Ethical conceptual replication of visualization research considering sources of methodological bias and practical significance

General design principles for visualization have been relatively well-established based on a combination of cognitive and perceptual theory and empirical evaluations over the past 20 years. To determine how these principles hold up across use contexts and end-users, I argue that we should emphasize conceptual replication focused on determining practical significance and reducing methodological biases. This shift in thinking aims to determine how design principles interact with methodological approaches, laying the groundwork for visualization meta-science.Comment: Submitted to contribute to the discussion at VisPsych2020, a workshop at the IEEE Visualization Conference 2020 Salt Lake City. For associated code, see https://osf.io/ebwx9

Malware in the Future? Forecasting of Analyst Detection of Cyber Events

There have been extensive efforts in government, academia, and industry to anticipate, forecast, and mitigate cyber attacks. A common approach is time-series forecasting of cyber attacks based on data from network telescopes, honeypots, and automated intrusion detection/prevention systems. This research has uncovered key insights such as systematicity in cyber attacks. Here, we propose an alternate perspective of this problem by performing forecasting of attacks that are analyst-detected and -verified occurrences of malware. We call these instances of malware cyber event data. Specifically, our dataset was analyst-detected incidents from a large operational Computer Security Service Provider (CSSP) for the U.S. Department of Defense, which rarely relies only on automated systems. Our data set consists of weekly counts of cyber events over approximately seven years. Since all cyber events were validated by analysts, our dataset is unlikely to have false positives which are often endemic in other sources of data. Further, the higher-quality data could be used for a number for resource allocation, estimation of security resources, and the development of effective risk-management strategies. We used a Bayesian State Space Model for forecasting and found that events one week ahead could be predicted. To quantify bursts, we used a Markov model. Our findings of systematicity in analyst-detected cyber attacks are consistent with previous work using other sources. The advanced information provided by a forecast may help with threat awareness by providing a probable value and range for future cyber events one week ahead. Other potential applications for cyber event forecasting include proactive allocation of resources and capabilities for cyber defense (e.g., analyst staffing and sensor configuration) in CSSPs. Enhanced threat awareness may improve cybersecurity.Comment: Revised version resubmitted to journa

How does your viewing perspective matter for decision-making with flood risk maps?*

The globally increasing frequency of flood events highlights the importance of effective flood risk communication. The influence of the viewing perspective of mapped flood events on human risk perception has not yet been a research focus of the geovisualization community. This empirical study aims to fill this gap by investigating how the viewing perspective of flood risk maps, that is, 2D orthographic vs. 2.5D oblique views, influence human flood risk perception and decision-making. Results on how viewing perspective might influence measured risk perception are in line with prior inconclusive research on the utility and usability of adding a third viewing dimension on static maps. Unlike prior research would have suggested, we find that the individual risk attitude of our participants had no direct influence on their risk ratings in the context of this study. With additional empirical evidence on how static 2D and oblique 2.5D hazard maps might influence the public’s risk perception and decision-making, we hope to further inform policy and decision makers on the critical importance of well-designed cartographic displays for effective and efficient hazard and risk communication. We also provide an open-source code repository for making reproducible experiments with our static maps

Designing mobile spatial navigation systems from the user’s perspective: an interdisciplinary review

Navigation systems have become increasingly available and more complex over the past few decades as maps have changed from largely static visual and paper-based representations to interactive and multimodal computerized systems. In this introductory article to the Special Issue on Human-computer Interaction, Geographic Information, and Navigation, we review literature across a variety of fields to generate nine design principles to guide future research and development of navigation systems. Specifically, we suggest making mobile navigation systems more accessible and multimodal, which will make the systems more inclusive and usable for all types of users. We also introduce the research articles contributed to the present special issue and suggest future research directions to empirically evaluate emerging and untested features of user-adapted and context-aware mobile navigation systems

Leveraging Different Visual Designs for Communication of Severe Weather Events and their Uncertainty

In this work, we present several interactive visual designs for mobile visualization of severe weather events for the communication of weather hazards, their risks, uncertainty, and recommended actions. Our approach is based on previous work on uncertainty visualization [5], cognitive science [6], and decision sciences for risk management [3, 4]. We propose six configurations that vary the ratio of text vs graphics used in the visual display, and the interaction workflow needed for a non-expert user to make an informed decision and effective actions. Our goal is to test how efficient these configurations are and to what degree they are suitable to communicate weather hazards, associated uncertainty, risk, and recommended actions to non-experts. Future steps include two cycle of evaluations, consisting of a first pilot to rapidly test the prototype with a small number of participants, collect actionable insights, and incorporate potential improvements. In a second user study, we will perform a crowd-sourced extensive evaluation of the visualization prototypes

Ethical conceptual replication of visualization research considering sources of methodological bias and practical significance

General design principles for visualization have been relatively well-established based on a combination of cognitive and perceptual theory and empirical evaluations over the past 20 years. To determine how these principles hold up across use contexts and end-users, I argue that we should emphasize conceptual replication focused on determining practical significance and reducing methodological biases. This shift in thinking aims to determine how design principles interact with methodological approaches, laying the groundwork for visualization meta-science

Non-expert interpretations of hurricane forecast uncertainty visualizations

Data for Ruginski et al. (2016) paper in special issue of Spatial Cognition and Computation on Visually-supported reasoning with uncertaint