Data spaces are a relatively recent concept for a trusted and secure distributed data ecosystem through which to exchange resources in the Web. Several different efforts are currently being made to define guidance toward data space implementation, with some initiatives and organizations providing solutions and standards that address interoperability and good data exchange practices, especially in the domain of geospatial information. Geospatial Use Cases often require effective and high-quality data sharing between systems dealing with different aspects of real-world objects. However, the different solutions proposed do not yet provide a common interoperability framework with mature implementation options. This gap between concept and implementation risks confusing users and developers, instead of reciprocally strengthening the respective data spaces' infrastructures and capabilities. This paper reviews and compares some of the proposed solutions, providing mapping and integration of these blueprints to available interoperability standards. This concrete mapping is designed to support effective practical implementation of data spaces, and to guide future solutions developments.