Hello hello During the hackathon we talked about aggregators but I have no idea of how they are implemented. For example, Exiobase documents emissions of "HFC"s while we have characterisation factors

#rdf #correspondencetables #ontology

Interesting, I will have a deeper look when possible. I was updating the group readme. Should I move the references to the Hackathon somewhere else? it seems that this repo will survive and it will ha

#correspondencetables

As we are not the only people thinking about these topics, there has already been a lot of work in this area. It is relatively easy to find some half-baked implementations in RDF, e.g. datahub.io, joi

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Hello hello lets see if I am getting this right. Chris, when you say "put metadata systems in their native form into arborist (e.g. ISIC 3, ISIC 4, HS1, NACE, NAICS, CPC)" does that mean "as downloade

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In this case your example seems fine, you can still say that fbcl is subclass of POWC probably. you can also say sameAs between POWN and Nuclear, assuming that the only way of producing electricity is

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Thanks Matteo- It is a bit tricky keeping the class definitions and instances inline with the idea of `rdf:type` referring to multiple classes - could you provide an alternative implementation of the

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Hi Chris, have you checked the very useful examples here: https://www.w3.org/2006/07/SWD/SKOS/skos-and-owl/master.html In general let's use subsclass of and rdf:type when we know it is a subset or an

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@Matteo, Bo, Miguel; please comment and correct! Defining correspondence tables in RDF Based on my reading of https://www.w3.org/TR/skos-reference/, I created the following: @prefix bont: <http://onto

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I agree with Chris here. First, most classifications contain themselves hierarchies, typically indicated by some code convention, such as ISIC 4 "011" being a subclass of "01" and so on. These should

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Thanks Miguel- It seems clear to me that the first step should be defining the verbs we will use, and the reasons we are using these particular verbs. For example, both OWL and SKOS seem to offer simi

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In the future, should manual string matching be too time-consuming, you may consider to get some help from fuzzy string comparison (https://github.com/seatgeek/fuzzywuzzy) /Romain

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Dear all During the Friday meeting we discussed the issue of how to arrive from “raw data” to the data stored in the database. There was some disagreement and I think I did not explain myself clearly

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Dear all An update on this. Yesterday I created a repo following the python skeleton for the functions that will automate part of the workflow. Its called grafter. I have not had time to work on the f

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Dear all, my replies inline Best, Miguel

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Dear all- I am happy that there are a number of people participating here, and I think we have everything ready for assembly into a 1.0 version of this package. However, from reading these emails and

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Nice I’ve created an issue on the repo tagged as an enhancement. https://github.com/BONSAMURAIS/Correspondence-tables/issues/22 I also asked them for the correspondence table from SIEC to CPC and SIEC

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Dear all, I have received an update form the UNSD Statistical Classification office. This was the source of most of the tables that we currently have on GitHub. These were then removed from UNSD webpa

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Yes, that makes a lot of sense

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Please consider https://frictionlessdata.io/specs/csv-dialect/. We don't want to invent our own CSV dialect!

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When I tried to create metadata yesterday for one of the tables (isic4 to Nace2 I think) that table was in the format you describe. The problem was that some columns had mixed data types (e.g. strings

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