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Reifying RDF: What Works Well With Wikidata?

Summary

The authors look for the most convenient way to translate Wikidata into RDF so that it can be queried with ordinary SPARQL engines. The difficulty is that Wikidata statements carry qualifiers (for example, a period of validity) and references to sources. A mechanism is therefore needed for describing the triples themselves, that is, reification. First, the researchers propose a conceptual schema consisting of two tables. The first consists of quads (s, p, o, i), where i is a statement identifier. The second contains ordinary triples for qualifiers, labels and auxiliary value attributes. The task thus reduces to how to encode the quads in RDF. Starting from a Wikidata dump, the authors produced four datasets, each following a different model: named graphs, singleton properties, n-ary relations, and the standard form of reification. They then ran a benchmark of 14 queries, each in four variants, on five popular engines. There is no clear winner among standard reification, n-ary relations and named graphs. By contrast, singleton properties are poorly supported by most systems. The work offers practical guidance to Wikidata developers and to anyone who stores annotated facts in RDF.

Key points

  • Scale of Wikidata (as of July 2015): more than 65 million statements and about 18 million entities. Roughly half of the statements (32.5 million) already had a reference to a source.
  • Why quins (s, p, o, q, v) and schemes such as RDF are unsuitable:* the same base relation can have several different sets of qualifiers. An example is the two non-consecutive presidential terms of Grover Cleveland.
  • Engines tested: 4store, BlazeGraph, GraphDB, Jena TDB and Virtuoso. Virtuoso performed most reliably, whereas 4store returned few answers within the allotted time.
  • Which was fastest (70 "engine × query" combinations in total): named graphs in 17 cases, standard reification and n-ary relations in 16 cases each.
  • Trade-offs between the models: singleton properties give the most compact representation at the triple level but create a very large number of unique predicates. All engines except Virtuoso failed to cope with this. 4store also failed to cope with a large number of named graphs. Only n-ary relations naturally support property paths in SPARQL.

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

Fields: AI & machine learning

Topics Knowledge graphs & ontologies

Cite

Cite as Daniel Hernández, Aidan Hogan and Markus Krötzsch. 2015. Reifying RDF: What Works Well With Wikidata?. SSWS 2015 (ISWC workshop), CEUR-WS Vol-1457.

The paper itself, not this page. BibTeX from the library's record of the work.

@inproceedings{hernandez2015reifying,
  title = {{Reifying RDF: What Works Well With Wikidata?}},
  author = {Daniel Hernández, Aidan Hogan and Markus Krötzsch},
  booktitle = {SSWS 2015 (ISWC workshop), CEUR-WS Vol-1457},
  year = {2015},
  url = {https://ceur-ws.org/Vol-1457/}
}

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