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dimension's nodeKind is not required, but should be there (if ns.sh.nodeKind === ns.sh.Literal dimension is treated as literal dimension, otherwise as namedNode dimension). If nodeKind is absent, we treat dimension as Literal dimension,
dimension's scaleType is not required, but should be there so we can properly categorize dimension type (ns.qudt.NominalScale, ns.qudt.OrdinalScale, ns.qudt.RatioScale or ns.qudt.IntervalScale),
dimension's sh:in property should be specified to avoid sending additional queries to fetch available dimension values,
dimension should have:
localized ns.schema.name,
localized ns.schema.description,
ns.rdf.type === ns.cube.KeyDimension if it's a key dimension,
ns.rdf.type === ns.cube.MeasureDimension if it's a measure,
optionally have ns.qudt.hasUnit property,
ns.sh.order property to sort the dimensions e.g. in table preview,
The second point because is technically already required by the standalone-constraint-constraint however it allows an additional qudt:EnumerationScale.
sh:message "If qudt:scaleType is used it needs to be within ( qudt:IntervalScale qudt:NominalScale qudt:EnumerationScale qudt:RatioScale qudt:OrdinalScale )"
];
qudt:EnumerationScale is not actually mentioned by cube.link spec nor Cube Creator wiki. cc @Rdataflow
nodeKind
is not required, but should be there (ifns.sh.nodeKind
===ns.sh.Literal
dimension is treated as literal dimension, otherwise as namedNode dimension). IfnodeKind
is absent, we treat dimension as Literal dimension,scaleType
is not required, but should be there so we can properly categorize dimension type (ns.qudt.NominalScale
,ns.qudt.OrdinalScale
,ns.qudt.RatioScale
orns.qudt.IntervalScale
),sh:in
property should be specified to avoid sending additional queries to fetch available dimension values,ns.schema.name
,ns.schema.description
,ns.rdf.type
===ns.cube.KeyDimension
if it's a key dimension,ns.rdf.type
===ns.cube.MeasureDimension
if it's a measure,ns.qudt.hasUnit
property,ns.sh.order
property to sort the dimensions e.g. in table preview,Originally posted by @bprusinowski in #114 (comment)
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