A relational dependency network (RDN) is a directed graphical model widely used for multi-relational data. These networks allow cyclic dependencies, necessary to represent relational auto-correlations. We describe an approach for learning both the RDN’s structure and its parameters, given an input relational database: First learn a Bayesian network (BN), then transform the Bayesian network to an RDN. Thus fast Bayesian network learning translates into fast RDN learning. The BN-to-RDN transform comprises a simple, local adjustment of the Bayesian network structure and a closed-form transform of the Bayesian network parameters. This method can learn an RDN for a dataset with a million tuples in minutes. We empirically compare our approach to a state-of-the-art RDN learning approach that applies functional gradient boosting, using six benchmark datasets. Learning RDNs via BNs scales much better to large datasets than learning RDNs with current boosting methods.

Class-level models capture relational statistics over object attributes and their connecting links, answering questions such as "what is the percentage of friendship pairs where both friends are women?" Class-level relationships are important in themselves, and they support applications like policy making, strategic planning, and query optimization. We represent class statistics using Parametrized Bayes Nets (PBNs), a first-order logic extension of Bayes nets. Queries about classes require a new semantics for PBNs, as the standard grounding semantics is only appropriate for answering queries about specific ground facts. We propose a novel random selection semantics for PBNs, which does not make reference to a ground model, and supports class-level queries. The parameters for this semantics can be learned using the recent pseudo-likelihood measure (Schulte in SIAM SDM, pp. 462–473, 2011) as the objective function. This objective function is maximized by taking the empirical frequencies in the relational data as the parameter settings. We render the computation of these empirical frequencies tractable in the presence of negated relations by the inverse Möbius transform. Evaluation of our method on four benchmark datasets shows that maximum pseudo-likelihood provides fast and accurate estimates at different sample sizes.

In current radiologists' workstations, a scroll mouse is typically used as the primary input device for navigating image slices and conducting operations on an image. Radiological analysis and diagnosis rely on careful observation and annotation of medical images. During analysis of 3D MRI and CT volumes, thousands of mouse clicks are performed everyday, which can cause wrist fatigue. This paper presents a dynamic control-to-display (C-D) gain mouse movement method, controlled by an eyegaze tracker as the target predictor. By adjusting the C-D gain according to the distance to the target, the mouse click targeting time is reduced. Our theoretical and experimental studies show that the mouse movement time to a known target can be reduced by up to 15%. We also present an experiment with 12 participants to evaluate the role of eyegaze targeting in the realistic situation of unknown target positions. These results indicate that using eyegaze to predict the target position, the dynamic C-D gain method can improve pointing performance by 8% and reduce the error rate over traditional mouse movement.

We present a controlled, quantitative study with 12 participants comparing interaction with a haptically enhanced mixing board against interaction with a mouse in an abstract task that is motivated by several practical parameter space exploration settings. The study participants received 24 sets of one to eight integer values between 0 and 127, which they had to match by making adjustments with physical or graphical sliders. Based on recorded slider motion path data, we developed an analysis algorithm that identifies and measures different types of activity intervals, including error time moving irrelevant sliders and end time in breaks after completing each trial item. Our results showed a significant increase in speed of the mixing board interaction accompanied by reduced perceived cognitive load when compared with the traditional mouse-based GUI interaction. The gains in speed are largely due to the improved times required for the hand to reach for the first slider (acquisition time) and also when moving between different ones, while the actual time spent manipulating relevant sliders is very similar for either input device. These results agree strongly with qualitative predictions from Fitts' Law that the larger targets afforded by the mixer handles contributed to its faster performance. For further investigation, we computed a measure of motion simultaneity based on velocity correlation, which allowed to identify types of items for which increased simultaneous adjustments occur. For continuous parameter space exploration our findings suggest that mixing boards are a good option to provide detailed multi-value control. The strengths of this input method particularly show in settings where screen space is precious and undisrupted visual focus is crucial.

We describe a technique for bundled curve representations in parallel-coordinates plots and present a controlled user study evaluating their effectiveness. Replacing the traditional C^0 polygonal lines by C^1 continuous piecewise Bezier curves makes it easier to visually trace data points through each coordinate axis. The resulting Bezier curves can then be bundled to visualize data with given cluster structures. Curve bundles are efficient to compute, provide visual separation between data clusters, reduce visual clutter, and present a clearer overview of the dataset. A controlled user study with 14 participants confirmed the effectiveness of curve bundling for parallel-coordinates visualization: 1) compared to polygonal lines, it is equally capable of revealing correlations between neighboring data attributes; 2) its geometric cues can be effective in displaying cluster information. For some datasets curve bundling allows the color perceptual channel to be applied to other data attributes, while for complex cluster patterns, bundling and color can represent clustering far more clearly than either alone.

The Body-Centered Cubic (BCC) and Face-Centered Cubic (FCC) lattices have been analytically shown to be more efficient sampling lattices than the traditional Cartesian Cubic (CC) lattice, but there has been no estimate of their visual comparability. Two perceptual studies (each with N=12 participants) compared the visual quality of images rendered from BCC and FCC lattices to images rendered from the CC lattice. Images were generated from two signals: the commonly used Marschner-Lobb synthetic function and a computed tomography scan of a fish tail. Observers found that BCC and FCC could produce images of comparable visual quality to CC, using 30-35 percent fewer samples. For the images used in our studies, the L_2 error metric shows high correlation with the judgement of human observers. Using the L_2 metric as a proxy, the results of the experiments appear to extend across a wide range of images and parameter choices.

Three interaction techniques were evaluated for scrolling stack mode displays of volumetric data. Two used a scroll-wheel mouse: one used only the wheel, while another used a "click and drag" technique for fast scrolling, leaving the wheel for fine adjustments. The third technique used a Shuttle Xpress jog wheel. In a within-subjects design, nine radiologists searched stacked images for simulated hyper-intense regions on brain, knee, and thigh MR studies. Dependent measures were speed, accuracy, navigation path, and user preference. The radiologists considered the task realistic. They had high inter-subject variability in completion times, far larger than the differences between techniques. Most radiologists (eight out of nine) preferred familiar mouse-based techniques. Most participants scanned the data in two passes, first locating anomalies, then scanning for omissions. Participants spent a mean 10.4 s/trial exploring anomalies, with only mild variation between participants. Their rates of forward navigation searching for anomalies varied much more. Interaction technique significantly affected forward navigation rate (scroll wheel 5.4 slices/s, click and drag 9.4, and jog wheel 6.9). It is not clear what constrained the slowest navigators. The fastest navigator used a unique strategy of moving quickly just beyond an anomaly, then backing up. Eight naïve students performed a similar protocol. Their times and variability were similar to the radiologists, but more (three out of eight) students preferred the jog wheel. It may be worthwhile to introduce techniques such as the jog wheel to radiologists during training, and several techniques might be provided on workstations, allowing individuals to choose their preferred method.

Introduction Academic computer science has an odd relationship with software: Publishing papers about software is considered a distinctly stronger contribution than publishing the software. The historical reasons for this paradox no longer apply, but their legacy remains. This limits researchers who see the open-source software movement as an opportunity to make a scholarly contribution. Expanded definitions of scholarship acknowledge both application and discovery as important components. 1 One obstacle remains: evaluation. To raise software to the status of a first-class contribution, we propose "best practices" for the evaluation of the scholarly contribution of open-source software. Typically, scholars who develop software do not include it as a primary contribution for performance reviews. Instead, they write articles about the software and present the articles as contributions. This conflation of articles and software serves neither medium well. An article describes an original intellectual contribution consisting of an idea, the argument for its importance and correctness, and supporting data. In contrast, software is more often an implementation of prior ideas in a usable form. It bridges the often considerable gap between an idea and the practical application of that idea. The original idea and its implementation represent distinct kinds of contribution. The critical gap is the perceived incomparability of these two contributions. Lacking a concise description adapted to the traditional practices of performance review committees, software is difficult to evaluate as a scholarly contribution and is often relegated to second-class status. We propose a framework for common assessment based on widely accepted definitions of scholarship. Within this general framework, we consider the material and procedures that a performance review committee uses to evaluate a publication. We then describe how software can be summarized in a compatible form of bibliographic citation and supplementary material.

We present a design space explorer for the space of experimental designs. For many design problems, design decisions are determined by the consequences of the design rather than its elemental parts. To support this need, the explorer is constructed to make the designer aware of design-level options, provide a structured context for design, and provide feedback on the consequences of design decisions. We argue that this approach encourages the designer to consider a wider variety of designs, which will lead to more effective designs overall. In a qualitative study, experiment designers using the explorer were found to consider a wider variety of designs and more designs overall than they reported considering in their normal practice.

In today's technology-laden society human - computer interaction (HCI) is an important knowledge area for computer scientists and software engineers. This paper surveys existing approaches to incorporate HCI into computer science (CS) and such related issues as the perceived gap between the interests of the HCI community and the needs of CS educators. It presents several implementations of the HCI subset of the CC'01 curricular guidelines, targeting CS educators with varying degrees of HCI expertise. These implementations include course/module outlines from freshman to graduate levels, suggested texts, and project ideas and issues, such as programming languages and environments. Most importantly, each outline incorporates Bloom's taxonomy to identify the depth of knowledge to be mastered by students. This paper condenses collaborative contributions of 26 HCI/CS educators aiming to improve HCI coverage in mainstream CS curricula.

This paper presents a user study of the visual quality of an imaging pipeline employing the optimal body-centered cubic (BCC) sampling lattice. We provide perceptual evidence supporting the theoretical expectation that sampling and reconstruction on the BCC lattice offer superior imaging quality over the traditionally popular Cartesian cubic (CC) sampling lattice. We asked 12 participants to choose the better of two images: one image rendered from data sampled on the CC lattice and one image that is rendered from data sampled on the BCC lattice. We used both synthetic and CT volumetric data, and confirm that the theoretical advantages of BCC sampling carry over to the perceived quality of rendered images. Using 25% to 35% fewer samples, BCC sampled data result in images that exhibit comparable visual quality to their CC counterparts.

The goal of this research was to evaluate two different stack mode layouts for 3D medical images - a regular stack mode layout where just the topmost image was visible, and a new stack mode layout, which included the images just before and after the main image. We developed stripped down user interfaces to test the techniques, and designed a look-alike radiology task using 3D artificial target stimuli implanted in the slices of medical image volumes. The task required searching for targets and identifying the range of slices containing the targets. Eight naive students participated, using a within-subjects design. We measured the response time and accuracy of subjects using the two layouts and tracked the eyegaze of several subjects while they performed the task. Eyegaze data was divided into fixations and saccades Subjects were 19% slower with the new stack layout than the standard stack layout, but 5 of the 8 subjects preferred the new layout. Analysis of the eyegaze data showed that in the new technique, the context images on both sides were fixated once the target was found in the topmost image. We believe that the extra time was caused by the difficulty in controlling the rate of scrolling, causing overshooting. We surmise that providing some contextual detail such as adjacent slices in the new stack mode layout is helpful to reduce cognitive load for this radiology look-alike task.

We use a haptically enhanced mixing board with a video projector as an interface to various data visualization tasks. We report results of an expert review with four participants, qualitatively evaluating the board for three different applications: dynamic queries (abstract task), parallel coordinates interface (multi-dimensional combinatorial search), and ExoVis (3D spatial navigation). Our investigation sought to determine the strengths of this physical input given its capability to facilitate bimanual interaction, constraint maintenance, tight coupling of input and output, and other features. Participants generally had little difficulty with the mappings of parameters to sliders. The graspable sliders apparently reduced the mental exertion needed to acquire control, allowing participants to attend more directly to understanding the visualization. Participants often designated specific roles for each hand, but only rarely moved both hands simultaneously.

Two studies evaluated linear and hierarchy+elision small‐screen display formats for clinical reasoning tasks. A controlled, quantitative study with 28 medically naive participants using a task abstracted from clinical use of laboratory results found that both display formats supported rapid and accurate decision making. Distribution of the search targets significantly affected speed, with decisions in linear format made 13% faster (4.7 sec) when all targets could be viewed on a single screen than when targets required scrolling between several screens and in hierarchical format 15% faster (5.1 sec) when all the targets were confined within one category. Performance was equivalent regardless of the relative order of the target results and data in the laboratory report. In a qualitative study, 7 physicians used the displays to perform a realistic diagnosis. Physicians were comfortable with both display formats, but preference varied with clinical experience. The 5 less experienced clinicians favored hierarchy+elision, whereas the 2 highly experienced clinicians tended to prefer the linear display.

Most users do not experience the same level of fluency in their interactions with computers that they do with physical objects in their daily life. We believe that much of this results from the limitations of unimodal interaction. Previous efforts in the haptics literature to remedy those limitations have been creative and numerous, but have failed to produce substantial improvements in human performance. This paper presents a new approach, whereby haptic interaction techniques are designed from scratch, in explicit consideration of the strengths and weaknesses of the haptic and motor systems. We introduce a haptic alternative to the tool palette, called Pokespace, which follows this approach. Two studies (6 and 12 participants) conducted with Pokespace found no performance improvement over a traditional interface, but showed that participants learned to use the interface proficiently after about 10 minutes, and could do so without visual attention. The studies also suggested several improvements to our design.

A high quality computer synthesis of an acoustic sound source does not necessarily yield a playable virtual musical instrument. A computer simulation of an acoustic musical instrument creates a disconnect between sound production and user input, and correspondingly, between hearing and feeling, in contrast to their interconnection in an acoustic instrument. This disconnect denies the user important haptic clues well known to help instrument control, impeding the user's ability to find, and remain inside, regions of playability. This research explores the addition of haptic feedback to a virtual reed model. In particular, we render the instrument's parameter space as a dynamic force field in order to support fine motor movements and, in turn, provide the user with cues regarding the instrument's oscillatory state and possible regions of playability. We then observe the effects that this additional feedback has on the user's ability to play the virtual instrument

We describe a series of experiments that compare 2D displays, 3D displays, and combined 2D/3D displays (orientation icon, ExoVis, and clip planes) for relative position estimation, orientation, and volume of interest tasks. Our results indicate that 3D displays can be very effective for approximate navigation and relative positioning when appropriate cues, such as shadows, are present. However, 3D displays are not effective for precise navigation and positioning except possibly in specific circumstances, for instance, when good viewing angles or measurement tools are available. For precise tasks in other situations, orientation icon and ExoVis displays were better than strict 2D or 3D displays (displays consisting exclusively of 2D or 3D views). The combined displays had as good or better performance, inspired higher confidence, and allowed natural, integrated navigation. Clip plane displays were not effective for 3D orientation because users could not easily view more than one 2D slice at a time and had to frequently change the visibility of individual slices. Major factors contributing to display preference and usability were task characteristics, orientation cues, occlusion, and spatial proximity of views that were used together.