A core design choice of ETER is to rely on, as far as possible, existing methodologies, specifically from official statistics, for the definition of variables and indicators. This allows for the reusing of data collected in the framework of educational and R&D statistics for ETER and guarantees the possibility of comparison between ETER and international statistics.

More specifically, the definition of ETER variables largely builds on the UNESCOUIS/OECD/EUROSTAT (UOE) manual for the data collection on education. ETER definitions concerning students and degrees are based on the UOE with few adaptations related to different statistical units. ETER definitions concerning HEI personnel also largely comply with UOE definitions with some adaptation to te specific context of higher education (such as the explicit inclusion of educational personnel).

As for financial data, ETER has its own definitions since the unit of analysis is different (national budgets vs institutions). As for the definition of Research & Development (R&D) expenditures, ETER follows definitions and rules in the Frascati Manual 2015 also adopted by the EUROSTAT for R&D statistics.

Finally, ETER uses its own definitions and methodologies for variables of non-statistical nature (most institutional descriptors and geographical information) and variables from other sources (credit mobility, quality assurance).

Notably, even if definitions might be the same as adopted in UOE, different statistical units might imply different counting methods. For example, in UOE students enrolled at multiple institutions (for example, in the framework of joint programs) are counted only once, while in ETER they will be counted in each individual institution. Accordingly, the sum of students enrolled in ETER HEIs might exceed national totals in the UOE data collection. The focus on the institutional level might generate other discrepancies, such as institutions enrolling students but not awarding degrees.