Best practices for spatial language data harmonization, sharing and map creation-A case study of Uralic

Area of Science:

• Digital Linguistics
• Geospatial Data Analysis
• Computational Social Science

Background:

• Lack of comprehensive geographical language distribution databases hinders linguistic spatiality studies and public outreach.
• Existing language distribution data is often fragmented, presented in non-digital formats like printed maps or text.
• Digitizing and harmonizing this data is crucial for advanced spatial analysis and understanding language diversity.

Purpose of the Study:

• To establish best practices for creating and sharing digital spatial language data.
• To compile and harmonize geospatial data for Uralic language distributions as a case study.
• To make extensive, harmonized linguistic distribution datasets and visualizations freely accessible.

Main Methods:

• Collecting and harmonizing existing linguistic distribution data.
• Digitizing information into geospatial data with location, time, and other parameters.
• Collaborating with language experts to refine distribution data and create state-of-the-art maps.

Main Results:

• Development of best practices for digital spatial language data creation and sharing.
• Compilation of a comprehensive, harmonized geospatial database of Uralic language distributions.
• Creation of detailed map visualizations of Uralic language distributions.

Conclusions:

• The presented methodology provides a framework for building digital spatial language databases.
• Freely available Uralic language distribution data facilitates further research on language spatiality and diversity.
• Digital spatial data enhances the study of linguistic changes and their correlation with other factors.