Many dimensions, for example state/county/city or sector/industry group/industry/subindustry (eg GICS), have parent/child or broader/narrower relationships between dimension values at each level. Other schemes like SKOS or DSPL 1.0 can model this, but DSPL 2.0 does not yet include such a facility.

In this issue, discuss what such an extension could look like.

DSPL 1.0 and other schemes permit grouping of measures into categories. For example, the SDG indicators are grouped under their corresponding goals and targets, and the World Development Indicator measures are grouped under a nested hierarchy of topics.

In this issue, discuss how to extend DSPL 2.0 to support this functionality.

We may want to indicate how to generate IDs for the triples corresponding to the rows in CSV files.

This will facilitate having a well defined mapping from DSPL 2 datasets to triples, and may make it feasible to use dimension values and footnotes defined in CSV files across datasets.

Tentative proposal

Attempt to generate easy-to-keep-unique IDs, and make no provisions for ID collisions.

codeList

For each CSV row,

• Start with the containing dimension's ID.
• If there is no fragment, set the fragment to the dimension's name, URL encoded.
• Append an = and the URL-encoded codeValue to the fragment.

For example, if a row's codeValue is us and its containing Dimension has @id of #country, the row's triples should be generated as if from equivalent JSON-LD with "@id": "#country=us".

footnote

For each CSV row,

• Start with the containing StatisticalDataset's @id.
• If there is a fragment, append a /
• Append footnote= and the URL-encoded codeValue to the fragment

For example, if the dataset's @id is the empty string, a footnote with codeValue of p would yield an ID of #footnote=p. Similarly, if the dataset @id is #my_dataset, the footnote would have @id of #my_dataset/footnote=p.

observation

For each CSV row,

• Start with the slice's @id.
• If there is a fragment, append a / to it.
• Sort the dimension values by dimension name.
• For each dimension value, append the URL-encoded name, = and the URL-encoded codeValue to the fragment, separating the entries with /.
• Sort the measure values by measure name
• For each measure value, append the URL-encoded name to the fragment, separating entries with /.

For example, an observation in a slice with an @id of #europe_unemployment_slice with dimensions

• gender of m,
• country of uk, and
• month of 2010-10

and measures

• unemployment_rate and
• unemployment

would have an @id of #europe_unemployment_slice/country=uk/gender=m/month=2010-10/unemployment/unemployment_rate

Per @coto,

There are two Chilean Currencies, one is CLF also know UF, mostly used for real states, it is a currency with inflation included. The other currency is CLP, Chilean Peso. the currency used daily by Chilean people.

The file samples/google/canonical/currencies.csv conjoins these into one row with ID "CLP CLF" and description "Chilean Peso Unidades de fomento". Instead, there should be separate rows for each, with CLP described as "Chilean Peso" with symbol "$" and CLF described as "Chilean Unidades de fomento" with symbol "CF"

As is, they would fail to match either of the currencies, and the codes are never used together for a single value.

This is actually more widespread, with 24 entries exhibiting this problem, eg currencies for Bolivia, Colombia, Cuba, Haiti (where the second currency is USD). Bhutan, Mexico, etc.

Fixes #41

I left PR #40 fixing a conceptual error of currencies that you had about my country. Please someone close it or merge it since I won't sign the CLA agreement to pass the check.
BR

Right now we don't have an explicit mechanism for deciding which CSV column names correspond to each dimension or measure in a slice.
We had discussed using the fragment part of the dimension/measure's @id for this, when present.
I propose, if it is not present or is not suitable, that we permit the CSV column name to be specified as a string value for the identifier property on the CategoricalDimension, TimeDimension and StatisticalMeasure. E.g., (omitting dataset for terseness):

    {
      "@type": "StatisticalMeasure",
      "@id": "#employment",
      "name": "Employed",
      "identifier": "employed",
      "description": "The total number of people employed",
      "url": "http://www.bls.gov/cps/cps_htgm.htm",
      "unitCode": "IE"
    }

with the fragment case looking like

    {
      "@type": "TimeDimension",
      "@id": "#month",
      "name": "Month",
      "equvalentType": "xsd:gYearMonth",
      "dateFormat": "MMM yyyy"
    }

There are two Chilean Currencies according ISO 4217:

1. CLF: also know as UF, mostly used for real states, it is a currency used in Chile with inflation included.
2. CLP: Chilean Peso. the currency used daily by Chilean people.

it is confusing using CLP CLF together, in the market is CLP or CLF (UF).

Fix in samples/google/canonical/currencies.csv according what was tried to do in #40

References:

• https://en.wikipedia.org/wiki/Unidad_de_Fomento
• https://en.wikipedia.org/wiki/Chilean_peso
• https://si3.bcentral.cl/indicadoressiete/secure/Serie.aspx?gcode=UF&param=RABmAFYAWQB3AGYAaQBuAEkALQAzADUAbgBNAGgAaAAkADUAVwBQAC4AbQBYADAARwBOAGUAYwBjACMAQQBaAHAARgBhAGcAUABTAGUAYwBsAEMAMQA0AE0AawBLAF8AdQBDACQASABzAG0AXwA2AHQAawBvAFcAZwBKAEwAegBzAF8AbgBMAHIAYgBDAC4ARQA3AFUAVwB4AFIAWQBhAEEAOABkAHkAZwAxAEEARAA=

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