Data interoperability is key to the FAIR principles, yet can be challenging to put into practice. This document provides guidance on practices involved in achieving data interoperability, more specifically, practices around data citation, persistent identifiers (PIDs), semantic resources, and metadata. All of these create a data interoperability framework and are important building blocks of a FAIR ecosystem. The purpose of such a framework is to set some specific requirements for the digital objects that it will be applied to. Generally these include that the digital object/data need to be accompanied by standardised metadata for it to be cited and be unambiguously identified, using a persistent identifier. The metadata should also describe the object according to a community-endorsed vocabulary, richly enough for it to be understandable and reusable by anyone in that community. In addition, the data files that comprise the object need to be represented in common and open formats. ACME-FAIR is a 7-part guide developed in the FAIRsFAIR project, whose main purpose is to help managers of Research Data Management and related professional services to self-assess how they are enabling researchers, and the professional staff who support them, to put the FAIR data principles into practice (for short we refer to this as ���FAIR-enabling practice���). This part addresses the key issue of Defining Data Interoperability Frameworks. Please give us your comments in any of the ways detailed on p.5.