Consultation participation and their own register declarations, side by side. Counts, not judgments — participation is not influence.
Counts here are a floor, never a total: they cover the 583 consultation files tracked so far (42,224 submissions, mostly 2025–26), so an organization's real filing history is larger, not smaller.
Register facts self-declared (snapshot 2 Sept 2026); cost bands are floors. Shared files are shared attention, not evidence of coordination.
What each said, in their own words
Their opening passages on the files they share, verbatim and in filing order. We do not summarize, compare, or characterize positions — read them at source.
Please find attached our detailed feedback. Summary: The development of high-value datasets (HVDs) in specific fields will have major positive consequences for society. Such datasets offer significant potential for citizens and businesses, to help address societal challenges and to develop innovative services and products.
Given the importance of procurement datasets and the growing efforts across EU jurisdictions to adopt open data contracting standards (OCDS), in particular but not only in relation to the new rules on eForms (Commission Implementing Regulation (EU) 2019/1780 of 23 September 2019), it is a missed opportunity for the specific list of statistical high-value datasets (HVD) not to include procurement statistics.
The proposed Regulation on foreign subsidies distorting the internal market (RFSDIT) is both (1) undesirable and (2) problematic, in particular as it concerns the investigation of foreign subsidies linked to public procurement procedures. The following is limited to chapter 4. 1.
DIGITALEUROPE welcomes efforts by the European Commission to address the distortion caused by foreign subsidies in the Single Market, which may provide certain businesses an unfair competitive advantage in the global market. Any new instrument should be focused on identifying, assessing, and mitigating distortion caused specifically by subsidies while remaining proportionate, fair and non-discriminatory.
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