Item — HN Reader

I wonder if data scientists engage in a triangulation* of their sources and models to explain things?

*I refer to this sense of triangulation: https://en.wikipedia.org/wiki/Triangulation_(social_science)

1 comments

Look into the provenance research that has come out of the semantic web community. They have developed a model where triple statements behave like short english sentences:

  :subject :object :predicate .

ex:

  :alice :loves :bob .

This statement by itself tells you nothing, did Alice say she loves Bob, or was it Bob who said it is Alice who loves him, or did Carol see the way Alice looked at Bob and concluded that she must love him, and what exactly is the quantitive difference between this love she feels for Bob and my love for chocolate.

To support this kind of information each term is annotated with meta-data like document of origin, author, time and place.

ex:

  :s1 rdfs:type rdfs:Statement ;
      rdf:subject :alice ;
      rdf:object :loves ;
      rdf:predicate :bob .
  
  :a1 rdfs:type prov:Activity
      prov:wasAssociatedWith :alice ;
      prov:hadMember s1 .
  
  :alice rdfs:type prov:Agent .

In computer science they call this process reification and it could be the first step into creating a model that takes the source into account.

This is very useful. I'll check out this vocabulary, wrnr, thank you!