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![Introduction and motivation
Need for context in Semantic Web
Most of Semantic Web data holds in specific contextual space
(time, location, topic...)
No explicit support for modelling and reasoning
with context sensitive knowledge in SW
(Often handcrafted in implementation)
Ô Need for well-defined theory of contexts
Contextualized Knowledge Repository (CKR)
DL based framework for representation and reasoning with
contextual knowledge in the Semantic Web
Contextual theory: based on formal AI theories of context
[McCarthy, 1993, Lenat, 1998, Giunchiglia and Ghidini, 2001]
Other DL contextual frameworks:
[Bao et al., 2010, Klarman and Gutiérrez-Basulto, 2010].
L. Serafini et al. (DKM - FBK) A CKR for TOD Trento, July 30, 2014 4 / 39](https://image.slidesharecdn.com/opendatatnslides-141016100051-conversion-gate01/75/A-Contextualized-Knowledge-Repository-for-Open-Data-about-Trentino-5-2048.jpg)
![Metalanguage LG
Metavocabulary: G = NCG ] NRG ] NIG
N NIG: context names
M NIG: module names
C NCG: context classes, including class Ctx
R NRG: contextual relations
A NRG: contextual attributes
For A 2 A, a set DA NIG of attribute values of A
L. Serafini et al. (DKM - FBK) A CKR for TOD Trento, July 30, 2014 15 / 39](https://image.slidesharecdn.com/opendatatnslides-141016100051-conversion-gate01/75/A-Contextualized-Knowledge-Repository-for-Open-Data-about-Trentino-19-2048.jpg)
![Metalanguage LG
Metavocabulary: G = NCG ] NRG ] NIG
N NIG: context names
M NIG: module names
C NCG: context classes, including class Ctx
R NRG: contextual relations
A NRG: contextual attributes
For A 2 A, a set DA NIG of attribute values of A
Metalanguage LG: SROIQ-RL axioms over context expressions:
C := B j fcg jC1 u C2 jC1 t C2 j 9R.C1 j 9R.fcg j 9R.j 9A.fdAg j 9mod.fmg
D := B jD1 u D2 j :C1 j 8R.D1 j 9R.fcg j 9A.fdAg j 9mod.fmg j
6 nR.C1 j 6 nR.
E := B j E1 u E2 j 9R.fcg j 9A.fdAg j 9mod.fmg
L. Serafini et al. (DKM - FBK) A CKR for TOD Trento, July 30, 2014 15 / 39](https://image.slidesharecdn.com/opendatatnslides-141016100051-conversion-gate01/75/A-Contextualized-Knowledge-Repository-for-Open-Data-about-Trentino-20-2048.jpg)
![Metalanguage LG
Metavocabulary: G = NCG ] NRG ] NIG
N NIG: context names
M NIG: module names
C NCG: context classes, including class Ctx
R NRG: contextual relations
A NRG: contextual attributes
For A 2 A, a set DA NIG of attribute values of A
Metalanguage LG: SROIQ-RL axioms over context expressions:
C := B j fcg jC1 u C2 jC1 t C2 j 9R.C1 j 9R.fcg j 9R.j 9A.fdAg j 9mod.fmg
D := B jD1 u D2 j :C1 j 8R.D1 j 9R.fcg j 9A.fdAg j 9mod.fmg j
6 nR.C1 j 6 nR.
E := B j E1 u E2 j 9R.fcg j 9A.fdAg j 9mod.fmg
Individual variable this: c 2 N [ fthisg
L. Serafini et al. (DKM - FBK) A CKR for TOD Trento, July 30, 2014 15 / 39](https://image.slidesharecdn.com/opendatatnslides-141016100051-conversion-gate01/75/A-Contextualized-Knowledge-Repository-for-Open-Data-about-Trentino-21-2048.jpg)
![Object language LS
Object vocabulary: any DL vocabulary S = NCS ] NRS ] NIS
Eval expression
Given X an object expression in S and C a context expression in G
eval(X,C)
“The interpretation of X in all the contexts of type C”
Left-side only: “imports” meaning of X from all of the contexts in C
Object language LS: SROIQ-RL axioms over object expressions
Object language with references Le
S: extension with eval expressions
L. Serafini et al. (DKM - FBK) A CKR for TOD Trento, July 30, 2014 16 / 39](https://image.slidesharecdn.com/opendatatnslides-141016100051-conversion-gate01/75/A-Contextualized-Knowledge-Repository-for-Open-Data-about-Trentino-22-2048.jpg)
![Materialization calculus Kic
Materialization calculus Kic:
Calculus for instance checking in SROIQ-RL CKR
Extension to the CKR structure of materialization calculus for
SROEL of [Krötzsch, 2010]
Formalizes the operation of forward closure in implementation
Idea
Composed by 3 sets of rules:
Input rules I: translation of DL axioms to Datalog atoms
Deduction rules P: forward inference rules
Output rules O: translation for DL proved axiom
L. Serafini et al. (DKM - FBK) A CKR for TOD Trento, July 30, 2014 23 / 39](https://image.slidesharecdn.com/opendatatnslides-141016100051-conversion-gate01/75/A-Contextualized-Knowledge-Repository-for-Open-Data-about-Trentino-32-2048.jpg)
![CKR calculus in SPRINGLES: evaluation strategy
Composition of SPRINGLES primitives: parallel rule evaluation,
sequence, fixpoint, repeat (not used by CKR)
:closure-strategy
spr:sequenceOf ( :task_add_axioms :task_global_closure
:task_link_modules :task_ctx_closure ) .
:task_add_axioms
spr:evalOf (
:dep-glob :prp-ap :cls-thing :cls-nothing :dt-type ) .
:task_global_closure
spr:bind ?g_inf = ckr:global-inf ;
spr:fixPointOf [ spr:evalOf (
:pel-c-subc ... :pel-r-subrc :pgl-c-addmod
:pgl-i-addmod :pgl-c-submodc :pgl-c-subattc ) ] .
:task_link_modules
spr:evalOf ( :dep-local-i :dep-local-c ) .
:task_ctx_closure
spr:fixPointOf [ spr:evalOf (
:pel-c-subc ... :pel-r-subrc
:plc-c-subevalat :plc-c-subexeval ) ] .
Francesco Corcoglioniti (DKM - FBK) A CKR for TOD Trento, July 30, 2014 30 / 39](https://image.slidesharecdn.com/opendatatnslides-141016100051-conversion-gate01/75/A-Contextualized-Knowledge-Repository-for-Open-Data-about-Trentino-41-2048.jpg)
Uploaded byPlanetData Network of Excellence
A Contextualized Knowledge Repository for Open Data about Trentino
The document describes a Contextualized Knowledge Repository (CKR) framework for representing and reasoning with contextual knowledge on the Semantic Web. It discusses the need to make context explicit in the Semantic Web in order to represent knowledge that holds in specific contextual spaces like time, location, or topic. The CKR is presented as a formalism based on description logics that defines contexts as first-class objects and allows associating knowledge with contexts. It describes a prototype CKR implementation and outlines how a CKR could be used to represent open data about the Trentino region with contextual metadata.
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A Contextualized Knowledge Repository for Open Data about Trentino
- 1. A Contextualized KnowledgeRepository for Open Data about Trentino Loris Bozzato Gaetano Calabrese Luciano Serafini Data and Knowledge Management Research Unit, Fondazione Bruno Kessler, Trento, Italy Trento, July 30, 2014 L. Serafini et al. (DKM - FBK) A CKR for TOD Trento, July 30, 2014 1 / 39
- 2. Outline 1 Introduction:context in Semantic Web and Linked Open Data 2 Theory of contexts in AI 3 Contextualized Knowledge Repository (CKR) 4 Reasoning in CKR 5 CKR Prototype implementation 6 A CKR for Trentino Open Data L. Serafini et al. (DKM - FBK) A CKR for TOD Trento, July 30, 2014 2 / 39
- 3. Outline 1 Introduction:context in Semantic Web and Linked Open Data 2 Theory of contexts in AI 3 Contextualized Knowledge Repository (CKR) 4 Reasoning in CKR 5 CKR Prototype implementation 6 A CKR for Trentino Open Data L. Serafini et al. (DKM - FBK) A CKR for TOD Trento, July 30, 2014 3 / 39
- 4. Introduction and motivation Need for context in Semantic Web Most of Semantic Web data holds in specific contextual space (time, location, topic...) No explicit support for modelling and reasoning with context sensitive knowledge in SW (Often handcrafted in implementation) Ô Need for well-defined theory of contexts L. Serafini et al. (DKM - FBK) A CKR for TOD Trento, July 30, 2014 4 / 39
- 5. Introduction and motivation Need for context in Semantic Web Most of Semantic Web data holds in specific contextual space (time, location, topic...) No explicit support for modelling and reasoning with context sensitive knowledge in SW (Often handcrafted in implementation) Ô Need for well-defined theory of contexts Contextualized Knowledge Repository (CKR) DL based framework for representation and reasoning with contextual knowledge in the Semantic Web Contextual theory: based on formal AI theories of context [McCarthy, 1993, Lenat, 1998, Giunchiglia and Ghidini, 2001] Other DL contextual frameworks: [Bao et al., 2010, Klarman and Gutiérrez-Basulto, 2010]. L. Serafini et al. (DKM - FBK) A CKR for TOD Trento, July 30, 2014 4 / 39
- 6. Contextual modelling needs A study on typical use of context in SW lead us to the definition of a set of representation requirements: Requirements Statement contextualization: associate context to facts Symbols locality: local meaning for symbols Cross-context TBox statements: knowledge relations across contexts Complex contextualization: more than one contextual values to facts Modularity: separation of knowledge in independent modules Unified reasoning and query: inference and query use context structure . . . L. Serafini et al. (DKM - FBK) A CKR for TOD Trento, July 30, 2014 5 / 39
- 7. Contextual modelling needs A study on typical use of context in SW lead us to the definition of a set of representation requirements: Requirements Statement contextualization: associate context to facts Symbols locality: local meaning for symbols Cross-context TBox statements: knowledge relations across contexts Complex contextualization: more than one contextual values to facts Modularity: separation of knowledge in independent modules Unified reasoning and query: inference and query use context structure . . . L. Serafini et al. (DKM - FBK) A CKR for TOD Trento, July 30, 2014 5 / 39
- 8. Outline 1 Introduction:context in Semantic Web and Linked Open Data 2 Theory of contexts in AI 3 Contextualized Knowledge Repository (CKR) 4 Reasoning in CKR 5 CKR Prototype implementation 6 A CKR for Trentino Open Data L. Serafini et al. (DKM - FBK) A CKR for TOD Trento, July 30, 2014 6 / 39
- 9. Contextual knowledge representationand reasoning Every formula is asserted in a context, i.e., there is no absolute truth: ist(c1, Winner(Italy)) ist(c2, Winner(Spain)) L. Serafini et al. (DKM - FBK) A CKR for TOD Trento, July 30, 2014 7 / 39
- 10. Contextual knowledge representationand reasoning Every formula is asserted in a context, i.e., there is no absolute truth: ist(c1, Winner(Italy)) ist(c2, Winner(Spain)) Contexts are first class objects, and the logic provides terms to denote contexts, and formulas to predicate about contexts: is_about(c1, FifaWorldCup) time(c1, 2006) is_about(c2, FifaWorldCup) time(c2, 2010) is_about(c3, Football) time(c3, 2000 2010) disjoint(c1, c2) covers(c3, c1) covers(c3, c2) L. Serafini et al. (DKM - FBK) A CKR for TOD Trento, July 30, 2014 7 / 39
- 11. Contextual knowledge representationand reasoning Every formula is asserted in a context, i.e., there is no absolute truth: ist(c1, Winner(Italy)) ist(c2, Winner(Spain)) Contexts are first class objects, and the logic provides terms to denote contexts, and formulas to predicate about contexts: is_about(c1, FifaWorldCup) time(c1, 2006) is_about(c2, FifaWorldCup) time(c2, 2010) is_about(c3, Football) time(c3, 2000 2010) disjoint(c1, c2) covers(c3, c1) covers(c3, c2) knowledge propagates across contexts: 8x(ist(c1,Winner(x)) ! ist(c2.Team(x)) L. Serafini et al. (DKM - FBK) A CKR for TOD Trento, July 30, 2014 7 / 39
- 12. “Context as abox” representation paradigm a context is a theory—set of sentences in a logical language, closed under logical consequence—associated with a region in a contextual space; Location Time Topic South africa FIFA world cup Spain.Qualified.First Holland.Qualified.Second best_player(Cavani) ... 2010 L. Serafini et al. (DKM - FBK) A CKR for TOD Trento, July 30, 2014 8 / 39
- 13. Context as aBox C = time(C, 2010 06 14), location(C,World), topic(C, FIFA_WC_Match_11) TeamA(Team_Italy) TeamB(Team_Paraguay) Referee(Benito_Archundia) scored(Daniele_Derossi, 63) scored(Antolin_Alcaraz, 39) match_document(http : //www.fifa.com/mm/document/.../...5fstart.pdf ) match_document(http : //www.fifa.com/mm/document/.../...5lineup.pdf ) photo(http : //www.fifa.com/mm/pict/.../...xyz.jpg) . . . L. Serafini et al. (DKM - FBK) A CKR for TOD Trento, July 30, 2014 9 / 39
- 14. Contextual dimension FromDoug Lenat (CYC) TIME e.g.: 2001, 20/3/2009-20/3/2011,. . . TYPEOFTIME e.g., NightTime, DuringWorldWarII, . . . GEOLOCATION e.g. Italy, Spain, London, . . . TYPEOFPLACE e.g. Country, Office, Town, . . . CULTURE e.g., Political Culture, Democratic political culture, sport, . . . SOPHISTICATION/SECURITY who can access knowledge of this context? e.g, physicians, Manager, Human Resources stuff, . . . TOPIC what is a context about? Values are taken from topic classification systems GRANULARITY from molecular to cellular to organ to organism to society level MODALITY beliefs, agreements, expectations, memories, etc., ARGUMENT-PREFERENCE What is the (default) set of heuristics used in this context, to resolve pro/con argument clashes? JUSTIFICATION e.g., definitional, causal, statistical, appeals to intuition, by faith, by assumption, etc. DOMAIN ASSUMPTIONS . . . L. Serafini et al. (DKM - FBK) A CKR for TOD Trento, July 30, 2014 10 / 39
- 15. Contextual dimension Requirementsfrom the Semantic Web TIME information on when knowledge holds PROVENANCE information about the source from which knowledge comes from ACCESS CONTROL information on access rights on knowledge PROPOSITIONAL ATTITUDES beliefs and modalities VERSIONING/EVOLUTION information on how knowledge evolves TRUST information about bow reliable is the infomration contained in a context. generalizing. . . We develop a general logical framework that supports n dimensions. L. Serafini et al. (DKM - FBK) A CKR for TOD Trento, July 30, 2014 11 / 39
- 16. Outline 1 Introduction:context in Semantic Web and Linked Open Data 2 Theory of contexts in AI 3 Contextualized Knowledge Repository (CKR) 4 Reasoning in CKR 5 CKR Prototype implementation 6 A CKR for Trentino Open Data L. Serafini et al. (DKM - FBK) A CKR for TOD Trento, July 30, 2014 12 / 39
- 17. CKR introduction Thestructure of a CKR is composed by 2 layers: Global context Metaknowledge: structure of contexts, context classes, relations, modules and attributes (Global) object knowledge: object knowledge shared by all contexts (Local) contexts Object knowledge with references: local object knowledge with references to value of predicates in other contexts Knowledge distributed across different modules L. Serafini et al. (DKM - FBK) A CKR for TOD Trento, July 30, 2014 13 / 39
- 18. SROIQ-RL Restriction ofSROIQ to the syntax of OWL-RL axioms: Left-side concept C: C := Aj fag j C1 u C2 j C1 t C2 j 9R.C1 j 9R.fag j 9R. Right-side concept D: D := AjD1 u D2 j :C1 j 8R.D1 j 9R.fag j 6 nR.C1 j 6 nR. with n 2 f0, 1g Both-side concept E: E := Aj E1 u E2 j 9R.fag TBox axioms: C v D, E E ABox axioms: D(a), R(a, b) L. Serafini et al. (DKM - FBK) A CKR for TOD Trento, July 30, 2014 14 / 39
- 19. Metalanguage LG Metavocabulary:G = NCG ] NRG ] NIG N NIG: context names M NIG: module names C NCG: context classes, including class Ctx R NRG: contextual relations A NRG: contextual attributes For A 2 A, a set DA NIG of attribute values of A L. Serafini et al. (DKM - FBK) A CKR for TOD Trento, July 30, 2014 15 / 39
- 20. Metalanguage LG Metavocabulary:G = NCG ] NRG ] NIG N NIG: context names M NIG: module names C NCG: context classes, including class Ctx R NRG: contextual relations A NRG: contextual attributes For A 2 A, a set DA NIG of attribute values of A Metalanguage LG: SROIQ-RL axioms over context expressions: C := B j fcg jC1 u C2 jC1 t C2 j 9R.C1 j 9R.fcg j 9R.j 9A.fdAg j 9mod.fmg D := B jD1 u D2 j :C1 j 8R.D1 j 9R.fcg j 9A.fdAg j 9mod.fmg j 6 nR.C1 j 6 nR. E := B j E1 u E2 j 9R.fcg j 9A.fdAg j 9mod.fmg L. Serafini et al. (DKM - FBK) A CKR for TOD Trento, July 30, 2014 15 / 39
- 21. Metalanguage LG Metavocabulary:G = NCG ] NRG ] NIG N NIG: context names M NIG: module names C NCG: context classes, including class Ctx R NRG: contextual relations A NRG: contextual attributes For A 2 A, a set DA NIG of attribute values of A Metalanguage LG: SROIQ-RL axioms over context expressions: C := B j fcg jC1 u C2 jC1 t C2 j 9R.C1 j 9R.fcg j 9R.j 9A.fdAg j 9mod.fmg D := B jD1 u D2 j :C1 j 8R.D1 j 9R.fcg j 9A.fdAg j 9mod.fmg j 6 nR.C1 j 6 nR. E := B j E1 u E2 j 9R.fcg j 9A.fdAg j 9mod.fmg Individual variable this: c 2 N [ fthisg L. Serafini et al. (DKM - FBK) A CKR for TOD Trento, July 30, 2014 15 / 39
- 22. Object language LS Object vocabulary: any DL vocabulary S = NCS ] NRS ] NIS Eval expression Given X an object expression in S and C a context expression in G eval(X,C) “The interpretation of X in all the contexts of type C” Left-side only: “imports” meaning of X from all of the contexts in C Object language LS: SROIQ-RL axioms over object expressions Object language with references Le S: extension with eval expressions L. Serafini et al. (DKM - FBK) A CKR for TOD Trento, July 30, 2014 16 / 39
- 23. Contextualized Knowledge Repository Contextualized Knowledge Repository: K = hG, fKmgm2Mi G is a KB over G [ S, containing metalanguage axioms in LG or global object axioms in LS for every module name m 2 M, Km is a KB over S, containing object axioms with references in Le S L. Serafini et al. (DKM - FBK) A CKR for TOD Trento, July 30, 2014 17 / 39
- 24. A CKR forrepresenting provenance, access-control, and trust metadata (PlanetData EU Project L. Serafini et al. (DKM - FBK) A CKR for TOD Trento, July 30, 2014 18 / 39
- 25. Tourism example: introduction Tourism example: Idea: Tourism recommendation for events in Trentino Structure of contexts represent events and tourists information Ô Task: find interesting events on the base of tourists’ preferences We model this domain in a CKR Ktour = hG, fKmgm2Mi L. Serafini et al. (DKM - FBK) A CKR for TOD Trento, July 30, 2014 19 / 39
- 26. Tourism example: CKRstructure Event CulturalEvent SportEvent VolleyMatch VolleyA1 Competition Concert Tourist SportiveTourist CulturalTourist campionato_A1_2012-13 G trento_cuneo_120922 volley_fan_01 trento_latina_130203 modena_trento_130112 hasParentEvent L. Serafini et al. (DKM - FBK) A CKR for TOD Trento, July 30, 2014 20 / 39
- 27. Tourism example: CKRstructure Event CulturalEvent SportEvent VolleyMatch VolleyA1 Competition Concert Tourist SportiveTourist CulturalTourist campionato_A1_2012-13 G trento_cuneo_120922 volley_fan_01 trento_latina_130203 modena_trento_130112 m_sport_ev m_event m_v_match m_match1 m_match2 m_match3 m_tourist m_sp_tourist m_tourist01 hasParentEvent L. Serafini et al. (DKM - FBK) A CKR for TOD Trento, July 30, 2014 20 / 39
- 28. Tourism example: CKRstructure Event CulturalEvent SportEvent VolleyMatch VolleyA1 Competition Concert Tourist SportiveTourist CulturalTourist campionato_A1_2012-13 G trento_cuneo_120922 volley_fan_01 trento_latina_130203 modena_trento_130112 Kevent m_sport_ev m_event m_v_match m_match1 m_match2 m_match3 m_tourist m_sp_tourist m_tourist01 hasParentEvent Ksport_ev Kv_match Kmatch1 ... Ktourist01 L. Serafini et al. (DKM - FBK) A CKR for TOD Trento, July 30, 2014 20 / 39
- 29. Tourism example: somemodules contents In Kv_match: HomeTeam v Team HostTeam v Team Winner v Team Loser v Team In Kmatch2: HomeTeam(casa_modena_volley) HostTeam(itas_trentino_volley) Winner(casa_modena_volley) Loser(itas_trentino_volley) L. Serafini et al. (DKM - FBK) A CKR for TOD Trento, July 30, 2014 21 / 39
- 30. Tourism example: somemodules contents In Kv_match: HomeTeam v Team HostTeam v Team Winner v Team Loser v Team In Kmatch2: HomeTeam(casa_modena_volley) HostTeam(itas_trentino_volley) Winner(casa_modena_volley) Loser(itas_trentino_volley) ... In Ksport_ev: “Winners of major volley matches are top teams” eval(Winner,VolleyMatch u 9hasParentEvent.VolleyA1Competition) v TopTeam In Ksp_tourist: “Top teams are preferred teams” eval(TopTeam, SportEvent) v PreferredTeam L. Serafini et al. (DKM - FBK) A CKR for TOD Trento, July 30, 2014 21 / 39
- 31. Outline 1 Introduction:context in Semantic Web and Linked Open Data 2 Theory of contexts in AI 3 Contextualized Knowledge Repository (CKR) 4 Reasoning in CKR 5 CKR Prototype implementation 6 A CKR for Trentino Open Data L. Serafini et al. (DKM - FBK) A CKR for TOD Trento, July 30, 2014 22 / 39
- 32. Materialization calculus Kic Materialization calculus Kic: Calculus for instance checking in SROIQ-RL CKR Extension to the CKR structure of materialization calculus for SROEL of [Krötzsch, 2010] Formalizes the operation of forward closure in implementation Idea Composed by 3 sets of rules: Input rules I: translation of DL axioms to Datalog atoms Deduction rules P: forward inference rules Output rules O: translation for DL proved axiom L. Serafini et al. (DKM - FBK) A CKR for TOD Trento, July 30, 2014 23 / 39
- 33. Translation and deductionrules EL translation rules Iel(S, c) C(a)7! finst(a,C, c)g R(a, b)7! ftriple(a,R, b, c)g fag v C7! finst(a,C, c)g A v C7! fsubClass(A,C, c)g A u B v C7! fsubConj(A, B,C, c)g 9R.A v C7! fsubEx(R,A,C, c)g R v T7! fsubRole(R, T, c)g RS v T7! fsubRChain(R, S, T, c)g EL deduction rules Pel subClass(y, z, c), inst(x, y, c) ! inst(x, z, c) subConj(y1, y2, z, c), inst(x, y1, c), inst(x, y2, c) ! inst(x, z, c) subEx(v, y, z, c), triple(x, v, x0 , c), inst(x0 , y, c) ! inst(x, z, c) subRole(v,w, c), triple(x, v, x0 , c) ! triple(x,w, x0 , c) subRChain(u, v,w, c), triple(x, u, y, c), triple(y, v, z, c) ! triple(x,w, z, c) Output translation O(a, c) C(a)7! finst(a,C, c)g R(a, b)7! ftriple(a,R, b, c)g L. Serafini et al. (DKM - FBK) A CKR for TOD Trento, July 30, 2014 24 / 39
- 34. Translation and deductionrules Global rules Iglob(G) and Pglob C v 9mod.fmg7! fhasMod(C,m,gm)g C 2 C7! fsubClass(C, Ctx,gm)g C v 9A.fdg7! fhasAtt(C,A, d,gm)g c 2 N7! finst(c, Ctx,gm)g fcg v 9mod.fmg7! ftriple(c, mod,m,gm)g fcg v 9A.fdg7! ftriple(c,A, d,gm)g hasMod(c,m,gm), inst(x, c,gm) ! triple(x, mod,m,gm) hasAtt(c, a, d,gm), inst(x, c,gm) ! triple(x, a, d,gm) Local rules Iloc(S, c) and Ploc eval(A,C) v B7! fsubEval(A,C, B, c)g eval(R,C) v T7! fsubEvalR(R,C, T, c)g subEval(a, c1, b, c), inst(c0 , c1,gm), inst(x, a, c0) ! inst(x, b, c) subEvalR(r, c1, t, c), inst(c0 , c1,gm), triple(x, r, y, c0) ! triple(x, t, y, c) L. Serafini et al. (DKM - FBK) A CKR for TOD Trento, July 30, 2014 25 / 39
- 35. Outline 1 Introduction:context in Semantic Web and Linked Open Data 2 Theory of contexts in AI 3 Contextualized Knowledge Repository (CKR) 4 Reasoning in CKR 5 CKR Prototype implementation 6 A CKR for Trentino Open Data L. Serafini et al. (DKM - FBK) A CKR for TOD Trento, July 30, 2014 26 / 39
- 36. CKR Prototype: introduction The prototype extends the Sesame Java framework with three modules: CKR core – CKR implementation on top of a Sesame RDF store knowledge addition/removal closure materialization SPARQL 1.1 queries transactions CKR server – extension of Sesame Server Workbench exposes CKR primitives includes a SPARQL endpoint includes an admin UI CKR client – library to access a CKR from a remote Java application Client JVM Client application CKR API CKR client Sesame HTTP API CKR core RDF store (Sesame native, memory, OWLIM, Bigdata) Server JVM SPARQL client CKR server persistent storage Web browser may embed in Java apps. CKR API SAIL API SPARQL endpoint Admin interface Francesco Corcoglioniti (DKM - FBK) A CKR for TOD Trento, July 30, 2014 27 / 39
- 37. SPRINGLES CKR Coreis implemented on top of SPRINGLES: SParql-based Rule Inference over Named Graphs Layer Extending Sesame CKR API add triple to context CKR Core CKR implementation add triple to graph SPRINGLES RDF store SAIL API SAIL API CKR rules add triple; eval. rules and add inferences SPRINGLES features: transparent/on-demand closure materialization based on rules rules encoded as SPARQL queries addressing Named Graphs (NG) customizable rule evaluation strategy Why SPRINGLES: no inference over NGs in RDF stores Why SPARQL: exploits optimized query engines can scale to large KBs (cf. RETE) Francesco Corcoglioniti (DKM - FBK) A CKR for TOD Trento, July 30, 2014 28 / 39
- 38. CKR calculus inSPRINGLES: rule example :pel-c-subc a spr:Rule ; spr:head GRAPH ?mx { ?x rdf:type ?z } ; spr:body GRAPH ?m1 { ?y rdfs:subClassOf ?z } GRAPH ?m2 { ?x rdf:type ?y } GRAPH sys:dep { ?mx sys:derivedFrom ?m1,?m2 } FILTER NOT EXISTS { GRAPH ?m0 { ?x rdf:type ?z } GRAPH sys:dep { ?mx sys:derivedFrom ?m0 } } . Context C ckr:hasModule ckr:hasModule . . . triples in ckr:global ?x rdf:type ?y ?y rdfs:subClassOf ?z Module ?m1 Module ?m2 Francesco Corcoglioniti (DKM - FBK) A CKR for TOD Trento, July 30, 2014 29 / 39
- 39. CKR calculus inSPRINGLES: rule example :pel-c-subc a spr:Rule ; spr:head GRAPH ?mx { ?x rdf:type ?z } ; spr:body GRAPH ?m1 { ?y rdfs:subClassOf ?z } GRAPH ?m2 { ?x rdf:type ?y } GRAPH sys:dep { ?mx sys:derivedFrom ?m1,?m2 } FILTER NOT EXISTS { GRAPH ?m0 { ?x rdf:type ?z } GRAPH sys:dep { ?mx sys:derivedFrom ?m0 } } . Context C . . . triples in ckr:global triples in sys:dep ?x rdf:type ?y ?y rdfs:subClassOf ?z ckr:hasModule sys:closureOf ckr:hasModule ckr:hasModule sys:derivedFrom sys:derivedFrom Module ?m1 Module ?m2 Module ?mx Francesco Corcoglioniti (DKM - FBK) A CKR for TOD Trento, July 30, 2014 29 / 39
- 40. CKR calculus inSPRINGLES: rule example :pel-c-subc a spr:Rule ; spr:head GRAPH ?mx { ?x rdf:type ?z } ; spr:body GRAPH ?m1 { ?y rdfs:subClassOf ?z } GRAPH ?m2 { ?x rdf:type ?y } GRAPH sys:dep { ?mx sys:derivedFrom ?m1,?m2 } FILTER NOT EXISTS { GRAPH ?m0 { ?x rdf:type ?z } GRAPH sys:dep { ?mx sys:derivedFrom ?m0 } } . Context C ckr:hasModule ckr:hasModule sys:derivedFrom . . . ckr:hasModule sys:closureOf sys:derivedFrom triples in ckr:global triples in sys:dep inference ?x rdf:type ?y ?y rdfs:subClassOf ?z ?x rdf:type ?z Module ?m1 Module ?m2 Module ?mx Francesco Corcoglioniti (DKM - FBK) A CKR for TOD Trento, July 30, 2014 29 / 39
- 41. CKR calculus inSPRINGLES: evaluation strategy Composition of SPRINGLES primitives: parallel rule evaluation, sequence, fixpoint, repeat (not used by CKR) :closure-strategy spr:sequenceOf ( :task_add_axioms :task_global_closure :task_link_modules :task_ctx_closure ) . :task_add_axioms spr:evalOf ( :dep-glob :prp-ap :cls-thing :cls-nothing :dt-type ) . :task_global_closure spr:bind ?g_inf = ckr:global-inf ; spr:fixPointOf [ spr:evalOf ( :pel-c-subc ... :pel-r-subrc :pgl-c-addmod :pgl-i-addmod :pgl-c-submodc :pgl-c-subattc ) ] . :task_link_modules spr:evalOf ( :dep-local-i :dep-local-c ) . :task_ctx_closure spr:fixPointOf [ spr:evalOf ( :pel-c-subc ... :pel-r-subrc :plc-c-subevalat :plc-c-subexeval ) ] . Francesco Corcoglioniti (DKM - FBK) A CKR for TOD Trento, July 30, 2014 30 / 39
- 42. Outline 1 Introduction:context in Semantic Web and Linked Open Data 2 Theory of contexts in AI 3 Contextualized Knowledge Repository (CKR) 4 Reasoning in CKR 5 CKR Prototype implementation 6 A CKR for Trentino Open Data Francesco Corcoglioniti (DKM - FBK) A CKR for TOD Trento, July 30, 2014 31 / 39
- 43. Import in RDFStore OpenDataTN Data Package page Datasets Download Francesco Corcoglioniti (DKM - FBK) A CKR for TOD Trento, July 30, 2014 32 / 39
- 44. Import in RDFStore OpenDataTN Data Package page Datasets Download RDF CSV JSON XML Package Metadata Francesco Corcoglioniti (DKM - FBK) A CKR for TOD Trento, July 30, 2014 32 / 39
- 45. Import in RDFStore OpenDataTN Data Package page Datasets Download RDF CSV JSON XML Package Metadata Local storage Francesco Corcoglioniti (DKM - FBK) A CKR for TOD Trento, July 30, 2014 32 / 39
- 46. Import in RDFStore OpenDataTN Data Package page Datasets Download Package Metadata RDF Mapping + RDF conversion RDF CSV JSON XML Local storage Francesco Corcoglioniti (DKM - FBK) A CKR for TOD Trento, July 30, 2014 32 / 39
- 47. Import in RDFStore OpenDataTN Data Package page Datasets Download Package Metadata RDF Store Import RDF Mapping + RDF conversion RDF CSV JSON XML Local storage Francesco Corcoglioniti (DKM - FBK) A CKR for TOD Trento, July 30, 2014 32 / 39
- 48. Francesco Corcoglioniti (DKM- FBK) A CKR for TOD Trento, July 30, 2014 33 / 39
- 49. Francesco Corcoglioniti (DKM- FBK) A CKR for TOD Trento, July 30, 2014 34 / 39
- 50. Metalevel structure Package p_biblioteche Dataset hasMember d_biblioteche 07/08/14 hasCreationDate hasTag libri Francesco Corcoglioniti (DKM - FBK) A CKR for TOD Trento, July 30, 2014 35 / 39
- 51. Metalevel structure Package hasCreationDate p_biblioteche Dataset hasMember 07/08/14 hasTag libri d_biblioteche Mapping Activity d_biblioteche_ma usedFile usedMap wasGeneratedByMapping SourceFile MappingFile d_biblioteche_json d_biblioteche_map Francesco Corcoglioniti (DKM - FBK) A CKR for TOD Trento, July 30, 2014 35 / 39
- 52. RDF store measures RDF Store measures: Total of imported datasets: 2078 RDF: 157 JSON: 799 CSV: 1122 Number of asserted and inferred triples: 21,201,011 Francesco Corcoglioniti (DKM - FBK) A CKR for TOD Trento, July 30, 2014 36 / 39
- 53. Query interface Queryinterface REST GET request REST interface SPARQL 1.1 MetaReasons Server RDF Store Francesco Corcoglioniti (DKM - FBK) A CKR for TOD Trento, July 30, 2014 37 / 39
- 54. Thank you forlistening OpenData Trentino Repository Loris Bozzato, Gaetano Calabrese, Luciano Serafini https://dkm.fbk.eu/ DKM - Data and Knowledge Management Research Unit, FBK-Irst, Fondazione Bruno Kessler - Trento, Italy Francesco Corcoglioniti (DKM - FBK) A CKR for TOD Trento, July 30, 2014 38 / 39
- 55. References I Bao,J., Tao, J., and McGuinness, D. (2010). Context representation for the semantic web. In Procs. of WebSci10. Giunchiglia, F. and Ghidini, C. (2001). Local Models Semantics, or Contextual Reasoning = Locality + Compatibility. Artificial Intelligence, 127:2001. Klarman, S. and Gutiérrez-Basulto, V. (2010). ALCALC : a context description logic. In JELIA. Krötzsch, M. (2010). Efficient Inferencing for OWL EL. In JELIA 2010, volume 6341 of Lecture Notes in Computer Science, pages 234–246. Springer. Lenat, D. (1998). The Dimensions of Context Space. Technical report, CYCorp. Published online http://www.cyc.com/doc/context-space.pdf (accessed June 21, 2009). McCarthy, J. (1993). Notes on formalizing context. In IJCAI. Francesco Corcoglioniti (DKM - FBK) A CKR for TOD Trento, July 30, 2014 39 / 39