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Consult the tooltips in the header rows for more information about what is expected.

Tip

It is highly recommended you delete any columns from the template that are not needed. This eliminates potential confusion and makes the sheets much less unwieldy.


Rules and guidelines

  • You must always enter the Organization to which the resource is associated, either by name or by URI

    Tip
    It is best to use the Sweet to add the Organization (e.g. lab) to which these resources are associated, and then reference this name or URI in the files.
  • References in the primary file, either to resources represented in a secondary file or resources in the repository, need to use the exact label (ignoring case) for the correct linkage to occur
  • If there is more than one value for a given column, enter values separated by ; (semicolon). Conversely, check your input file for the presence of ; in values that are not meant to be split and substitute for a different character.
  • Every resource (primary or secondary) needs to have a name and a type as a minimum. For simplification, the type column is omitted if there are no possible subclasses (e.g. Person, Human Subject). If the template has a type column, you must enter a value.
  • Use URIs instead of labels with caution, as all checks are also by-passed (in particular, the ETL process does not verify that the resource exists in the repository or that the term exists in the ontology, so you may end up with non-conforming data).

  • Generate ETL templates for the most specific type needed, i.e. Antibody instead of parent type Reagent, Core Facility instead of parent type Organization, Biological process phenotype instead of parent type Phenotype, Journal Article instead of parent type Document, etc. This is because the properties generated for each of these more sub-types will be different than those generated for the root class.

    Tip

    We have found that the URI option is most useful when all values in the column are the same - otherwise it makes visual inspection of the data more difficult.

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