RE: ISSUE-31 (Aggregation): Supporting aggregation for other than SKOS hierarchies [Data Cube Vocabulary]


I have a short comment on this one for now.  Relying on the SKOS relations of broader / narrower to express hierarchies is semantically limited.  There are 2 main kinds of hierarchical relations: generic and partitive.  Both should be available for use.  The broader / narrower constructs in SKOS subsume both, yet they are quite different.

Generic refers to the super-type / sub-type relation.  An example is the relationship between vehicle and automobile.  An automobile is a vehicle, but not every vehicle is an automobile.

Partitive refers to the part-whole relation.  An example is the relationship between an automobile and the engine.  The engine is a part of an automobile, but it is not an automobile itself.

The ISO standards 704 and 1087-1 describe this very well.  SKOS references ISO 2788, but that standard is imprecise in this matter.

You mentioned SDMX in the statistical community.  The other important metadata standard in use there is the DDI (Data Documentation Initiative), and an effort out of DDI work is to extend SKOS to include a richer semantics as I described above.  This is being called XKOS.  Richard is involved.


Dan Gillman
Bureau of Labor Statistics
Office of Survey Methods Research
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Washington, DC 20212 USA
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-----Original Message-----
From: Government Linked Data Working Group
Issue Tracker [] 
Sent: Friday, February 17, 2012 11:14 AM
Subject: ISSUE-31 (Aggregation): Supporting aggregation for other than SKOS hierarchies [Data Cube Vocabulary]

ISSUE-31 (Aggregation): Supporting aggregation for other than SKOS hierarchies [Data Cube Vocabulary]

Raised by: Dave Reynolds
On product: Data Cube Vocabulary

Data Cube, like SDMX, supports a notion of hierarchical dimensions. 

For example, a data set on population might be broken down by sex. If the code list is hierarchical (with an ex:ALL top category with subcategories of ex:Male and ex:Female) then it is possible to publish a dataset with the overall population corresponding to the top level code (ex:ALL) and then the number of men and women coded against the sub-categories. In the current design skos:Concepts are used for such code list and thus skos:broader/skos:narrower used to define the hierarchy.

Do we need to generalize or clarify this mechanism?


(1) Should Data Cube allow non-SKOS hierarchical code lists? E.g. by declaring the property which links codes into a subsumption hierarchy.

A specific use case for this is for geographic information. Many statistical data sets published by governments include dimensions of time (sdmx:refTime) and area (sdmx:refArea). For representing geographic or administrative regions there are large existing linked data sets (such as where the spatial containment relation has already been defined and is not skos:narrower. Similarly for representing time periods like Quarters, Half (Government) years etc there are services such as the UK reference time service ( Can those hierarchies be directly used for Data Cube dimensions?

See also discussion thread at [1].

(2) Should it be possible to explicitly provide an aggregate value at the level of a qb:Slice? 

A specific use case for this publication of financial data. Some UK local authorities have published payments information using a Payments ontology[2] which derives Data Cube. Individual expenditure line times appear as single qb:Observations, these are then grouped into qb:Slices which make up a single payment and the total payment is given at the slice level. This may be a common pattern which, if support directly by Data Cube, would allow for publication of aggregates which cross multiple dimensions.

The possible ways of expressing such aggregation relations is related to ISSUE-30.



Received on Friday, 17 February 2012 18:48:56 UTC