The study of human activity in space and time is an inherent part of human geography. In order to perform such studies, data on the time use of individuals, in terms of sequence and timing of performed activities, are collected and analysed. A common assumption when analysing individuals’ time use is that groups that exhibit similar background and demographic characteristics also display similarities in how they use their time to structure their daily lives. In this article, we set out to investigate the correctness of such assumptions. We propose a visual analytics process based on sequence similarity measures tailored to event-based data such as performed activity sequences. The process allows an analyst to retrieve similarly behaving records according to user-selected similarity preferences and interactively explore aspects of this similarity in a multiple linked-view environment.

Visual comparison is an intrinsic part of interactive data exploration and analysis. The literature provides a large body of existing solutions that help users accomplish comparison tasks. These solutions are mostly of visual nature and custom-made for specific data. We ask the question if a more general support is possible by focusing on the interaction aspect of comparison tasks. As an answer to this question, we propose a novel interaction concept that is inspired by real-world behavior of people comparing information printed on paper. In line with real-world interaction, our approach supports users (1) in interactively specifying pieces of graphical information to be compared, (2) in flexibly arranging these pieces on the screen, and (3) in performing the actual comparison of side-by-side and overlapping arrangements of the graphical information. Complementary visual cues and add-ons further assist users in carrying out comparison tasks. Our concept and the integrated interaction techniques are generally applicable and can be coupled with different visualization techniques. We implemented an interactive prototype and conducted a qualitative user study to assess the concepts usefulness in the context of three different visualization techniques. The obtained feedback indicates that our interaction techniques mimic the natural behavior quite well, can be learned quickly, and are easy to apply to visual comparison tasks.

With the widespread use of deformation simulations in medical applications, the realism of the force feedback has become an important issue. In order to reach real-time performance with sufficient realism the approach of adaptivity, solution of different parts of the system with different resolutions and refresh rates, has been commonly deployed. The change in accuracy resulting from the use of adaptivity, however, has been been paid scant attention in the deformation simulation field. Presentation of error metrics is rare, while more focus is given to the real-time stability. We propose an abstract pipeline to perform error analysis for different types of deformation techniques which can consider different simulation parameters. A case study is also performed using the pipeline, and the various uses of the error estimation are discussed.

Today weather forecasts assist in the preparation of roads during the winter season to avoid accidents resulting from snow, rain and slipperiness. As with any weather forecast there is always a search for improvement. One way to do this is by verifying the forecasted parameters with the actual weather observed in the forecasted area. To facilitate identification of significant trends and patterns within weather data we have developed an application based on interactive information visualization techniques. The application was created in close collaboration with domain experts from the Swedish Meteorological and Hydrological Institute and initial feedback from a performed user study shows that interactive visualization speeds up the analysis process as well as increases flexibility compared to currently used manual methods.

This paper presents an interview-based study of the definition of sequence similarity in different application areas of event-based data. The applicability of nine identified measures across these areas is investigated and discussed. The work helps highlight what are the core characteristics sought when analysing event-based data and performs a first validation of this across disciplines. The results of the study make a solid basis for follow-up evaluations of the practical applicability and usability of the similarity measures.

Operators of power grid supervisory control systems have to gather information from a wide variety of views to build situation awareness. Findings from a conducted field study show that this task is challenging and cognitively demanding. Visualization research for power grid supervisory control systems has focused on developing new visualization techniques for representing one aspect of the power system data. Little work has been done to demonstrate how information visualization techniques can support the operator in the sense making process to achieve situation awareness. To fill this gap, and with support from a field study, we propose solutions based on multiple and coordinated views, visual interactive filtering and parallel coordinates.

The research work presented in this thesis is concerned with the analysis of the human body as a calibration platform for estimation of a pinhole camera model used in Augmented Reality environments mediated through Optical See-Through Head-Mounted Display. Since the quality of the calibration ultimately depends on a subject’s ability to construct visual alignments, the research effort is initially centered around user studies investigating human-induced noise, such as postural sway and head aiming precision. Knowledge about subject behavior is then applied to a sensitivity analysis in which simulations are used to determine the impact of user noise on camera parameter estimation.

Quantitative evaluation of the calibration procedure is challenging since the current state of the technology does not permit access to the user’s view and measurements in the image plane as seen by the user. In an attempt to circumvent this problem, researchers have previously placed a camera in the eye socket of a mannequin, and performed both calibration and evaluation using the auxiliary signal from the camera. However, such a method does not reflect the impact of human noise during the calibration stage, and the calibration is not transferable to a human as the eyepoint of the mannequin and the intended user may not coincide. The experiments performed in this thesis use human subjects for all stages of calibration and evaluation. Moreover, some of the measurable camera parameters are verified with an external reference, addressing not only calibration precision, but also accuracy.

The purpose of this paper is to present how, using a visualization method, electricity use can be derived from the everyday activity patterns of household members. Target groups are, on the one hand, professionals in the energy sector and energy advisors who need more knowledge about household energy use, and, on the other hand, household members wanting to reduce the energy use by revealing their own habits and thereby finding out how changed activity performance may influence electricity use. The focus is on the relation between utilizing electric appliances to perform everyday life activities and the use of electricity. The visualization method is based on the time-geographic approach developed by Hägerstrand and includes a model that estimates appliance electricity use from household members’ activities. Focus, in this paper, is put on some basic activities performed to satisfy daily life needs: cooking and use of information, communication and entertainment devices. These activities appear frequently in the everyday life of households, even though not all household members perform them all. The method is applied on a data material comprising time-diaries written by 463 individuals (aged 10 to 85+) in 179 households in different parts of Sweden. The visualization method reveals when and for how long activities that claim electric appliances are performed by which individual(s). It also shows electricity load curves generated from the use of appliances at different levels, such as individual, household and group or population levels. At household level the method can reveal which household members are the main users of electricity, i.e. the division of labour between household members. Thereby it also informs about whom could be approached by energy companies and energy advisors in information campaigns. The main result of the study is that systematic differences in activity patterns in subgroups of a population can be identified (e.g. men and women) but that directed information based on these patterns has to be made with care and with the risk of making too broad generalizations.

Studies of the ecology of microbial populations are increasingly common within many research areas as the field of microbiomics develops rapidly. The study of the ecology in sampled microbial populations generates high dimensional data sets. Although many analysis methods are available for examination of such data, a tailored tool was required to fulfill the need of interactivity and flexibility for microbiologists. In this paper, MicrobiVis is presented. It is a tool for visual exploration and interactive analysis of microbiomic populations. MicrobiVis has been designed in close collaboration with end users. It extends previous interactive systems for explorative dimensionality reduction by including a range of domain relevant features. It contributes a flexible and explorative dimensionality reduction as well as a visual and interactive environment for examination of data subsets. By combining information visualization and methods based on analytic tasks common in microbiology as a means for gaining new and relevant insights. The utility of MicrobiVis is demonstrated through a use case describinghow a microbiologist may use the system for a visual analysis of amicrobial data set. Its usability and potential is indicated throughpositive feedback from the current end users.

We will present the software application VISUAL-TimePAcTS/energy use. The application shows, in a flexible way, the energy use of individuals, households, groups and whole populations which is calculated through individuals’ performed activities. Input data is diary logs for the 24 hours of the day. There are several visualizations opportunities. First, all activities performed by each individual in the population can be shown. Second, activity patterns (i.e. combinations and repetitions of activities) can be identified and represented. Third, the activities that request energy for their performance can be visualized. Fourth, “load curves” that show the power demand can be constructed, within the application, from a set of rules relating energy consumed by different appliances to performed activities requiring these appliances. We will also present principles used for doing the activity categorization (a categorization scheme), and how we hope to develop the software further. The application opens new opportunities to make use of national time use surveys.

There have been many attempts to exploit three- dimensional displays in Air Traffic Control where it has long been suspected that the 3D display may help to reduce the cognitive load on the controller by removing the need to construct an elaborate mental model of the air space and the traffic contained within it. 3D displays could allow the controller to simply re-interpret the presented information in real time without the need for them to construct this internal model and without the need to remember large amounts of complex information. This should result in controllers being able to manage larger numbers of aircraft without loss of safety, as well as reducing the pressure on controllers allowing for longer work sessions with less problems of mental fatigue.

The purpose of this study has been to explore the use of 3D in controller training and, in this initial study, to examine the basic reaction of the controllers to 3D representations and the effects, if any, which the introduction of 3D has on their work.

Event-based data are encountered daily in many disciplines and are used for various purposes. They are collections of ordered sequences of events where each event has a start time and a duration. Examples of such data include medical records, internet surfing records, transaction records, industrial process or system control records, and activity diary data.

This thesis is concerned with the exploration of event-based data, and in particular the identification and analysis of sequences within them. Sequences are interesting in this context since they enable the understanding of the evolving character of event data records over time. They can reveal trends, relationships and similarities across the data, allow for comparisons to be made within and between the records, and can also help predict forthcoming events.The presented work has researched methods for identifying and exploring such event-sequences which are based on modern visualization, interaction and data mining techniques.

An interactive visualization environment that facilitates analysis and exploration of event-based data has been designed and developed, which permits a user to freely explore different aspects of this data and visually identify interesting features and trends. Visual data mining methods have been developed within this environment, that facilitate the automatic identification and exploration of interesting sequences as patterns. The first method makes use of a sequence mining algorithm that identifies sequences of events as patterns, in an iterative fashion, according to certain user-defined constraints. The resulting patterns can then be displayed and interactively explored by the user.The second method has been inspired by web-mining algorithms and the use of graph similarity. A tree-inspired visual exploration environment has been developed that allows a user to systematically and interactively explore interesting event-sequences.Having identified interesting sequences as patterns it becomes interesting to further explore how these are incorporated across the data and classify the records based on the similarities in the way these sequences are manifested within them. In the final method developed in this work, a set of similarity metrics has been identified for characterizing event-sequences, which are then used within a clustering algorithm in order to find similarly behavinggroups. The resulting clusters, as well as attributes of the clusteringparameters and data records, are displayed in a set of linked views allowing the user to interactively explore relationships within these.

The research has been focused on the exploration of activity diary data for the study of individuals' time-use and has resulted in a powerful research tool facilitating understanding and thorough analysis of the complexity of everyday life.

Just noticeable difference (JND) describes how much two perceptual sensory inputs must differ in order to be distinguishable from each other. Knowledge of the JND is vital when two features in a dataset are to be separably represented. JND has received a lot of attention in haptic research and this study makes a contribution to the field by determining JNDs during users' probing of volumetric data at two force levels. We also investigated whether these JNDs were affected by where in the haptic workspace the probing occurred. Reference force magnitudes were 0.1 N and 0.8 N, and the volume data was presented in rectangular blocks positioned at the eight corners of a cube 10 cm³ in size. Results showed that the JNDs varied significantly for the two force levels, with mean values of 38.5% and 8.8% obtained for the 0.1 N and 0.8 N levels, respectively, and that the JND was influenced by where the data was positioned.

While label placement algorithms are generally successful in managing visual clutter by preventing label overlap, they can also cause significant label movement in dynamic displays. This study investigates motion detection thresholds for various types of label movement in realistic and complex virtual environments, which can be helpful for designing less salient and disturbing algorithms. Our results show that label movement in stereoscopic depth is shown to be less noticeable than similar lateral monoscopic movement, inherent to 2D label placement algorithms. Furthermore, label movement can be introduced more readily into the visual periphery (over 15° eccentricity) because of reduced sensitivity in this region. Moreover, under the realistic viewing conditions that we used, motion of isolated labels is more easily detected than that of overlapping labels. This perhaps counterintuitive finding may be explained by visual masking due to the visual clutter arising from the label overlap. The quantitative description of the findings presented in this paper should be useful not only for label placement applications, but also for any cluttered AR or VR application in which designers wish to control the users’ visual attention, either making text labels more or less noticeable as needed.

For the simulation of soft tissue deformation Finite ElementMethod (FEM) has been the technique which achieves most physicallyrealistic behaviour. However to provide stable force feedback,high refresh rates are needed which makes the use of FEMnon-trivial.To solve the challenge of the compromise between speed and realism,asynchronous regions which solves different parts of the modelwith different frequencies and different resolutions are used. Thelocal neighbourhood of the contact is solved with higher frequencyand resolution while the more remote regions are solved with lowerfrequency and resolutions. Different solution methods, implicit andexplicit, can be used to solve different regions and the size of theregions can be adapted depending on the strain to maximize theefficiency.

The mitigation of registration errors is a central challenge for improving the usability of AugmentedReality systems. While the technical achievements within tracking and display technology continue toimprove the conditions for good registration, little research is directed towards understanding theuser’s visual alignment performance during the calibration process. This paper reports 12 standingsubjects’ visual alignment performance using an optical see-through head mounted display for viewingdirections varied in azimuth (0°, ±30°, ±60°) and elevation (0°, ±10°). Although viewing direction hasa statistically significant effect on the shape of the distribution, the effect is small and negligible forpractical purposes and can be approximated to a circular distribution with a standard deviation of 0.2°for all viewing directions studied in this paper. In addition to quantifying head aiming accuracy with ahead fixed cursor and illustrating the deteriorating accuracy of boresight calibration with increasingviewing direction extremity, the results are applicable for filter design determining the onset and end ofhead rotation.

In a time of global change and global resource constraints the academic community is constantly seeking new ways of communicating current research to inform the public and create a basis for decision making on an individual to global scale. For climate researchers, this challenge is pertinent, given the vast amount of information regarding issues, such as emissions, scenarios, trends, risks and options for mitigation and adaptation that flows through media every day. To create a solid representation of research data and scenarios as well as what impacts of climate change could imply in different regions, climate researchers have over the past years started to collaborate with designers and researchers within the field of visualization. Applications assisting data analysis as well as geospatial and abstract visual representations bear great potential for future research and science communication. We are referring to this transdisciplinary field of research and science communication as climate visualization.

Employing three-dimensional displays in Air Traffic Control (ATC) has been the object of study and debates for numerous years. Although empirical studies have often led to mixed results, some preliminary evidence suggests that training could be a suitable domain of application for 3D interfaces. Little evidence, however, is available to fully support this claim. We attempted to fill this gap with a project that aims at studying and evaluating 3D displays for ATC training purposes. This paper describes the first steps of this project, by reporting and discussing the results of a study aiming at understanding whether ATC trainees form a three-dimensional image of air traffic and at comprehending what the nature of this 3D picture is.

This paper reports on an experiment comparing label placement techniques in a dynamic virtual environment rendered on a stereoscopic display. The labeled objects are in motion, and thus labels need to continuously maintain separation for legibility. The results from our user study show that traditional label placement algorithms, which always strive for full label separation in the 2D view plane, produce motion that disturbs the user in a visual search task. Alternative algorithms maintaining separation in only one spatial dimension are rated less disturbing, even though several modifications are made to traditional algorithms for reducing the amount and salience of label motion. Maintaining depth separation of labels through stereoscopic disparity adjustments is judged theleast disturbing, while such separation yields similar user performance to traditional algorithms. These results are important in the design offuture 3D user interfaces, where disturbing or distracting motion due to object labeling should be avoided.

The complex nature of multivariate data sets calls forhigh interactive performance and intuitive metaphors. Aspecific type of multivariate data is where the variables sum up to a constant, here defined as multicomponent data.This application paper presents an interactive applicationfor analysis of modelled multicomponent data. The aim isto find high performance variable combinations that fulfil some requested properties. The application is basedon coordinated views that include parallel coordinates, a ternary diagram, a 2D scatter plot and a line plot. It supports numerous interaction techniques enabling fast analysisof complex patterns in multicomponent data sets. The application is developed in collaboration with researchers within the fields of statistics and chemistry. An informal usability evaluation indicates that the interactive nature ofthe application clearly facilitates the analysis process.

In order to simulate both physically and visually realistic soft tissuedeformations, the Finite Element Method (FEM) is the mostpopular choice in the literature. However it is non-trivial to modelcomplex behaviour of soft tissue with sufficient refresh rates, especiallyfor haptic force feedback which requires an update rate ofthe order of 1 kHz. In this study the use of asynchronous regions isproposed to speed up the solution of FEM equations in real-time. Inthis way it is possible to solve the local neighborhood of the contactwith high refresh rates, while evaluating the more distant regions atlower frequencies, saving computational power to model complexbehaviour within the contact area. Solution of the different regionsusing different methods is also possible. To attain maximum efficiencythe size of the regions can be changed, in real-time, in responseto the size of the deformation.

This paper introduces Vector Field Perpendicular Surfaces as a means to represent vector data with special focus on variations across the vectors in the field. These surfaces are a perpendicular analogue to streamlines, with the vector data always being parallel to the normals of the surface. In this way the orientation of the data is conveyed to the viewer, while providing a continuous representation across the vectors of the field. This paper describes the properties of such surfaces including an issue with helicity density in the vector data, an approach to generating them, several stop conditions and special means to handle also fields with non-zero helicity density.

The precision with which users can maintain boresight alignment between visual targets at different depths is recorded for 24 subjects using two different boresight targets. Subjects' normal head stability is established using their Romberg coefficients. Weibull distributions are used to describe the probabilities of the magnitude of head positional errors and the three dimensional cloud of errors is displayed by orthogonal two dimensional density plots. These data will lead to an understanding of the limits of user introduced calibration error in augmented reality systems.

The rendering of large data sets can result in cluttered displays and non-interactive update rates, leading to time consuming analyses. A straightforward solution is to reduce the number of items, thereby producing an abstraction of the data set. For the visual analysis to remain accurate, the graphical representation of the abstraction must preserve the significant features present in the original data. This paper presents a screen space quality method, based on distance transforms, that measures the visual quality of a data abstraction. This screen space measure is shown to better capture significant visual structures in data, compared with data space measures. The presented method is implemented on the GPU, allowing interactive creation of high quality graphical representations of multivariate data sets containing tens of thousands of items. © 2008 The Eurographics Association and Blackwell Publishing Ltd.

The postural sway in 24 subjects performing a boresight calibration task on a large format head-up display is studied to estimate the impact of human limits on boresight calibration precision and ultimately on static registration errors. The dependent variables, accumulated sway path and omni-directional standard deviation, are analyzed for the calibration exercise and compared against control cases where subjects are quietly standing with eyes open and eyes closed. Findings show that postural stability significantly deteriorates during boresight calibration compared to when the subject is not occupied with a visual task. Analysis over time shows that the calibration error can be reduced by 39% if calibration measurements are recorded in a three second interval at approximately 15 seconds into the calibration session as opposed to an initial reading. Furthermore parameter optimization on experiment data suggests a Weibull distribution as a possible error description and estimation for omni-directional calibration precision. This paper extends previously published preliminary analyses and the conclusions are verified with experiment data that has been corrected for subject inverted pendulum compensatory head rotation by providing a better estimate of the position of the eye. With correction the statistical findings are reinforced.

Recent work has shown that overlapping labels in far-field AR environments can be successfully segregated by remapping them to predefined stereoscopic depth layers. User performance was found to be optimal when setting the interlayer disparity to 5-10 arcmin. The current paper investigates to what extent this label segregation technique, label layering, is affected by important perceptual defects in AR such as registration errors and mismatches in accommodation, visual resolution and contrast. A virtual environment matched to a corresponding AR condition but lacking these problems showed a reduction in average response time by 10%. However, the performance pattern for different label layering parameters was not significantly different in the AR and VR environments, showing robustness of this label segregation technique against such perceptual issues.

This paper describes a novel technique for segregating overlapping labels in stereoscopic see-through displays. The present study investigates the labeling of far-field objects, with distances ranging 100-120 m. At these distances the stereoscopic disparity difference between objects is below 1 arcmin, so labels rendered at the same distance as their corresponding objects appear as if on a flat layer in the display. This flattening is due to limitations of both display and human visual resolution. By remapping labels to predetermined depth layers on the optical path between the observer and the labeled object, an interlayer disparity ranging from 5 to 20 arcmin can be achieved for 5 overlapping labels. The present study evaluates the impact of such depth separation of superimposed layers, and found that a 5 arcmin interlayer disparity yields a significantly lower response time, over 20% on average, in a visual search task compared to correctly registering labels and objects in depth. Notably the performance does not improve when doubling the interlayer disparity to 10 arcmin and, surprisingly, the performance degrades significantly when again doubling the interlayer disparity to 20 arcmin, approximating the performance in situations with no interlayer disparity. These results confirm that our technique can be used to segregate overlapping labels in the far visual field, without the cost associated with traditional label placement algorithms.

Data can be found everywhere, for example in the form of price, size, weight and colour of all products sold by a company, or as time series of daily observations of temperature, precipitation, wind and visibility from thousands of stations. Due to their size and complexity it is intrinsically hard to form a global overview and understanding of them. Information visualization aims at overcoming these difficulties by transforming data into representations that can be more easily interpreted.

This thesis presents work on the development of methods to enable efficient information visualization of multivariate and time-varying data sets by conveying information in a clear and interpretable way, and in a reasonable time. The work presented is primarily based on a popular multivariate visualization technique called parallel coordinates but many of the methods can be generalized to apply to other information visualization techniques.

A three-dimensional, multi-relational version of parallel coordinates is presented that enables a simultaneous analysis of all pairwise relationships between a single focus variable and all other variables included in the display. This approach permits a more rapid analysis of highly multivariate data sets. Through a number of user studies the multi-relational parallel coordinates technique has been evaluated against standard, two-dimensional parallel coordinates and been found to better support a number of different types of task.

High precision density maps and transfer functions are presented as a means to reveal structure in large data displayed in parallel coordinates. These two approaches make it possible to interactively analyse arbitrary regions in a parallel coordinates display without risking the loss of significant structure.

Another focus of this thesis relates to the visualization of time-varying, multivariate data. This has been studied both in the specific application area of system identification using volumetric representations, as well as in the general case by the introduction of temporal parallel coordinates.

The methods described in this thesis have all been implemented using modern computer graphics hardware which enables the display and manipulation of very large data sets in real time. A wide range of data sets, both synthetically generated and taken from real applications, have been used to test these methods. It is expected that, as long as the data have multivariate properties, they could be employed efficiently.

With current methods for volume haptics in scientific visualization, features in time-varying data can freely move straight through the haptic probe without generating any haptic feedback-the algorithms are simply not designed to handle variation with time but consider only the instantaneous configuration when the haptic feedback is calculated. This article introduces haptic rendering of dynamic volumetric data to provide a means for haptic exploration of dynamic behavior in volumetric data. We show how haptic feedback can be produced that is consistent with volumetric data moving within the virtual environment and with data that, in itself, evolves over time. Haptic interaction with time-varying data is demonstrated by allowing palpation of a computerized tomography sequence of a beating human heart.

In this paper we present an in situ evaluation of a haptic system, with a representative test population, we aim to determine what, if any, benefit haptics can have in a biomolecular education context. We have developed a haptic application for conveying concepts of molecular interactions, specifically in protein-ligand docking. Utilizing a semi-immersive environment with stereo graphics, users are able to manipulate the ligand and feel its interactions in the docking process. The evaluation used cognitive knowledge tests and interviews focused on learning gains. Compared with using time efficiency as the single quality measure this gives a better indication of a system's applicability in an educational environment. Surveys were used to gather opinions and suggestions for improvements. Students do gain from using the application in the learning process but the learning appears to be independent of the addition of haptic feedback. However the addition of force feedback did decrease time requirements and improved the students understanding of the docking process in terms of the forces involved, as is apparent from the students' descriptions of the experience. The students also indicated a number of features which could be improved in future development.

Motivation - To identify a suitable interaction modality -among the ones currently implemented in a three-dimensional (3D) environment for Air Traffic Control- for allowing interactive exploration of and gathering information about 3D weather structures. Research approach - A usability study entailing four interaction modalities (also called -interaction interfaces-): voice, wand, pen and sketch interfaces, across a task requiring 3D surface exploration, information gathering and recall of information. Quantitative data (time, errors and a composite performance index) as well as qualitative data were collected. Findings/Design - Overall, the results indicate that the wand supported a better performance when compared to the other interaction interfaces. Among the four interaction interfaces, the voice interface seems to present additional limitations, mostly related to time lag in the voice recognition, that were judged as a source of frustration. Originality/Value - The present work provides empirical results deriving from a comparative usability study of four interaction interfaces; it contributes to the study of interaction in 3D environments with new empirical data.

This paper introduces Temporal Density Parallel Coordinates (TDPC) and Depth Cue Parallel Coordinates (DCPC) which extend the standard 2D parallel coordinates technique to capture time-varying dynamics. The proposed techniques can be used to analyse temporal positions of data items as well as temporal positions of changes occurring using 2D displays. To represent temporal changes, polygons (instead of traditional lines) are rendered in parallel coordinates. The results presented show that rendering polygons is superior at revealing large temporal changes. Both TDPC and DCPC have been efficiently implemented on the GPU allowing the visualization of thousands of data items over thousands of time steps at interactive frame rates.

Direct volume haptics can provide both guidance and extra information during exploration of volumetric data. In this paper we present a novel approach to volume haptics enabling haptic exploration of tissue shape, borders and material properties in data despite low contrast and low signal to noise ratio, as is common in medical MRI data or low dose CT data. The method uses filtering based on implicit knowledge and addresses the problem of overlapping scalar ranges through the introduction of fuzzy classification and corresponding transfer functions for material properties as well as classification-based distance masking for haptic force direction.

This paper shows how 3-dimensional interactive visualization can be used as a tool in system identification. Non-linear or time-dependent dynamics often leave a significant residual with linear, time-invariant models. The structure of this residual is decisive for the subsequent modelling, and by using advanced visualization techniques, the modeller may gain a deeper insight into this structure than can be obtained by standard correlation analysis.

Analysing multivariate data is a difficult task. Extensive interaction with the data is often necessary and, hence, the analysis can be quite time consuming. In this paper, we introduce a method to allow the user to simultaneously examine the relationships of a single dimension with many others in the data. The single dimension can then be interactively changed to allow the user to quickly examine all possible combinations. This method is achieved by extending the standard parallel coordinate approach to a 3D clustered multi-relational parallel coordinate representation (CMRPC). To aid this method, we use a technique called relation spacing which is used to position the axes according to how 'interesting' the different relations are. We also propose a number of interaction techniques to further facilitate the analysis process.

Datasets from Computational Fluid Dynamics (CFD) can be post-processed and visualized to aid understanding of the flow phenomena present. Visualization of CFD data, however, often suffers from problems such as occlusion and cluttering when methods such as glyphing and volume rendering are applied. In this paper we present a case study where new modes for haptic interaction are used to enhance the exploration of CFD data. A VR environment with interactive graphics and an integrated graphical user interface has been implemented. In contrast to previous work on haptic interaction with CFD data we employ a 'reactive' haptic scheme as opposed to direct force maping. The reactive approach not only generates more stable feedback but also provides clearer and more intuitive cues about the underlying data. Two haptic modes are used to enhance the understanding of different features in the flow data: One presents the orientation of the data and also guides the user to follow the stream as it flows around the aircraft fuselage. The other provides a haptic representation of vortex data. This mode enables the user to perceive and so follow tendencies of vorticity and vortices.

We show how 3-dimensional volume graphics can be used as a tool in system identification. Time-dependent dynamics often leave a significant residual with linear, time-invariant models. The structure of this residual is decisive for the subsequent modelling, and by using advanced visualization techniques, the modeller may gain a deeper insight into this structure than that which can be obtained from standard correlation analysis. We present a development platform that merges a rich variety of estimation programs with state of the art visualization techniques.