Interoperability means that both humans and machines can retrieve and read your (meta)data. To allow this, you should ensure that the data can be exchanged and used across different applications and systems.
The FAIR principles suggest the following steps to make research data interoperable.
I1: (Meta)data use a formal, accessible, shared and broadly applicable language for knowledge representation
I2: (Meta)data use vocabularies that follow the FAIR principles
I3: (Meta)data include qualified references to other (meta)data
Visit GoFAIR’s website to read about the principles in detail.
Standard ontologies, controlled vocabularies and metadata standards: In some research communities, vocabularies and ontologies are clearly defined. To enhance the interoperability of your research data as well as the chances of both humans and computers being able to read the data, you are advised to use standard ontologies, controlled vocabularies and a recognised standard for metadata like the DataCite Metadata Schema.
Technical interoperability: You should allow (meta)data to be exchanged and used across different applications and systems, for instance by making use of open file formats such as .csv or .txt. This is so that you and other researchers can exchange and interpret each other’s research data and the metadata.