Don’t like RDF Reification?Making Statements about Statements

Using Singleton Property

Vinh NguyenKno.e.sis

Wright State University

Olivier BodenreiderNational Library of MedicineNational Institute of Health

Amit ShethKno.e.sis

Wright State University

WWW 2014, Seoul

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Linked Open Data

• > 70% Metadata • Relation Extraction fromunstructured text (PubMed, Wiki)• Evidences• Judgement

Subject Predicate Object Starts Ends

Bob Dylan marriedTo Sarah Lownds 1965-11-22 1977-06-29

Bob Dylan marriedTo Carolyn Dennis 1986-06-## 1992-10-##

Motivation ScenarioFacts:

Meta Queries:

Query type Sample query

Provenance P1. Where is this fact from? P2. When was it created? P3. Who created this fact?

Time T1. When did this fact occur?T2. What is the time span of this fact?T3. Which events happened in the same year?

Location L1. What is the location associated with this fact? L2. Which events happened at the same place?

Certainty C1. What is the author confidence of this fact?

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Subject Predicate Object

Bob Dylan marriedTo Sarah Lownds

Bob Dylan marriedTo Carolyn Dennis

Subject Predicate Object Starts Ends

Bob Dylan marriedTo Sarah Lownds 1965-11-22 1977-06-29

Standard RDF Reification

Form of Triples: Standard RDF Reification

Pros:

1. Intuitive, easy to understand

Cons:1. Takes 3N triples (4N if including

Statement typing) to represent a statement => Not scalable

2. No formal semantics defined => Semantics is unclear

3. Discouraged in LOD!

Time-aware Facts:

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Subject Predicate Object

#stmt1 type Statement

#stmt1 hasSubject BobDylan

#stmt1 hasProperty marriedTo

#stmt1 hasObject Sara Lownds

Bob Dylan marriedTo Sarah Lownds

#stmt1 starts 1965-11-22

#stmt1 ends 1977-06-29

Subject Predicate Object Starts Ends

Bob Dylan marriedTo Sarah Lownds 1965-11-22 1977-06-29

Standard RDF Reification

RDF Reification vs. Singleton PropertyTime-aware Facts:

Subject Predicate Object

#stmt1 type Statement

#stmt1 hasSubject BobDylan

#stmt1 hasProperty marriedTo

#stmt1 hasObject Sara Lownds

Bob Dylan marriedTo Sarah Lownds

#stmt1 starts 1965-11-22

#stmt1 ends 1977-06-29

Subject Predicate Object

marriedTo#1 rdf:sp marriedTo

BobDylan marriedTo#1 Sarah Lownds

marriedTo#1 starts 1965-11-22

marriedTo#1 ends 1977-06-29

Singleton Property

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Subject Predicate Object Source DateExtracted

Bob Dylan marriedTo Sarah Lownds wikipage:Bob_Dylan 2009-06-07

Form of Triples: PaCE

Pros:1. Save ~50% number of triples

compared to reification thanks to the repeated subject, predicate, and object.

Cons:1. Not intuitive, hard to

understand

2. Limited expressiveness

Provenance-aware Facts:

Provenance-aware Context Entity

Subject Predicate Object

BobDylan_wp rdf:type Bob Dylan

SaraLownds_wp rdf:type Sara Lownds

BobDylan_wp marriedTo SaraLownds_wp

BobDylan_wp hasSource wiki:Bob_Dylan

BobDylan_wp hasDateExt 2009-06-07

Satya S. Sahoo, Olivier Bodenreider, Pascal Hitzler, Amit Sheth, and Krishnaprasad Thirunarayan. 2010. Provenance context entity (PaCE): scalable provenance tracking for scientific RDF data. In Proceedings of the 22nd international conference on Scientific and statistical database management (SSDBM'10),

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Subject Predicate Object Source DateExtracted

Bob Dylan marriedTo Sarah Lownds wikipage:Bob_Dylan 2009-06-07

Provenance-aware Context Entity

Subject Predicate Object

BobDylan_wp rdf:type Bob Dylan

SaraLownds_wp rdf:type Sara Lownds

BobDylan_wp marriedTo SaraLownds_wp

BobDylan_wp hasSource wiki:Bob_Dylan

BobDylan_wp hasDateExt 2009-06-07

Facts and Provenance:PaCE vs. Singleton Property

Subject Predicate Object

marriedTo#1 rdf:sp marriedTo

BobDylan marriedTo#1 Sarah Lownds

marriedTo#1 hasSource wp:Bob_Dylan

marriedTo#1 hasDateExt 2009-06-07

Singleton Property

Form of Quadruples: Named Graph

Pros:

1. Intuitive --creating # named graphs for # sources

2. Attach metadata for a set of triples3. SPARQL supported

Cons:

1. Defined for provenance only

2. Ambiguous semantics while associating different types of metadata at triple level

Time-aware Facts:

* Carroll, Jeremy J., et al. "Named graphs, provenance and trust." Proceedings of the 14th international conference on World Wide Web. ACM, 2005.

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Subject Predicate Object Starts Ends

Bob Dylan marriedTo Sarah Lownds 1965-11-22 1977-06-29

Named GraphSubject Predicate Object NG

Bob Dylan marriedTo Sarah Lownds ng_1

ng_1 starts 1965-11-22 Prov_graph

ng_2 ends 1977-06-29 Prov_graph

Named GraphSubject Predicate Object NG

Bob Dylan marriedTo Sarah Lownds ng_1

ng_1 starts 1965-11-22 Prov_graph

ng_2 ends 1977-06-29 Prov_graph

Time-aware Facts:

Subject Predicate Object Starts Ends

Bob Dylan marriedTo Sarah Lownds 1965-11-22 1977-06-29

Named Graph vs. Singleton Property

Subject Predicate Object

marriedTo#1 rdf:sp marriedTo

Bob Dylan marriedTo#1 Sarah Lownds

marriedTo#1 starts 1965-11-22

marriedTo#1 ends 1977-06-29 9

Singleton Property

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RDF+:Subject Predicate Object Meta Property Meta value

Bob Dylan marriedTo Sarah Lownds starts 1965-11-22

Bob Dylan marriedTo Sarah Lownds ends 1977-06-29

Form of Quintuples: RDF+

Cons:1. The representation is not in the form of RDF. Statement identifiers are used

internally. Require the mappings from RDF to RDF+ and vice versa.

2. The SPARQL query syntax and semantics need to be extended to support RDF+

Facts and Temporal Information:

* Dividino, Renata, et al. "Querying for provenance, trust, uncertainty and other meta knowledge in RDF." Web Semantics: Science, Services and Agents on the World Wide Web 7.3 (2009): 204-219.

Subject Predicate Object Starts Ends

Bob Dylan marriedTo Sarah Lownds 1965-11-22 1977-06-29

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Overall Goal

3. Scalable, e.g., to LOD

A mechanism to make statements about statements should meet these requirements:

2. Formal semantics defined1. Intuitive, easy to understand

4. Compatible with existing standards

5. Multiple types of metadata

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Generic Property vs. Singleton PropertySubject Predicate Object Source MarriageDate

Bob Dylan marriedTo Sarah Lownds wikipage:Bob_Dylan 1965-11-22

BarackObama marriedTo MichelleObama wikipage:Barack_Obama 1992-10-03

Facts and Provenance:

Generic Property:

1. marriedTo is an RDF property

2. marriedTo => {(Bob Dylan, Sarah Dylan), (Barack Obama, Michelle Obama),……}

3. Any assertion to marriedTo is applicable to all pairs of entities!

Singleton Property:

1. marriedTo#1, marriedTo#2 are RDF property2. Different property instances: marriedTo#1,marriedTo#2,…marriedTo#n

3. Any assertion to marriedTo#1/marriedTo#2/…/marriedTo#n is applicable to only ONE pair <= KEY

instanceOf

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• Given a vocabulary V,

Model-Theoretic SemanticsOriginal* Simple Interpretation I :

satisfies additional criteria as follows:

• IPS: a subset of IR, called the set of singleton properties of I,

New simple Interpretation I :

satisfies additional criteria as follows:

• xs IP∈ s if

⟨xs, rdf:SingletonPropertyI I⟩ ∈ EXT (rdf:typeI)

New RDF Interpretation I :

• IR: a non-empty set of resources, alternatively called domain or universe of discourse of I.

• IP: the set of generic properties of I

• IEXT: a function assigning to each property a set of pairs from IR where IEXT (p) is called the extension of property p

• IS: a function, mapping URIs from V into the union set of IR and IP,

• IL: a function from the typed literals from V into the set of resources IR,

• LV: a subset of IR, called the set of literal values.

• IEXT : IP → 2IR X IR

IS_EXT : IPS→ IR X IR.

• IS_EXT (ps): is a function assigning to each singleton property a pair of entities from IR.

• xs IP∈ s if

⟨xs, xI I⟩ ∈ EXT (rdf:singletonPropertyOfI),

and x IP, I∈ S_EXT (xs) = <s1, s2>

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IR = {α, β, γ, δ, θ, λ, σ, ϕ}

IP = {δ, θ, λ, σ, ϕ}

LV = {1965-11-22, 1977-06-29,

1986-06-##, 1992-10-##}IEXT = θ → { α, β } ⟨ ⟩

λ → { α, γ } ⟨ ⟩ σ → { θ, 1965-11-22 , ⟨ ⟩

⟨λ, 1986-06-## } ⟩φ → { θ, 1977-06-29 , ⟨ ⟩

⟨λ, 1992-10-## } ⟩rdf:sp → { θ, δ ,⟨ ⟩ λ, δ } ⟨ ⟩δ → { α, β ,⟨ ⟩ α, γ } ⟨ ⟩

IPS = {θ, λ}IS_EXT = θ→ α,β ⟨ ⟩

λ → α,γ⟨ ⟩

Model-Theoretic Semantics: ExampleExample of vocabulary VEX:

RDF Interpretation of VEX:

Subject Predicate Object

BobDylan isMarriedTo Sarah Lownds

BobDylan isMarriedTo#1 SaraLownds

isMarriedTo#1 rdf:sp isMarriedTo

isMarriedTo#1 hasStart 1965-11-22

isMarriedTo#1 hasEnd 1977-06-29

BobDylan isMarriedTo CarolynDennis

BobDylan isMarriedTo#2 CarolynDennis

isMarriedTo#2 rdf:sp isMarriedTo

isMarriedTo#2 hasStart 1986-06-##

isMarriedTo#2 hasEnd 1992-10-##

BobDylan

→ α

SaraLownds → β

CarolynDennis

→ γ

isMarriedTo → δ

isMarriedTo#1

→ θ

isMarriedTo#2

→ λ

hasStart

→ σ

hasEnd

→ φ

IS:

Querying Meta Triples Using SPARQLTriple Type Subject Predicate Object

Instantiating singleton property predicate_i rdf:sp predicate

Singleton triple subject predicate_i object

Meta triple predicate_i meta-predicate_j meta-value_j

Singleton Graph Pattern

Data Query:

1. Who married whom?

2. SPARQL query

SELECT ?person1 ?person2WHERE { ?person1 ?married_sp ?person2 .?married_sp rdf:sp:marriedTo .

}

Meta Query:

1. Who married whom and when?

2. SPARQL query

SELECT ?person1 ?person2 ?timeWHERE { ?person1 ?married_sp ?person2 .?married_sp rdf:sp:marriedTo . ?married_sp :happenedOn ?date .} 15

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Use Case: Temporal and Spatial YAGO2S

FactID Subject Predicate Object

#1 GratefulDead performed TheClosingOfWinterLand

#2 #1 occursIn SanFrancisco

#3 #1 occursOn 1978-12-31

Subject Predicate Object

performed_12345 rdf:singletonPropertyOf performed

GratefulDead performed_12345 TheClosingOfWinterLand

performed_12345 occursIn SanFrancisco

performed_12345 occursOn 1978-12-31

FactID in Yago2s

Singleton Property

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Experiment: BKR with Provenance

All datasets are available at http://wiki.knoesis.org/index.php/Singleton_Property

• Five data sets generated from the same seed BKR Singleton Property (SP) Reification (R) PaCE C1 (C1) PaCE C2 (C2) PaCE C3 (C3)

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Experiment Results

(A) random-value queries vs. fixed-value queries in msec.

(B) query length and execution time in msec.

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Conclusion

3. Scalable, e.g., to LOD

Does the singleton property approach meet these requirements?

2. Formal semantics defined1. Intuitive, easy to understand

4. Compatible with existing standards

5. Multiple types of metadata

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Further information, please visit http://wiki.knoesis.org/index.php/Singleton_Property