A comprehensive framework to enhance communication between researchers, higher education institutions (HEIs) and funders is proposed for assessing the FAIRness of research results. The proposed enhanced Data Management Plans (DMPs) include: (1) Specific, Measurable, Achievable, Relevant, and Time-bound (SMART) metrics, (2) Research Data Life Cycle (RDLC) management, (3) Findable, Accessible, Interoperable, and Reusable (FAIR) principles, and (4) Behaviour Driven Development (BDD) and Gherkin syntax. 

SMART metrics provide a structured approach for planning, developing, and evaluating research outcomes, based on objective-dependent variables. 

RDLC maps the assets derived from SMART metrics to assess their FAIRness, ensuring research outcomes are comprehensible to machines through enriched metadata. 

The FAIR principles are operationalised in this context by enhancing the findability, accessibility, interoperability and reusability as requirements written in Gherkin syntax, following SMART metrics. 

Finally, BDD facilitates their creation, updating and evaluation using asset-dependent scenarios, ensuring that all metrics are clear, actionable, and testable. 

This holistic framework supports the automation, interoperability and streamlining of research data management, promoting replicability in the short term and reproducibility in the long term of research results.

Future efforts will focus on applications across different domains, i.e., automating FAIR assessments for datasets, software, and digital models, while evaluating its direct impact on improving transparency and traceability for research data management.