at any point in time. This paper in contrast focuses on a data set in which activity is known. It uses this to explore ways to visualize large movement fields of individuals, using activity as the prime referential dimension for investigating space-time patterns. Visually central to the paper is the ringmap, a representation of cyclic time and activity, that is itself quasi spatial and is directly linked to a variety of visualizations of other dimensions and representations of spatio-temporal activity. Conceptuatly central is the ability to explore different levels of generalization in each of the space, time and activity dimensions, and to do this in any combination of the (s, t, a) phenomena. The fundamental tenet for this approach is that activity drives movement, and logically it is the key to comprehending pattern. The paper discusses these issues, illustrates the approach with specific example visualizations and invites critiques of the progress to date.
TL;DR: Visualizations leverage the human visual system to support the process of sensemaking, in which information is collected, organized, and analyzed to generate knowledge and inform action.
Abstract: Visualizations leverage the human visual system to support the process of sensemaking, in which information is collected, organized, and analyzed to generate knowledge and inform action. Although m...
TL;DR: Enhanced treemaps that incorporate spatial and temporal ordering for exploring a large multivariate spatio-temporal data set and appear to have potential as interactive interfaces for variable selection in spatio -temporal visualisation.
Abstract: We demonstrate and reflect upon the use of enhanced treemaps that incorporate spatial and temporal ordering for exploring a large multivariate spatio-temporal data set. The resulting data-dense views summarise and simultaneously present hundreds of space-, time-, and variable-constrained subsets of a large multivariate data set in a structure that facilitates their meaningful comparison and supports visual analysis. Interactive techniques allow localised patterns to be explored and subsets of interest selected and compared with the spatial aggregate. Spatial variation is considered through interactive raster maps and high-resolution local road maps. The techniques are developed in the context of 42.2 million records of vehicular activity in a 98 km2 area of central London and informally evaluated through a design used in the exploratory visualisation of this data set. The main advantages of our technique are the means to simultaneously display hundreds of summaries of the data and to interactively browse hundreds of variable combinations with ordering and symbolism that are consistent and appropriate for space- and time-based variables. These capabilities are difficult to achieve in the case of spatio-temporal data with categorical attributes using existing geovisualisation methods. We acknowledge limitations in the treemap representation but enhance the cognitive plausibility of this popular layout through our two-dimensional ordering algorithm and interactions. Patterns that are expected (e.g. more traffic in central London), interesting (e.g. the spatial and temporal distribution of particular vehicle types) and anomalous (e.g. low speeds on particular road sections) are detected at various scales and locations using the approach. In many cases, anomalies identify biases that may have implications for future use of the data set for analyses and applications. Ordered treemaps appear to have potential as interactive interfaces for variable selection in spatio-temporal visualisation.
TL;DR: The conceptual framework suggests an approach for design layout that can be flexibly modified to explore spatial and temporal trends, temporal relationships among events, periodic temporal patterns, the timing of irregularly repeating events, event-event relationships in terms of thematic attributes, and event patterns at different spatial andporal granularities.
Abstract: The expanding deployment of sensor systems that capture location, time, and multiple thematic variables is increasing the need for exploratory spatio-temporal data analysis tools. Geographic information systems (GIS) and time series analysis tools support exploration of spatial and temporal patterns respectively and independently, but tools for the exploration of both dimensions within a single system are relatively rare. The contribution of this research is a framework for the visualization and exploration of spatial, temporal, and thematic dimensions of sensor-based data. The unit of analysis is an event, a spatio-temporal data type extracted from sensor data. The conceptual framework suggests an approach for design layout that can be flexibly modified to explore spatial and temporal trends, temporal relationships among events, periodic temporal patterns, the timing of irregularly repeating events, event-event relationships in terms of thematic attributes, and event patterns at different spatial and temporal granularities. Flexible assignment of spatial, temporal, and thematic categories to a set of graphical interface elements that can be easily rearranged provides exploratory power as well as a generalizable design layout structure. The framework is illustrated with events extracted from Gulf of Maine Ocean Observing System data but the approach has broad application to other domains and applications in which time, space, and attributes need to be considered in conjunction.
TL;DR: The experiments aimed to determine the maximum number of variables that can be, from a user's point of view, efficiently used in a multi-relational 3D parallel coordinates display and to present a first attempt to study users' ability to analyse noisy data in parallel coordinates.
Abstract: This article presents a study that investigates the ability of humans to perceive relationships (patterns) in parallel coordinates, an ability that is crucial to the use of this popular visualization technique. It introduces a visual quality metric, acceptable distortions of patterns, which establishes the level of noise that may be present in data while allowing accurate identification of patterns. This metric was used to assess perceptual performance of standard 2D parallel coordinates and multi-relational 3D parallel coordinates in two experiments. In multirelational 3D parallel coordinates the axes are placed on a circle with a focus axis in the centre, allowing a simultaneous analysis between the focus variable and all other variables. The experiments aimed to determine the maximum number of variables that can be, from a user's point of view, efficiently used in a multi-relational 3D parallel coordinates display and to present a first attempt to study users' ability to analyse noisy data in parallel coordinates. The results show that, in terms of the acceptable level of noise in data, a multirelational 3D parallel coordinates visualization having 11 axes (variables) is as efficient as standard 2D parallel coordinates. Visualizing a larger number of variables would possibly require a greater amount of manipulation of the visualization and thus be less efficient.
TL;DR: The results of a teaching survey based on the information given by the attendees of Dagstuhl Seminar 07221 are described, which covers several aspects of offered InfoVis courses that range from different kinds of study materials to practical exercises.
Abstract: Teaching InfoVis is a challenge because it is a new and growing field. This paper describes the results of a teaching survey based on the information given by the attendees of Dagstuhl Seminar 07221. It covers several aspects of offered InfoVis courses that range from different kinds of study materials to practical exercises. We have reproduced the discussion during the seminar and added our own experiences. We hope that this paper can serve as an interesting and helpful source for current and future InfoVis teachers.
TL;DR: GIViz (Geospatial Interactions Visualizer), a visualization tool that enables system designers to analyze user interface behavior with a geospatial data set to gain a better understanding of the correlation between users' actions, the interaction strategy employed for approaching a particular type of task and users’ interests.
Abstract: Much information can be derived about users' geospatial information requirements based on how they interact with a geospatial system. Our research focuses on the analysis of mouse movements and map navigation operations as a proxy to implicitly determine users' interests. Visualization provides an effective way of investigating how these interactions can provide an insight into users' preferences and task at hand. This article describes GIViz (Geospatial Interactions Visualizer), a visualization tool that enables system designers to analyze user interface behavior with a geospatial data set. Behavior traits identified can be exploited to improve map personalization engines. In particular, this article discusses the visualization of user interface behavior to gain a better understanding of the correlation between users' actions, the interaction strategy employed for approaching a particular type of task and users' interests.
TL;DR: The results of the experiment confirm that the combined methodology can successfully identify spatio-temporal patterns in the local GWR parameter estimates that correspond to the controlled behaviour of the original parameters.
Abstract: The paper examines the potential for combining a spatial statistical methodology - Geographically Weighted Regression (GWR) - with geovisual analytical exploration to help understand complex spatio-temporal processes This is done by applying the combined statistical - exploratory methodology to a simulated data set in which the behaviour of regression parameters was controlled across space and time A variety of complex spatio-temporal processes was captured through space-time (ie as spatio-temporal) varying parameters whose values were known The task was to see if the proposed methodology could uncover these complex processes from the data alone The results of the experiment confirm that the combined methodology can successfully identify spatio-temporal patterns in the local GWR parameter estimates that correspond to the controlled behaviour of the original parameters
TL;DR: A cartographic solution able to represent dynamics, movements and changes that underlie possible problems based on the chorem concept is proposed, which represents an immediate synthesis of data of interest, and provides expert users with both a global view of objects and phenomena, and an insight into a specific issue.
Abstract: When dealing with scenarios referring to complex issues, such as political, economic and demographic problems, the usage of visual metaphors represents a more effective approach in supporting users to locate facts and new patterns. In this paper, we describe a research project whose aim is to investigate a cartographic solution able to represent dynamics, movements and changes that underlie possible problems. The solution we propose is based on the chorem concept. It represents an immediate synthesis of data of interest, and provides expert users with both a global view of objects and phenomena, and an insight into a specific issue. Based on preliminary studies, we first provide a formal definition and classification of chorems in terms of structure and meaning, meant to homogenize chorem construction and usage. Then, a system to generate chorematic maps from available data sets is described and an XML-like language, named ChorML is specified, enabling system modules communication. In order to validate our approach, we exemplify the construction of a chorematic map, which depicts the most significant flows of migrating population in Italy in 2000. Such a synthesis may represent the starting point for further processing tasks aimed to derive spatial analysis data, as well as to support expert users in decision making.
TL;DR: The results support the claim that GreenMax can be used to locate unexpected features or structures behind a graph and the contributions of GreenMax are evaluated in the larger context of visual analytics on large small-world graphs.
Abstract: We present an information visualization tool, known as GreenMax, to visually explore large small-world graphs with up to a million graph nodes on a desktop computer. A major motivation for scanning a small-world graph in such a dynamic fashion is the demanding goal of identifying not just the well-known features but also the unknown-known and unknown-unknown features of the graph. GreenMax uses a highly effective multilevel graph drawing approach to pre-process a large graph by generating a hierarchy of increasingly coarse layouts that later support the dynamic zooming of the graph. This paper describes the graph visualization challenges, elaborates our solution, and evaluates the contributions of GreenMax in the larger context of visual analytics on large small-world graphs. We report the results of two case studies using GreenMax and the results support our claim that we can use GreenMax to locate unexpected features or structures behind a graph.
TL;DR: A Temporal Focus + Context visualization model is proposed to overcome issues from such techniques resorting to concepts from Information Visualization, and has been applied to several test scenarios and proved appropriate and useful for a wide range of domains that require the display, exploration and analysis of spatial information discretely evolving over time.
Abstract: Spatiotemporal databases provide effective means to represent, manage and query information evolving over time. However, the visualization of record sets that result from spatiotemporal queries through traditional visualization techniques can be of difficult interpretation or may lack the ability to meaningfully display several instants at the same time. We propose a Temporal Focus + Context visualization model to overcome issues from such techniques resorting to concepts from Information Visualization. In this model, Focus + Context is applied to time rather than, as more typically, to attributes or space, and allows large amounts of data from distinct periods of time and from several record sets to be compressed onto one. Underlying the proposed visualization technique is the calculation of a temporal degree of interest (TDOI) for each record driven by specific analysis, exploration or presentation goals and based on the record valid time attribute, as well as on user-defined temporal visualization requirements. In the mapping stage of the visualization pipeline, the TDOI for a record is used to control graphical properties, such as transparency and color. More complex rendering properties, such as sketch drawing edges or other non-photorealistic enhancement techniques, can also be used to convey the temporal aspects of data, replacing the original graphical features of the record data. By enhancing or dimming the representation of a data item, according to the corresponding degree of interest, it is possible to meaningfully compress information about distinct temporal states of data onto the same visualization display. The model has been applied to several test scenarios and proved appropriate and useful for a wide range of domains that require the display, exploration and analysis of spatial information discretely evolving over time.
TL;DR: This article proposes an extension of the original Attribute Explorer technique by Spence and colleagues to take on the challenges presented in the domain of professional team-sport analysis and uses football game-event data to highlight the new possibilities.
Abstract: Advances in interactive systems and the ability to manage increasing amounts of high-dimensional data provide new opportunities in numerous domains. Information visualization techniques are especially useful in situations where analysts seek patterns and information of interest in massive data sets. In this article, we propose an extension of the original Attribute Explorer (AE) technique by Spence and colleagues to take on the challenges presented in the domain of professional team-sport analysis. We describe the implementation of an extended AE and use football game-event data to highlight the new possibilities.
Journal Article•
TL;DR: A radiation image storage panel having a fluorescent layer which comprises a binder and a stimulable phosphor dispersed therein provides an image of high sharpness.
Abstract: A radiation image storage panel having a fluorescent layer which comprises a binder and a stimulable phosphor dispersed therein. Further, the panel is colored with a colorant so that the mean reflectance of the panel in the wavelength region of the stimulating rays of the stimulable phosphor is lower than the mean reflectance of the panel in the wavelength region of the light emitted by the stimulable phosphor upon stimulation thereof. The panel provides an image of high sharpness.
Journal Article•
TL;DR: This report briefly presents the PUL IVS Analysis Center activities during 2008 and plans for the coming year, including improvements of the International Celestial Reference Frame (ICRF), including investigations of stochastic and systematic errors of radio source catalogs and comparison and combination of catalogs.
Abstract: This report briefly presents the PUL IVS Analysis Center activities during 2008 and plans for the coming year. The main topics of investigations in that period were comparison and combination of catalogs of radio source positions, analysis of VLBI EOP series, analysis of radio source position and zenith troposphere delay time series. 1. General Information The PUL IVS Analysis Center was organized in September 2006 and is located at the Central Astronomical Observatory at Pulkovo of Russian Academy of Sciences (Pulkovo Observatory). The main topics of our activity are: • Improvement of the International Celestial Reference Frame (ICRF), including investigations of stochastic and systematic errors of radio source catalogs, constructing combined catalogs, investigation of the ICRF stability, and investigation of radio source position time series. • Computation and analysis of EOP, station position, baseline length, and zenith troposphere delay time series. • Investigation of the Free Core Nutation (FCN). • Comparison of VLBI results with other space geodesy techniques. The PUL AC’s Web page http://www.gao.spb.ru/english/as/ac vlbi/ is supported.
Journal Article•
TL;DR: In this article, the authors analyze VLBI delays back to 1984 from the permanent geodetic network, and ten superconducting gravimeter records from the Global Geodynamic Project spanning more than 7 years.
Abstract: We analyze VLBI delays back to 1984 from the permanent geodetic network, and ten superconducting gravimeter records from the Global Geodynamic Project spanning more than 7 years. From the former data, we deduce nutation o sets, and from the latter we get gravimetric factors. Comparison of these observed quantities against theoretical expressions of the core and mantle admittance to the tidal potential allows us to estimate Love numbers and resonant frequencies and quality factors of the core. We point out strengths and deficiencies of each technique in their ability to retrieve the Earth's interior parameters.