Data ethics policies are defined and approved for the whole organization; communication and training reinforce the Code of Data Ethics; processes review how data is acquired, accessed and used, and what data-driven decisions produce, from an ethical standpoint; processes exist to report concerns and to resolve issues raised; milestones, metrics and measures quantify adherence to the code; and all of this runs as business as usual. Good practice embeds provenance in metadata, places tollgates in data management processes to check adherence, collects consent metadata covering legal consent and perceived consent alike, and treats accountability for ethics as every data consumer's responsibility.
The graph holds this control, the 0 it maps to, and the evidence behind each claim, over MCP and REST.