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Re: [dxwg] Question: how to catalog relational database data in DCAT? (#1240)

From: Rob Atkinson via GitHub <sysbot+gh@w3.org>
Date: Tue, 14 Jul 2020 00:24:46 +0000
To: public-dxwg-wg@w3.org
Message-ID: <issue_comment.created-657896502-1594686285-sysbot+gh@w3.org>
@riccardoAlbertoni - I thought long and hard about this in the context of WFS - and there seem to be a few possible patterns:

1) "traditional GIS" - download all the data (empty filter :-) ) then inspect it to work out what queries might make sense
2) "poke it with a stick" - keep trying possible queries until sensible data is returned (seems to work only the the most trivial cases where users already know the data
3) "query templates" - in a catalog or somewhere have an artefact which is a query template with possible parameters
4) "dimensional characterisation" - indicate which properties of a feature type are mapped to data dimensions, and the range of those dimensions - so it is possible to make a query as a "slice" against well documented dimensions.
5) "parameterised APIs" - a set of parameters against what is essentially some form of "stored query" - in which case parameters need to be mapped to the data model to explain the query
6) something else

1 and 2 dont really work at scale
3 requires a query templating language with ability to describe parameters
4 can be implemented by a profile of DCAT supporting RDF-QB
5 requires better semantically self-describing APIs and a canonical language to map parameter name and range against data model and data ranges.
6 ???

The underlying reality seems to be that ad-hoc APIs for slicing data proliferate because data providers dont really want to cope with exposing any possible query and comprehensive documentation is too hard to write, find and read.  

From what I have seen so far I think dimensional characterisation using RDF-QB is the option for a canonical metadata model that carries the most semantic information and can be used to restrict queries, build queries and document data itself. It also provides an option for mapping API parameters to data structures.  At this stage no other candidates have been suggested for the use cases of semantic description of data.



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