# 6.6. Data governance To clearly identify the responsibilities of each user, you will find below a responsibility matrix (RACI - Responsible, Accountable, Consulted, Informed). ## Definitions: **Responsible (R):** The role that is responsible for executing the task / activity. **Accountable (A):** The role that is accountable for the execution of the activity its correct execution and completeness. The person accountable for an activity is not necessarily the one responsible for executing it. **Consulted (C):** A role whose opinion is sought for the given activity. **Informed (I):** A role that is informed about the activity, but does not play an active part in it. ## Matrix:

	MyConnectivity	MyConnectivity	Organisation User	Organisation User	Organisation User	Organisation User
Activity / Role	Application Administration	Analyst	Organisation Administrator	Editor	Approver	Viewer
Produce Data	C	I	C	R	A	I
Data quality of data produced by the organisation (approve / reject)	R, A	I	R	R	A	I
Undo Approvals	R, A	I	R, A	I	C	I
General System reliability	R, A	C	I	I	I	I
Query Data Subsets	I	I	I	I	I	R, A
Analyse Data	I	R,A	I	I	I	I

## Additional clarifications concerning data quality ### Editor Editors are responsible for producing high quality VC data. ### Approvers Approvers are accountable for the quality of the VC data produced by their organisation’s Editors. ### Organisation Administrators Organisation administrators are responsible for undoing actions data approvals done by mistake by the Approver. This action is done upon request from the Approver. ### Application Administrators / MyConnectivity The application administrators / MyConnectivity are responsible for performing manual validation tasks to ensure the data quality. These can be tasks linked with automatic processes (e.g. address ingestion process, is not able to validate an existing address), or manual period data validations. The application administrators / MyConnectivity are responsible for the overall data quality of the system, for the automatic data quality processes as well as for the periodic auditing of the overall data quality.