Spacewalker: Traversing Representation Spaces for Fast Interactive Exploration and Annotation of Unstructured Data
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Date
2025
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
In industries such as healthcare, finance, and manufacturing, analysis of unstructured textual data presents significant challenges for analysis and decision making. Uncovering patterns within large-scale corpora and understanding their semantic impact is critical, but depends on domain experts or resource-intensive manual reviews. In response, we introduce Spacewalker, an interactive tool designed to analyze, explore, and annotate data across multiple modalities. It allows users to extract data representations, visualize them in low-dimensional spaces and traverse large datasets either exploratorily or by querying regions of interest. We evaluated Spacewalker through extensive studies, assessing its efficacy in improving data integrity verification and annotation. We show that Spacewalker reduces time and effort compared to traditional methods. The code of this work is publicly available on https://github.com/TIO-IKIM/Spacewalker.
Description
CCS Concepts: Information systems → Document representation; Human-centered computing → Visualization systems and tools
@inproceedings{10.2312:mlvis.20251155,
booktitle = {Machine Learning Methods in Visualisation for Big Data},
editor = {Archambault, Daniel and Nabney, Ian and Peltonen, Jaakko},
title = {{Spacewalker: Traversing Representation Spaces for Fast Interactive Exploration and Annotation of Unstructured Data}},
author = {Heine, Lukas and Hörst, Fabian and Fragemann, Jana and Luijten, Gijs and Egger, Jan and Bahnsen, Fin Hendrik and Sarfraz, M. Saquib and Kleesiek, Jens and Seibold, Constantin},
year = {2025},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-288-2},
DOI = {10.2312/mlvis.20251155}
}