A Cognitive Task Analysis (CTA) was performed to investigate the workflow, decision processes, and cognitive demands of information assurance (IA) analysts responsible for defending against attacks on critical computer networks. We interviewed observed 41 IA various aspects cyber defense in seven organizations within US Department Defense (DOD) industry. Results are presented as workflows analytical process attribute tables including analyst goals, decisions, required knowledge, obstacles...

Existing research on immersive analytics to support the sensemaking process focuses single-session tasks. However, in wild, can take days or months complete. In order understand full benefits of analytic systems, we need how systems provide flexibility for dynamic nature process. our work, build upon an existing system - Immersive Space Think, evaluate tasks over time. We conducted a user study with eight participants three separate analysis sessions each. found significant differences...

The analysis of vast amounts network data for monitoring and safeguarding a core pillar the internet, root DNS, is an enormous challenge. Understanding distribution queries received by how those change over time, in intuitive manner sought. Traditional query performed packet packet, lacking global, temporal, visual coherence, obscuring latent trends clusters. Our approach leverages pattern recognition computational power deep learning with 2D 3D rendering techniques quick easy interpretation...

Article Free Access Share on Visual programming: the outlook from academia and industry Authors: K. N. Whitley Department of Computer Science, Vanderbilt University, Box 1679, Station B, Nashville, TN TNView Profile , Alan F. Blackwell MRC Applied Psychology Unit, 15 Chaucer Road, Cambridge, CB2 2EF, UK UKView Authors Info & Claims ESP '97: Papers presented at seventh workshop Empirical studies programmersOctober 1997 Pages 180–208https://doi.org/10.1145/266399.266415Published:01 October...

Network planners consider many factors in designing an indoor signal space to ensure a healthy network. These include material attenuation, channel overlap, peak bandwidth demand, and even humidity. Unfortunately, the current network planning software often fails account for these adequately. Further, state-of-the-art either uses few samples or limits itself single router. WaveRider is mixed reality application immersively viewing multiple routers their strengths spaces aid analysis. Our...

Deep learning has emerged as a powerful tool for feature-driven labeling of datasets. However, it to be effective, requires large and finely labeled training dataset. Precisely dataset is expensive, time-consuming, error prone. In this article, we present visually driven deep-learning approach that starts with coarsely iteratively refines the through intuitive interactions leverage latent structures Our can used (a) alleviate burden intensive manual captures fine nuances in high-dimensional...

The computational notebook serves as a versatile tool for data analysis. However, its conventional user interface falls short of keeping pace with the ever-growing data-related tasks, signaling need novel approaches. With rapid development interaction techniques and computing environments, there is growing interest in integrating emerging technologies data-driven workflows. Virtual reality, particular, has demonstrated potential interactive visualizations. In this work, we aimed to...

The computational notebook serves as a versatile tool for data analysis. However, its conventional user interface falls short of keeping pace with the ever-growing data-related tasks, signaling need novel approaches. With rapid development interaction techniques and computing environments, there is growing interest in integrating emerging technologies data-driven workflows. Virtual reality, particular, has demonstrated potential interactive visualizations. In this work, we aimed to...

Existing research on sensemaking in immersive analytics systems primarily focuses understanding how users complete analysis within these with quantitative and qualitative datasets. However, user studies mainly concentrate styles methodologies from a predominantly novice study population. While this approach provides excellent initial insights into what may do IA systems, it fails to address professionals utilize an analytic system for tasks. In our work, we build upon existing concept -...

Large Language Models (LLMs) have been widely applied in summarization due to their speedy and high-quality text generation. Summarization for sensemaking involves information compression insight extraction. Human guidance tasks can prioritize cluster relevant LLMs. However, users must translate cognitive thinking into natural language communicate with Can we use more readable operable visual representations guide the process sensemaking? Therefore, propose introducing an intermediate...

Eye gaze patterns vary based on reading purpose and complexity, can provide insights into a reader's perception of the content. We hypothesize that during complex sensemaking task with many text-based documents, we will be able to use eye-tracking data predict importance documents words, which could basis for intelligent suggestions made by system an analyst. introduce novel eye-gaze metric called 'GazeScore' predicts analyst's relevance each document word when they perform task. conducted...

As immersive analytics research becomes more popular, user studies have been aimed at evaluating the strategies and layouts of users' sensemaking during a single focused analysis task. However, approaches to are likely change as users become familiar/proficient with tool. In our work, we build upon an existing approach-Immersive Space Think-to understand how schemas for across multiple tasks. We conducted study 14 participants who completed three different tasks separate sessions. found...

In this paper, we show how volume rendering with a Programmable Transfer Function can be used for the effective and comprehensible visualization of WiFi signals. A traditional transfer function uses low-dimensional lookup table to map volumetric scalar field color opacity. present concept Function. We then generalizing lookup-based functions Functions enables us leverage view-dependent real-time attributes depict data variations surfaces low high-frequency components. Our facilitate...