arXiv subjects

Pawandeep Kaur Betz

Publications and source records attributed to Pawandeep Kaur Betz.

3 recordsLinked to original sources

arXiv2025

Integrating Knowledge Graphs and Visualization Dashboards for Advance Data Discovery in VESA

The increasing complexity and scale of scientific datasets demand advanced tools for efficient discovery and exploration. Traditional search systems often fall short in addressing the multidimensional nature of data and their intricate relationships, limiting their utility for researchers. This paper introduces the Knowledge Graph Based Visualization Search Application (VESA), which reshapes the process of data discovery by leveraging knowledge graph technology to establish meaningful connections and employing a visualization dashboard to enable multidimensional exploration. A software prototype is developed, showcasing our use case of connecting two Earth System Science repositories via a knowledge graph backend and visualization dashboard at the frontend. The framework's effectiveness was assessed against guidelines derived from a comprehensive literature review and further validated through an online user study. The evaluation revealed positive reception, highlighting VESA's low learning curve, ease of use, and potential to enhance data discovery workflows.

cs.DB↗

arXiv2024

Enhancing Uncertainty Communication in Time Series Predictions: Insights and Recommendations

As the world increasingly relies on mathematical models for forecasts in different areas, effective communication of uncertainty in time series predictions is important for informed decision making. This study explores how users estimate probabilistic uncertainty in time series predictions under different variants of line charts depicting uncertainty. It examines the role of individual characteristics and the influence of user-reported metrics on uncertainty estimations. By addressing these aspects, this paper aims to enhance the understanding of uncertainty visualization and for improving communication in time series forecast visualizations and the design of prediction data dashboards.As the world increasingly relies on mathematical models for forecasts in different areas, effective communication of uncertainty in time series predictions is important for informed decision making. This study explores how users estimate probabilistic uncertainty in time series predictions under different variants of line charts depicting uncertainty. It examines the role of individual characteristics and the influence of user-reported metrics on uncertainty estimations. By addressing these aspects, this paper aims to enhance the understanding of uncertainty visualization and for improving communication in time series forecast visualizations and the design of prediction data dashboards.

cs.HC↗

arXiv2023

ESID: Exploring the Design and Development of a Visual Analytics Tool for Epidemiological Emergencies

Visual analytics tools can help illustrate the spread of infectious diseases and enable informed decisions on epidemiological and public health issues. To create visualisation tools that are intuitive, easy to use, and effective in communicating information, continued research and development focusing on user-centric and methodological design models is extremely important. As a contribution to this topic, this paper presents the design and development process of the visual analytics application ESID (Epidemiological Scenarios for Infectious Diseases). ESID is a visual analytics tool aimed at projecting the future developments of infectious disease spread using reported and simulated data based on sound mathematical-epidemiological models. The development process involved a collaborative and participatory design approach with project partners from diverse scientific fields. The findings from these studies, along with the guidelines derived from them, played a pivotal role in shaping the visualisation tool.

cs.HC↗