An approach to converting weakly-structured data into thematic geospatial layers

<jats:p>The authors discuss developing an end-to-end methodology for converting weakly-structured spatial data into standardized geospatial products. The relevance of the study is driven by the problem of integrating heterogeneous information characterized by weak structural arrangement, heterogeneous coordinate formats, and polymorphic attribute characteristics. A comprehensive approach based on scripted processing tools is proposed; it includes formalization of a mathematical apparatus based on set theory, creation of data parsing and normalization algorithms, and constructing a multi-stage technological pipeline. Specialized algorithms were developed for attribute transliteration, territorial data aggregation, parsing of multi-format coordinates, and integration with reference geospatial layers. The method was implemented as a Python-based software complex and tested during creation of a web GIS for monitoring the geomagnetic situation. The solution ensures automation of processing workflows, elimination of subjective errors, and generation of ready-to-use GeoJSON layers suitable for analysis and visualization in modern GIS environments</jats:p>