The primary goal of visual data exploration tools is to enable the discovery of new insights. To justify and reproduce insights, the discovery process needs to be documented and communicated. A ...common approach to documenting and presenting findings is to capture visualizations as images or videos. Images, however, are insufficient for telling the story of a visual discovery, as they lack full provenance information and context. Videos are difficult to produce and edit, particularly due to the non‐linear nature of the exploratory process. Most importantly, however, neither approach provides the opportunity to return to any point in the exploration in order to review the state of the visualization in detail or to conduct additional analyses. In this paper we present CLUE (Capture, Label, Understand, Explain), a model that tightly integrates data exploration and presentation of discoveries. Based on provenance data captured during the exploration process, users can extract key steps, add annotations, and author “Vistories”, visual stories based on the history of the exploration. These Vistories can be shared for others to view, but also to retrace and extend the original analysis. We discuss how the CLUE approach can be integrated into visualization tools and provide a prototype implementation. Finally, we demonstrate the general applicability of the model in two usage scenarios: a Gapminder‐inspired visualization to explore public health data and an example from molecular biology that illustrates how Vistories could be used in scientific journals.
This paper presents details and applications of a novel channel simulation software named NYUSIM, which can be used to generate realistic temporal and spatial channel responses to support realistic ...physical-and link-layer simulations and design for fifth-generation (5G) cellular communications. NYUSIM is built upon the statistical spatial channel model for broadband millimeter-wave (mmWave) wireless communication systems developed by researchers at New York University (NYU). The simulator is applicable for a wide range of carrier frequencies (500 MHz to 100 GHz), radio frequency (RF) bandwidths (0 to 800 MHz), antenna beamwidths (7° to 360° for azimuth and 7° to 45° for elevation), and operating scenarios (urban microcell, urban macrocell, and rural macrocell), and also incorporates multiple-input multiple-output (MIMO) antenna arrays at the transmitter and receiver. This paper also provides examples to demonstrate how to use NYUSIM for analyzing MIMO channel conditions and spectral efficiencies, which show that NYUSIM is an alternative and more realistic channel model compared to the 3rd Generation Partnership Project (3GPP) and other channel models for mmWave bands.
We present a novel visual exploration method based on small multiples and large singles for effective and efficient data analysis. Users are enabled to explore the state space by offering multiple ...alternatives from the current state. Users can then select the alternative of choice and continue the analysis. Furthermore, the intermediate steps in the exploration process are preserved and can be revisited and adapted using an intuitive navigation mechanism based on the well‐known undo‐redo stack and filmstrip metaphor. As proof of concept the exploration method is implemented in a prototype. The effectiveness of the exploration method is tested using a formal user study comparing four different interaction methods. By using Small Multiples as data exploration method users need fewer steps in answering questions and also explore a significantly larger part of the state space in the same amount of time, providing them with a broader perspective on the data, hence lowering the chance of missing important features. Also, users prefer visual exploration with small multiples over non‐small multiple variants.
Dynamic graph visualization focuses on the challenge of representing the evolution of relationships between entities in readable, scalable and effective diagrams. This work surveys the growing number ...of approaches in this discipline. We derive a hierarchical taxonomy of techniques by systematically categorizing and tagging publications. While static graph visualizations are often divided into node‐link and matrix representations, we identify the representation of time as the major distinguishing feature for dynamic graph visualizations: either graphs are represented as animated diagrams or as static charts based on a timeline. Evaluations of animated approaches focus on dynamic stability for preserving the viewer's mental map or, in general, compare animated diagrams to timeline‐based ones. A bibliographic analysis provides insights into the organization and development of the field and its community. Finally, we identify and discuss challenges for future research. We also provide feedback from experts, collected with a questionnaire, which gives a broad perspective of these challenges and the current state of the field.
Dynamic graph visualization focuses on the challenge of representing the evolution of relationships between entities in readable, scalable and effective diagrams. This work surveys the growing number of approaches in this discipline. We derive a hierarchical taxonomy of techniques by systematically categorizing and tagging publications. While static graph visualizations are often divided into node‐link and matrix representations, we identify the representation of time as the major distinguishing feature for dynamic graph visualizations: either graphs are represented as animated diagrams or as static charts based on a timeline. Evaluations of animated approaches focus on dynamic stability for preserving the viewer's mental map or, in general, compare animated diagrams to timeline‐based ones.
The development of a new dissolved gas analysis (DGA) method often requires a comparative study to assess the accuracy of the proposed technique. This is faced with the following challenges: (i) the ...time and effort required to implement and validate the implementation of existing DGA methods, adds to the comparative study cost; (ii) the output states of different DGA methods are not similar, which makes it difficult to put methods side by side in a comparative study; and (iii) the availability of test data is limited. In this study, a user-friendly graphical user interface software package, DGALab, is developed to overcome these challenges. DGALab implements a unified DGA diagnosis framework to map the output states of DGA methods to uniform specifications. DGALab includes a library implementing most common DGA techniques, and includes a repository for input datasets available in the literature and collected directly from laboratories. DGALab simplifies the addition of new DGA techniques written in virtually any programming language. As a result, the process of developing a new DGA technique is greatly simplified using DGALab. To evaluate the software package results, the datasets and methods implemented therein were used to regenerate the results published in earlier research papers.
We present ManuKnowVis, the result of a design study, in which we contextualize data from multiple knowledge repositories of a manufacturing process for battery modules used in electric vehicles. In ...data-driven analyses of manufacturing data, we observed a discrepancy between two stakeholder groups involved in serial manufacturing processes: Knowledge providers (e.g., engineers) have domain knowledge about the manufacturing process but have difficulties in implementing data-driven analyses. Knowledge consumers (e.g., data scientists) have no first-hand domain knowledge but are highly skilled in performing data-driven analyses. ManuKnowVis bridges the gap between providers and consumers and enables the creation and completion of manufacturing knowledge. We contribute a multi-stakeholder design study, where we developed ManuKnowVis in three main iterations with consumers and providers from an automotive company. The iterative development led us to a multiple linked view tool, in which, on the one hand, providers can describe and connect individual entities (e.g., stations or produced parts) of the manufacturing process based on their domain knowledge. On the other hand, consumers can leverage this enhanced data to better understand complex domain problems, thus, performing data analyses more efficiently. As such, our approach directly impacts the success of data-driven analyses from manufacturing data. To demonstrate the usefulness of our approach, we carried out a case study with seven domain experts, which demonstrates how providers can externalize their knowledge and consumers can implement data-driven analyses more efficiently.
In this paper we introduce TimeArcs, a novel visualization technique for representing dynamic relationships between entities in a network. Force‐directed layouts provide a way to highlight related ...entities by positioning them near to each other Entities are brought closer to each other (forming clusters) by forces applied on nodes and connections between nodes. In many application domains, relationships between entities are not temporally stable, which means that cluster structures and cluster memberships also may vary across time. Our approach merges multiple force‐directed layouts at different time points into a single comprehensive visualization that provides a big picture overview of the most significant clusters within a user‐defined period of time. TimeArcs also supports a range of interactive features, such as allowing users to drill‐down in order to see details about a particular cluster. To highlight the benefits of this technique, we demonstrate its application to various datasets, including the IMDB co‐star network, a dataset showing conflicting evidences within biomedical literature of protein interactions, and collocated popular phrases obtained from political blogs.
Given the recent changes in the open source software (OSS) landscape, we examined OSS contributors’ current valued factors, practices, and challenges concerning usability. Our survey provides ...insights for OSS practitioners and tool designers to promote a user-centric mindset and improve usability practice in OSS communities.
A Single-Channel EOG-Based Speller He, Shenghong; Li, Yuanqing
IEEE transactions on neural systems and rehabilitation engineering,
11/2017, Letnik:
25, Številka:
11
Journal Article
Recenzirano
Electrooculography (EOG) signals, which can be used to infer the intentions of a user based on eye movements, are widely used in human-computer interface (HCI) systems. Most existing EOG-based HCI ...systems incorporate a limited number of commands because they generally associate different commands with a few different types of eye movements, such as looking up, down, left, or right. This paper presents a novel single-channel EOG-based HCI that allows users to spell asynchronously by only blinking. Forty buttons corresponding to 40 characters displayed to the user via a graphical user interface are intensified in a random order. To select a button, the user must blink his/her eyes in synchrony as the target button is flashed. Two data processing procedures, specifically support vector machine (SVM) classification and waveform detection, are combined to detect eye blinks. During detection, we simultaneously feed the feature vectors extracted from the ongoing EOG signal into the SVM classification and waveform detection modules. Decisions are made based on the results of the SVM classification and waveform detection. Three online experiments were conducted with eight healthy subjects. We achieved an average accuracy of 94.4% and a response time of 4.14 s for selecting a character in synchronous mode, as well as an average accuracy of 93.43% and a false positive rate of 0.03/min in the idle state in asynchronous mode. The experimental results, therefore, demonstrated the effectiveness of this single-channel EOG-based speller.
PDF
