We recommend the use of some terms from Safe Haven Provenance ontology for documenting review processes.
e.g. https://w3id.org/shp#ValidationCheck
heck of project activities and entities against project requirements and permissions. This involves one or more data Analysts who are involved in data validation checks after the Lead Analyst has built a cohort, extracted and pseudonymised data and/or linked the datasets for a research project. Validation checks concentrate on technical aspects,whether the coding is correct and that datasets match the Data Linkage Plan and Data Specification File. It generates a validation check report.
e.g. https://w3id.org/shp#SignOff
Senior member of staff reviewed the validated datasets for data integrity and data pseudonymisation. Data signoff has more of an emphasis on validity of extraction, data validation process and aligns with research project ethical permissions. This is a key step prior to data transferring between different servers/environments (e.g. NHS data moving onto University servers, or data on University servers being released to a project folder for a researcher to access.
If these are interpreted strictly, they may not cover use of automated tools (but tool-assisted manual checks are probably ok) - worth thinking about when considering SACRO and so on.
We recommend the use of some terms from Safe Haven Provenance ontology for documenting review processes.
e.g. https://w3id.org/shp#ValidationCheck
e.g. https://w3id.org/shp#SignOff
If these are interpreted strictly, they may not cover use of automated tools (but tool-assisted manual checks are probably ok) - worth thinking about when considering SACRO and so on.