1. SPARQLeR: Extended Sparql for Semantic Association Discovery Krzysztof Kochut and Maciej Janik Work supported by the National Science Foundation Grant No. IIS-0325464, entitled “SemDIS: Discovering Complex Relationships in the Semantic Web”. ESWC 2007, Innsbruck, Austria June 4, 2007

2. Computer Science Department University of Georgia Paths in RDF Directed path Undirected path Undirected path, but with specific properties and directionality

3. Computer Science Department University of Georgia Why are paths interesting ? A path describes how entities are related. –Relationships on the path define meaning of this connection. –Entities on the path specify the content. Do you have migraine? Try taking magnesium! –Path discovered by Dr. D.R.Swanson from partial information available in PubMed publications stress can lead to loss of magnesium in the human body migraine patients seem to be experiencing stress … that’s why … migraine could lead to a loss of magnesium, so … take magnesium to fight migraine! Swanson, R.D. Migraine and Magnesium: Eleven Neglected Connections. Perspectives in Biology and Medicine, 31 (4). 526-557.

4. Computer Science Department University of Georgia Formally, what is a simple path ? Simple directed path between resources r 0 and r n in a description base R: –sequence r 0 p 1 r 1 p 2 r 2, …, p n-1 r n-1 p n r n (n>0) –r 0 p 1 r 1, r 1 p 2 r 2, …, r n-2 p n-1 r n-1, r n-1 p n r n (n>0) are triples in R. –all of the resources r i (0 ≤i ≤ n) in the path are distinct Simple undirected path between resources r 0 and r n in R: –sequence r 0 p 1 r 1 p 2 r 2, …, p n-1 r n-1 p n r n (n>0) –for each r i-1 p i r i (0 < i ≤ n) in the path, either r i-1 p i r i or r i p i r i-1 is a triple in R –all of the resources r i (0 ≤i ≤ n) in the path are distinct

5. Computer Science Department University of Georgia Paths and SPARQL SPARQL query can express only static graph patterns. –Some flexibility is introduced by an OPTIONAL part, but it does not solve path problems. No support for flexible length path expressions. –Glycan biosynthesis pathway in biology has a specific pattern (properties), but its length may be unknown. –Path discovery may be of unknown length and pattern, like in Dr. Swanson’s example.

6. Computer Science Department University of Georgia What we need to discover paths? Knowledge discovery needs more flexible patterns. –Patterns may be partially known or even unknown (unrestricted path). –Properties on the path, their order and directionality create a specific meaning. –Entities on the path provide content. –Relationships to entities outside of the path give an additional context.

7. Computer Science Department University of Georgia Proposed extensions A path may have a flexible length –For computational reasons, length is limited. Constraints on properties –Specific properties must appear in the path. –Their order and directionality is meaningful. –They can form a repeating pattern. Constraints on resources –Specific resources must be on the path. –They can be anywhere on the path or at specific positions.

8. Computer Science Department University of Georgia SPARQLeR Extension of SPARQL for semantic association discovery. Seamlessly integrated into the SPARQL syntax. Graph patterns incorporating simple paths with constraints. Constraints are based on regular expressions over properties.

9. Computer Science Department University of Georgia What is a path in SPARQLeR ? Path is a meta-property that connects two resources. –Defined as a sequence of interleaving properties and resources. –Starts and ends with properties (endpoint resources are not included). –A path of length 1 is a sequence with just one property. Path The class of RDFMS paths.

10. Computer Science Department University of Georgia Path patterns in SPARQLeR Meta-property – similar concept to a property –Resource –[property]  Resource –Resource –[path]  Resource Path as a Sequence –Test if a resource is in the path: rdfs:member –Test if a resource is at a specific position in the path: rdf:_2, rdf:_4,... SPARQLeR-specific path properties –Test all resources or all properties in the path: rdfms:entityResource and rdfms:propertyResource Example: all resources on a path must be of type foo:Person

11. Computer Science Department University of Georgia Path pattern anatomy p1p1 p1p1 p1p1 p1p1 p2p2 p2p2 p2p2 p3p3 rdfs:member rdf:_6 p3p3 rdf:_3 rdfs:member p2p2 1 2 357 64 length: 4 elements: 7 rdfms:entityResource p1p1 rdfms:propertyResource Path patterns (match of path variable)

12. Computer Science Department University of Georgia Path types in SPARQLeR Directionality of relationships in the path defines its specific semantics. SPARQLeR allows definition of the following path types –As defined in graph theory Directed Undirected –SPARQLeR specific extension Defined directionality path (includes directed path)

13. Computer Science Department University of Georgia Directionality of properties in path Defined directionality paths: –Neither directed nor undirected –Each property in a path has a specified directionality Example: simple graph with p relationship (a) X p* Y, directed path (b) X p* Y, undirected path (c) X ( p p -1 )* Y, directional path XY (a)(b)(c) pppp pp pp

14. Computer Science Department University of Georgia Inverse property operator In standard SPARQL there is no need for inverse property operator –Pattern syntax is based on individual statements, so it is easy to reverse direction. Defining path constraints requires the inverse operator –A pPath expression defines constraints on properties, not on individual statements. –Without the inverse property operator some paths constraints would be impossible to express (as shown in the previous example).

15. Computer Science Department University of Georgia RegExp in path constraints Path constraints on properties are based on regular expressions –Uses syntax similar to lex –Easy for grep users Examples: a c* da+ (b|c) a [abc] c? d( b a -1 )+ c

16. Computer Science Department University of Georgia Path constraints in SPARQLeR Defined as regular path expressions –Can specify patterns of properties in the path –Directionality requirement needs the inverse operator  (‘-’ minus) –p Supported regular expressions p (single property) -p (the inverse of p) [p 1 p 2... p n ] (class of properties) -[p 1 p 2... p n ] (class of inverse properties) [^p 1 p 2.. p n ] (complement of properties) -[^p 1 p 2.. p n ] (inverse of complement of properties). (wildcard) x | y (alternative) xy (concatenation) x* (Kleene star); x+ (one or more repetition) (x) (match a path matched by x)

17. Computer Science Department University of Georgia Path constraints (cont’d) Class of properties and inverse operator –Complement operator can be applied only to defined properties, not their inverses –Inverse operator Not allowed inside class of properties Inverses set created from defined properties –Example: properties: q r s t [^rt]  q s –[^qr]  t -1 s -1 (inverses) ([^st] | –[^t])  q r q -1 r -1 s -1

18. Computer Science Department University of Georgia Integrating paths into SPARQL Path variable binds a path –Name begins with ‘%’ instead of ‘?’ Simple patterns – path between two resources SELECT ?prop WHERE { ?prop } SELECT %path WHERE { %path } Single source path SELECT %path, ?res WHERE { %path ?res}

19. Computer Science Department University of Georgia Integrating paths into SPARQL Resources on the path SELECT %path WHERE { %path. %path rdfs:member } SELECT %path WHERE { %path. %path rdf:_1 } Listing path elements – list operator SELECT list(%path) WHERE { %path }

20. Computer Science Department University of Georgia Expressing path constraints Bounded path length –only constants allowed FILTER(length(%path)<5) FILTER(length(%path)>3 && length(%path)<7)

21. Computer Science Department University of Georgia Expressing path constraints Constraints added as a regular expression filter (existing syntax in SPARQL) regex( pathvariable, pathexpr, pathflags ) FILTER(regex(%path,”.*foo:prop.*”,”uis”)) –Flags: i (instances) s (schema) l (literals) h (match using hierarchy) d (set directionality) u (undirected) –Default flags: d i

22. Computer Science Department University of Georgia Some examples SELECT list(%path), ?res WHERE { %path ?res. %path rdfs:member ?x. ?x foo:locatedIn wiki:Europe FILTER(regex(%path,”foo:prop+”)} SELECT list(%path) WHERE { %path. %path rdfms:entityResource ?x. ?x rdf:type foo:Person FILTER(regex(%path,”(foo:prop|foo:rel)+”,”u”)} SELECT list(%path) WHERE { %path FILTER(length(%path) =4 && regex(%path,”(foo:prop -foo:rel)+”)}

23. Computer Science Department University of Georgia SPARQLeR Prototype Implementation Prototype implementation is based on BRAHMS – RDF/S main memory storage. Path search based on a bi-directional BFS for simple paths. Checking of path constraints in regex is implemented as a simulation of DFAs. Janik, M. and Kochut, K., BRAHMS: A WorkBench RDF Store And High Performance Memory System for Semantic Association Discovery. ISWC 2005

24. Computer Science Department University of Georgia Implementation details Each path expression ( FILTER regex ) is translated into a DFA. –For path between two resources, partial constraints are checked while building the search trie from both endpoints – forward and reverse DFAs –When a path is connected, the forward DFA used to check the full (path) constraint.

25. Computer Science Department University of Georgia Experiments: biology pathway Biosynthesis paths in biology (glycomics) How specific glyco peptide is created from a basic structure? –Find pathway between dolichol phosphate and glyco peptide G00009 Path has 15 reactions (30 hops, as each reaction is represented by its substrates and products) Only undirected path connects the endpoint resources, but a specific directionality pattern is present RDF representation: sample reactions in the path

26. Computer Science Department University of Georgia Experiments : biology pathway Functionality test - proof of concept N-glycan biosynthesis pathway SELECT list(%path) WHERE { glyco:dolichol_phosphate %path glyco:glyco_peptide_G00009. %path rdfs:member enzyo:R05969 FILTER ( length(%path) <= 30 && regex(%path, "((-glyco:has_acceptor_substrate| -glyco:has_reactant) glyco:has_product)*" ) ) } Ontology:GlycO Length:30 hops Consists of:15 reactions Search time:milliseconds (less than 1 tick)... courtesy of Dr. Alison Vandersall-Nairn, University of Georgia

27. Computer Science Department University of Georgia Experiments Scalability –Modified DBLP datasets in RDF (added random citations) –Test on increasing dataset (adding older years of publications) –Search for cited publications (transitive) PREFIX opus: SELECT ?end_publication WHERE { %path ?end_publication FILTER ( length(%path)<=26 && regex(%path, "(opus:cites_publication)*" ) ) } B. Aleman-Meza et. al. Semantic Analytics on Social Networks: Experiences in Addressing the Problem of Conflict of Interest Detection. (WWW2006)

28. Computer Science Department University of Georgia Experiments – dataset characteristics

29. Computer Science Department University of Georgia Experiments – results: single source paths Search paths up to length 26

30. Computer Science Department University of Georgia Experiments – results: two endpoint paths

31. Computer Science Department University of Georgia More complex uses of path expressions Discover connecting paths with a shared node –Path between A and B, length up to 4 –Path between C and D, length up to 4 –Both paths have a shared resource A B C D C %path_2 D length(%path_2) <= 4 A %path_1 B length(%path_1) <= 4 %path_1 rdfs:member ?x %path_2 rdfs:member ?x ?x Potential subgraph discovery

32. Computer Science Department University of Georgia SPARQLeR summary Path expressions –use of regular expressions over properties Flexible path specification –Undirected –Defined directionality paths Directed –Length restricted Complex path patterns –Test of resources and properties on the path –Intersecting paths

33. Computer Science Department University of Georgia Conclusion and future work SPARQLeR extension fits seamlessly into the current SPARQL syntax. Performance of path queries is acceptable (if defined expression is highly selective). Optimization of path queries, complex expressions and multiple paths in query. Inclusion of context.

34. Computer Science Department University of Georgia SPARQLeR Krys Kochut, Maciej Janik Thank you

35. Computer Science Department University of Georgia Predicate Vs. Statement expressions Predicate alphabet p -p _ (wildcard) … simplicity … Statement alphabet s p o _ p o s _ o s p _ _ _ o _ p _ s _ _ _ _ _ Additional rules: Which statement pattern can be connected with which one …