ISSUE-225: Levels of granularity for dimensions and categories

Levels of granularity for dimensions and categories

State:
CLOSED
Product:
Quality & Granularity Vocabulary
Raised by:
Antoine Isaac
Opened on:
2015-12-06
Description:
Raised in public comment by Werner Bailer
https://lists.w3.org/Archives/Public/public-dwbp-comments/2015Oct/0019.html

[
2. Dimensions and categories

The dimensions proposed seem quite high-level, so it is difficult to think of categories that are more general and group dimensions. In contrast, it seems in some cases desirable to have a level between dimensions and metrics. For example, we are dealing with assessing mapping quality. The metrics fall in the dimension of accuracy (i.e., does the output of the mapping process represent the object less accurately), and form a specific group there. To make the distinction of the different levels more confusing, the note in 7.3 Processability currently says "Level on the 5-star scale", which sounds more like a metric than a dimension (there could of course be metrics aggregating results from other metric, daq:requires could be used to express such a dependency).

We are not sure if there is a strong need for categories, we would rather propose to consider nesting multiple levels of dimensions to allow grouping.
]
Related Actions Items:
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Related emails:
  1. Re: AW: Data Quality Vocabulary - Levels of granularity for dimensions and categories (from aisaac@few.vu.nl on 2016-04-28)
  2. Re: AW: Data Quality Vocabulary - Multiple/Derived values of a metric and Levels of granularity for dimensions and categories (from aisaac@few.vu.nl on 2016-04-28)
  3. AW: Data Quality Vocabulary - Levels of granularity for dimensions and categories (from werner.bailer@joanneum.at on 2016-04-19)
  4. AW: Data Quality Vocabulary - Multiple/Derived values of a metric and Levels of granularity for dimensions and categories (from werner.bailer@joanneum.at on 2016-04-19)
  5. Re: Data Quality Vocabulary - Levels of granularity for dimensions and categories (from aisaac@few.vu.nl on 2016-03-06)
  6. Re: Data Quality Vocabulary - Multiple/Derived values of a metric and Levels of granularity for dimensions and categories (from aisaac@few.vu.nl on 2016-03-06)
  7. Re: dwbp-ISSUE-225: Levels of granularity for dimensions and categories [Quality & Granularity Vocabulary] (from amgreiner@lbl.gov on 2015-12-07)
  8. AW: Data Quality Vocabulary - feedback welcome! (from werner.bailer@joanneum.at on 2015-12-07)
  9. Re: Data Quality Vocabulary - feedback welcome! (from aisaac@few.vu.nl on 2015-12-06)
  10. dwbp-ISSUE-225: Levels of granularity for dimensions and categories [Quality & Granularity Vocabulary] (from sysbot+tracker@w3.org on 2015-12-06)

Related notes:

Reaction from Jeremy
https://lists.w3.org/Archives/Public/public-dwbp-comments/2015Nov/0000.html

[
I’m not sure if I understood “nesting multiple levels of dimensions” correctly, but a category groups a set of dimensions which have a common type of information as a quality indicator. For example the Accessibility category groups dimensions such as Availability, Security and Performance. Each of these dimensions have a number of different metrics, each assessing different aspect of a dimension. This is how we define Category-Dimension-Metric in daq:

A Quality Dimension is a characteristic of a dataset relevant to the consumer (e.g. Availability of a dataset).

A Quality Metric is concrete quality measure for a concrete quality indicator usually associ- ated with a measuring procedure. This assessment procedure returns a score, which we also call the value of the metric. There are usually multi- ple metrics per dimension; e.g., availability can be measured by the accessibility of a SPARQL endpoint, or of an RDF dump. The value of a metric can be numeric (e.g., for the metric “human-readable labelling of classes, properties and entities”, the percentage of entities having an rdfs:label or rdfs:comment) or boolean (e.g. whether or not a SPARQL endpoint is accessible).

A Category is a group of quality dimensions in which a common type of information is used as quality indicator (e.g. Accessibility, which comprises not only availability but also dimensions such as security or performance). Grouping the dimensions into categories helps to organise the space of all quality aspects, given their large number.
]

Antoine Isaac, 6 Dec 2015, 16:44:04

Resolved [https://www.w3.org/2016/03/14-dwbp-minutes]
[
We've sent a answer at
https://lists.w3.org/Archives/Public/public-dwbp-comments/2016Mar/0003.html

ded more examples on dimensions and categories, hopefully this provides more guidance.

- for categories, dimensions and categories we've started to use SKOS. This could allow one to use SKOS semantic relationship to indicate specialization links inside any of the three levels, as we've penciled in a note at
http://w3c.github.io/dwbp/vocab-dqg.html#DimensionsOfISOIEC25012

- for relations of dependency/derivation between metrics we now have a pattern for linking simple metrics, as discussed in the other thread on Issue 222.

we plan to close the issue and re-open if we get an objection.
]

Antoine Isaac, 16 Mar 2016, 13:25:17

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