A proposed FAIR approach for disseminating geospatial information system maps

Area of Science:

• Geospatial Information Science
• Data Management
• Scientific Computing

Background:

• Public deposition of geospatial information system (GIS) datasets often lacks standardized metadata, hindering data discoverability and reuse.
• Existing data formats and proprietary systems can create barriers to interoperability and accessibility.
• The FAIR principles (Findable, Accessible, Interoperable, Reusable) are crucial for effective scientific data sharing.

Purpose of the Study:

• To introduce a draft Minimum Information About Geospatial Information System (MIAGIS) standard for public GIS dataset deposition.
• To develop a supporting Python package (miagis) for automating metadata creation and extraction.
• To enhance the findability, accessibility, interoperability, and reusability of GIS data.

Main Methods:

• Development of a draft MIAGIS standard including a directory structure and a minimum JSON metadata format.
• Creation of the miagis Python package to facilitate MIAGIS metadata file generation.
• Implementation of metadata extraction capabilities from Esri JSON, GEOJSON, and user-specified JSON formats within the miagis package.
• Demonstration of the MIAGIS standard and package using two example ArcGIS-generated map depositions.

Main Results:

• A draft MIAGIS standard has been proposed to standardize GIS dataset metadata.
• The miagis Python package successfully automates the creation of MIAGIS-compliant metadata.
• Metadata extraction from common GIS data formats is supported, simplifying the deposition process.

Conclusions:

• The draft MIAGIS standard and miagis Python package provide a framework for FAIRer public GIS data deposition.
• These tools aim to encourage the establishment of a GIS standards group for broader community adoption.
• The initiative supports the development of a future public repository for GIS datasets.