Ensuring seamless GIS data transfers requires a combination of standardization, automation and quality control. I personally prioritize the use of widely accepted formats such as GeoJSON and Shapefiles to maintain compatibility. Additionally, I find it essential to validate coordinate reference systems before any transfer, as inconsistencies in projections can lead to data integrity issues. From my experience, automating data workflows significantly improves accuracy and reduces errors. Tools like Python libraries such as GeoPandas help streamline conversions, optimize file sizes, and ensure metadata consistency. By combining these practices, GIS data transfers become more efficient and adaptable to evolving project requirements.

At Tri-Global, we employ the power of the Feature Manipulation Engine (FME) by Safe Software to ensure safe and efficient data transfer between multiple platforms. FME's three key capabilities help us accomplish this for our wide variety of clients across the electric, gas, water, forestry, and natural resources industries: support for over 450 formats and systems; built-in data validation tools; and the ability to map custom schemas between formats. This is a powerful tool that has also enabled us to define custom workbenches for exchanges between complex and custom datums that are automatically determined for our clients by a variety of factors.

The best communication is to use the same language, standarize data formats from start is the best way, not only platforms are involved in data transfer but also users, shapefiles base should always be a must, then you can use FME for users that do not require/have a complete knowledge of all the features.

To transfer data across different platforms, it is necessary to ensure that the data is of high quality and meets international standards. It is important to document data and metadata quality standards.