Reusing Geospatial Data of Invasive Alien Insect Species From the Literature: Significance, Challenges, and Potential.

Authors

Shuhao Tan, Yiqi Xu, Qiaoling Lin, Muzi Ge, Yuting Wu, Jianshi Jin

Published in

Integrative zoology. Aug 04, 2026. Epub Aug 04, 2026.

Abstract

In invasion biology, geospatial data are fundamental for analyzing invasion dynamics. Focusing on invasive alien insect species (IAIS) dispersal, this study assesses the role and reuse potential of published geospatial data via a bibliometric analysis of literature from 2016 to 2026. By examining all IAIS-related publications, we found 1032 articles (59.0% of the total) that presented geospatial data in thematic maps, forming a substantial repository. We analyzed these publications across four dimensions-visual representation, spatial scale, data reuse, and data accessibility-revealing point-based data (80.1%) as most common, regional-scale analysis (54.9%) predominant, high adoption of geospatial data reuse (74.7%), and a majority (51.0%) lacking downloadable source data. To evaluate data reuse value, we explored integrating datasets across regions, time periods, and species. Such integration can overcome limitations of individual studies, often with constrained spatial coverage, short temporal scales, and narrow taxonomic focus. However, the significant absence of raw data in publications hinders the reuse of geospatial data. We therefore propose developing computational techniques to extract quantitative data directly from thematic map figures in publications. We addressed key challenges and potential solutions in the data extraction workflow, including georeferencing, thematic feature recognition, and thematic layer separation. We anticipate that overcoming these data extraction challenges will transform static map images into dynamic, computable knowledge, paving the way for data sharing and enhanced global IAIS monitoring and governance.

PMID:
42550579
Bibliographic data and abstract were imported from PubMed on 04 Aug 2026.

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