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Geovicla: Automated Classification of Interactive Web-Based Geovisualizations

Authors Phil Hüffer , Auriol Degbelo , Benjamin Risse

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Subject Classification

ACM Subject Classification
  • Human-centered computing → Geographic visualization
  • Information systems → Web searching and information discovery
  • Information systems → Specialized information retrieval
Keywords
  • spatial information search
  • geovisualization search
  • findable interactive geovisualization
  • webpage classification

Metrics

Abstract

The exponential growth of interactive geovisualizations on the Web has underscored the need for automated techniques to enhance their findability. In this paper, we present the Geovicla dataset (2.5K instances), constructed through the harvesting and manual labelling of webpages from a broad range of domains. The webpages are categorized into three groups: "interactive visualisation", "interactive geovisualisation" and "`no interactive visualisation". Using this dataset, we compared three approaches for interactive (geo)visualization classification: (i) a heuristic-based approach (i.e. using manually derived rules), (ii) a feature-engineering approach (i.e. hand-crafted feature vectors combined with machine learning classifiers) and (iii) an embedding-based approach (i.e. automatically generated large language model (LLM) embeddings with machine learning classifiers). The results indicate that LLM embeddings, when used in conjunction with a multilayer perceptron, form a promising combination, achieving up to 74% accuracy for multiclass classification and 75% for binary classification. The dataset and the insights gained from our empirical comparison offer valuable resources for GIScience researchers aiming to enhance the discoverability of interactive geovisualizations.

Cite As Get BibTex

Phil Hüffer, Auriol Degbelo, and Benjamin Risse. Geovicla: Automated Classification of Interactive Web-Based Geovisualizations. In 13th International Conference on Geographic Information Science (GIScience 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 346, pp. 10:1-10:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025) https://doi.org/10.4230/LIPIcs.GIScience.2025.10

Author Details

Phil Hüffer
  • Institute for Geoinformatics, University of Münster, Germany
Auriol Degbelo
  • Chair of Geoinformatics, TU Dresden, Germany
Benjamin Risse
  • Institute for Geoinformatics, University of Münster, Germany

Funding

  • Degbelo, Auriol: Auriol Degbelo is funded by the German Research Foundation through the project NFDI4Earth (DFG project no. 460036893, https://www.nfdi4earth.de/) within the German National Research Data Infrastructure (NFDI, https://www.nfdi.de/).

Supplementary Materials

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