The European Union (EU) Water Framework Directive depends, for effective implementation, on Member States (MSs) agreeing to a concept of the unimpacted "reference" state, which will then provide the "expected" value in Ecological Quality Ratio (EQR) calculations. Reference assemblages of organism groups will, in turn, vary, due to geological, hydrological, climatic, physicochemical and biological factors. Member States tackle this by establishing "types" which share common characteristics. However, for the purposes of ensuring consistent application, broad transboundary types were also established within five Geographical Intercalibration Groups (GIGs, referred to here as "regions") as part of the EU's intercalibration exercise. In this paper, we evaluate these types using river diatom assemblages and also provide reference threshold values for two common metrics used in pan-European diatom assessments. A database was assembled, representing 14 EU Member States from Ireland and Portugal in the West, to Estonia and Cyprus in the East, in order to explore biogeographical patterns in assemblages unaffected by anthropogenic pressures. Multivariate analyses were used to examine this pattern and its relationship with geographic, typological and abiotic parameters. After taxonomic harmonisation, NMDS ordination of samples indicated weak differences in assemblage composition among regions. ANOSIM analyses, in turn, indicated that MS was the best factor to group similar samples whereas alkalinity, recognised as the primary environmental variable structuring diatom communities, although significant, explained less variability in the dataset. This, we believe, reflects the importance of methodological factors other than taxonomy (e.g. counting protocol, sample season) that may be constant within a MS but which vary between MSs. When two diatom metrics, the TI and IPS, were applied to the data, differences in the distribution of the metric scores between MS were generally not statistically significant even though some differences between regions were apparent. A trend of increasing values of TI (decreasing values of IPS) was observed in the sequence: Nordic <Alpine <Mediterranean <Central-Baltic <Eastern Continental regions. Additionally, some differences were observed among types within the Mediterranean and Nordic regions, though not for other regions. The data used in this exercise provides us with a region and, in some cases, a type specific benchmark dataset against which national reference data can be compared.