Part I: Motivation

Linked Data requires owl:sameAs

Linked data requires owl:sameAs

louvre:monaLisa
  dc:created "1503"^^xsd:gYear;
  dc:creator "Da Vinci".

louvre:monaLisa owl:sameAs sothebys:somePainting.

sothebys:somePainting
  sothebys:auctionDate "2018-06-07"^^xsd:date;
  sothebys:price "€1.000,-";
  sothebys:contact "mailto:bidding@sothebys.com"^^xsd:anyURI.

Similarity is not good enough

The only thing worse than owl:sameAs is ‘clever’ replacements for owl:sameAs.

lexvo:nearlySameAs lexvo:somewhatSameAs owl:sameAs.

lexvo:nearlySameAs lexvo:nearlySameAs lexvo:somewhatSameAs?

owl:sameAs lexvo:somewhatSameAs bbc:sameAs?

Use cases

• Findability through backlinks
• Query Answering under OWL entailment
• Ontology Alignment
• Empirical Semantics

We need an enabler for empirical research into how owl:sameAs is actually being used.

The analytic approach: “people make mistakes” / “it's just noise” is not enough.

www.sameAs.cc requirements

• A performant and cost-effective solution for determining whether two things are (claimed to be) the same.
• This solution must scale to the LOD Cloud.
• This solution must be formally interpretable (no skos:exactMatch, rdfs:seeAlso).
• It must be calculated incrementally.

Part II: Approach

Formal properties of Identity

Identity is the smallest equivalence relation, it is:

• reflexive (x,x)
• symmetric (x,y) → (y,x)
• transitive (x,y) ∧ (y,z) → (x,z)

Example

Explicit identity relation (domain {:a,:b,:c,:d})

:a owl:sameAs :b.

:d owl:sameAs :b.

:a owl:sameAs :a.
:a owl:sameAs :b.
:a owl:sameAs :d.
:b owl:sameAs :a.
:b owl:sameAs :b.

:b owl:sameAs :d.
:c owl:sameAs :c.
:d owl:sameAs :a.
:d owl:sameAs :b.
:d owl:sameAs :d.

Extract the explicit identity relation

prefix owl: <http://www.w3.org/2002/07/owl#>
construct {
  ?s owl:sameAs ?o
} where {
  {
    select distinct ?s ?o {
      ?s owl:sameAs ?o
      filter(?s < ?o)
    }
  }
}

Result set size: 558.9M

Create an HDT file in 4 hours (1 CPU core); 4.5GB + 2.2GB index

Compaction

For calculating the implicit identity relation we do not need the full explicit identity relation (558.9M):

2.8M

reflexive triples

225M

duplicate symmetric triples

Compaction reduces size by 42% (311M triples).

Calculate the implicit identity relation

• RDF nodes : N
• key : ID ↦ Ƥ(N)
• val : N ↦ ID
• Identity closure for x : key(val(x))

Run time: 5 hours (2 CPU cores); 9.3GB disk (RocksDB)

Part III: Analysis

Terms in the explicit identity relation

Explicit identity statements per term

Aggregation by namespace

Terms in implicit identity relation

№ Identity sets in implicit identity relation

Singleton identity sets

5,044,948,869

Non-singleton identity sets

48,999,184

Non-singleton identity sets

Kernel calculation

The size of a minimal explicit identity relation that denotes the same implicit identity relation.

Runtime

55.6 seconds (3 CPU cores)

Kernel size

130,673,158 triples

Percentage of the implicit identity relation

0.37%

Percentage of the explicit identity relation

23.4%

Part IV: Practical example

Explicit identity statements for ‘Barack Obama’

But are these really the same resource?

http://als.dbpedia.org/resource/Barack_Obama
http://am.dbpedia.org/resource/ባራክ_ኦባማ
http://data.nytimes.com/obama_barack_per
http://viaf.org/viaf/52010985
http://yago-knowledge.org/resource/Barack_Obama
http://rdf.freebase.com/ns/m.02mjmr

http://dbpedia.org/resource/Administration_of_Barack_Obama
http://dbpedia.org/resource/Barack_Obama_Cabinet
http://dbpedia.org/resource/Barack_Obama_presidency
http://yago-knowledge.org/resource/Presidency_of_Barack_Obama
http://rdf.freebase.com/ns/m.05b6w1g

‘Barack Obama’ after community detection