Use data aliasing to work with non-conforming data -- when the provided data has different columns names or different value ids for the same underlying thing. Example include:
- A lab provides assay data which uses different participant ids than those used in your study. (Using different participant ids is often desirable and intentional, as it provides a layer of PHI protection for the lab and the study.)
- Excel files have different column names for the same data, for example some files have the column "Immune Rating" and other have the column "Immune Score".
- The source files have a variety of names for the same visit id, for example, "M1", "Milestone #1", and "Visit 1".
In all of these cases, the system provides a way to import these non-conforming datasets into one standard dataset. See the following topics for details on handing these cases of non-conforming: