ChatKG: Visualizing Temporal Patterns as Knowledge Graph
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Date
2023
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
Line-chart visualizations of temporal data enable users to identify interesting patterns for the user to inquire about. Using oracles, such as chat AIs, Visual Analytic tools can automatically uncover explicit knowledge related information to said patterns. Yet, visualizing the association of data, patterns, and knowledge is not straightforward. In this paper, we present ChatKG, a novel visualization strategy that allows exploratory data analysis of a Knowledge Graph which associates a dataset of temporal sequences, the patterns found in each sequence, the temporal overlap between patterns, and related explicit knowledge to each given pattern. We exemplify and informally evaluate ChatKG by analyzing the world's life expectancy. For this, we implement an oracle that automatically extracts relevant or interesting patterns, inquires chatGPT for related information, and populates the Knowledge Graph which is visualized. Our tests and an interview conducted showed that ChatKG is well suited for temporal analysis of temporal patterns and their related knowledge when applied to history studies.
Description
CCS Concepts: Human-centered computing -> Visual analytics; Computing methodologies -> Knowledge representation and reasoning
@inproceedings{10.2312:eurova.20231090,
booktitle = {EuroVis Workshop on Visual Analytics (EuroVA)},
editor = {Angelini, Marco and El-Assady, Mennatallah},
title = {{ChatKG: Visualizing Temporal Patterns as Knowledge Graph}},
author = {Christino, Leonardo and Paulovich, Fernando V.},
year = {2023},
publisher = {The Eurographics Association},
ISSN = {2664-4487},
ISBN = {978-3-03868-222-6},
DOI = {10.2312/eurova.20231090}
}