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www.iks-project.eu
Co-funded by the European Union
Semantic CMS Community
Project Review Meeting Luxemburg, 14-03-2013
Knowledge Representation and Reasoning with Apache Stanbol
Andrea Nuzzolese [email protected]
STLab, ISTC-CNR Italy
www.iks-project.eu
What does KR and Reasoning layer provide to Sanbol?
� Services used to define and manipulate semantic data models in the CMS � i.e., Ontology Network Manager component
� Services able to retrieve additional semantic information about content � i.e., Reaoners and Rules components
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Ontology Network Manager: motivations
� To enable a more scalable reasoning by � activating only parts of the knowledge that is really needed
by the application � limiting the scope of specific reasoning tasks.
� To distinguish between core and volatile knowledge � core knowledge describes the semantic domain of the
CMS � volatile knowledge can be any knowledge coming from
external services, or extracted from contents etc.
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Ontology Network Manager
� The Ontology Network Manager provides a controlled environment for managing ontology networks
� An ontology network is “a collection of ontologies related together through a variety of different relationships such as mapping, modularization, and versioning.” [NeOn D1.1.5 Haase et. al]
� The ONM provides API and REST services for constructing ontology networks and maintaining connectivity at runtime
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Ontology networks in Stanbol
� The ONM relies on two types of artifacts for constructing ontology networks � Scope:
� a shared artifacts within the CMS for collecting all the persistent knowledge.
� can be seen as a "logical realm" for the ontologies that encompass a certain CMS-related set of concepts
e.g., "User", "Event", "Content”, "Community”,
� Session : � a shared artifact for volatile knowledge
e.g., knowledge extracted on-the-fly from content
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Scopes and sessions in th Ontology Network Manager
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Ontology Network Manager REST services
� /ontonet/ontology/{scopeName} � - {scopeName} list (GET), delete (DELETE) all registered
and/or active ontology scopes � + {scopeName} get or activate, delete or deactivate, create
(PUT) and update (POST) the ontology of the scope identified by {scopeName}
� ontonet/session/{id} � - {id} get, delete all registered ontology sessions � + {id} get, delete, create (PUT) and update (POST) the
ontology session identified by {id}
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Stanbol Rules
� Stanbol Rules is the component that supports the
construction and the management of inference rules within Stanbol
� Stanbol Rules provide an additional layer and a syntax for
expressing business logics by means of axioms � The management of rules is performed through HTTP REST
services
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Rules and Recipes
� Rules are organized into a logic container called recipe
� A recipe identifies a set of rules that share the same business logic � e.g., integrity check of data, Search Engine Optimizaion
� Rules within a recipe are interpreted and executed as a whole
� A rule can be shared by different recipes
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Stanbol Rules: some usage scenario
� Integrity check from data fusion � the CMS administrator can define integrity checks for data
fetched from heterogeneous and external sources in order to prevent unwanted formats or inconsistent data
� Vocabulary harmonization � Rules can be used for the alignment of external data
representation to internal one (managed via the Ontology Network Manager)
� DL reasoning � Rules can be used as axioms for inferring new knowledge
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Stanbol Rules adapters � Stanbol Rules are expressed by using the Stanbol Rule
language
� By need, rules are converted at runtime to the format required by a concrete rule engine
� By default, a list of rule adapters is provided � i.e., SWRL for DL reasoning through OWL API, Jena
Rules, Clerezza SPARQL Constructs, pure SPARQL Constructs
� Adapters can be easily extended by implementing the provided interface
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The rule language
� The rule syntax synoptic is
ruleName[body -> head] � The rule name uniquely identifies a rule � The body and head consist of a set of conjunctive atoms
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Core rule atoms
� Core atoms are � Class assertion
� i.e., is(classPredicate, argument) � Individual assertion
� i.e., has(properyPredicate, arg1, arg2) � Data value assertion
� i.e., values(properyPredicate, arg1, arg2)
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Additional rule atoms
� Comparison � e.g., same(arg1, arg2), greaterThan(arg1, arg2)
� String manipulation � e.g., concat(arg1, arg2), lowercase(arg)
� Arithmetical atoms � e.g., sum(arg1, arg2), mult(arg1, arg2)
� Production atoms � e.g., newIRI(arg1, arg2), newLiteral(arg1, arg2)
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A rule example prefix myont = <http://www.foo.org/myont.owl#> . uncleRule[
is(myont:Human, ?x) . has(myont:hasParent, ?x, ?z) . has(myont:hasSibling, ?z, ?y) -> has(myont:hasUncle, ?x, ?y)
]
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Rules REST services
� /rule � get, create (POST), and delete rules into the rule store
� /recipe � get, create (PUT), add rules into (POST), and delete a
recipe
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Stanbol Reasoners
� Common REST wrapper around available reasoners
� Provides a default reasoner based on Jena
� Other reasoners can be plugged through the OWLLink protocol
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Reasoning services � Currently implemented services are
� consistency checking � classification � enrichment � refactoring
� Inputs for reasoning are ontology networks and rules recipes
� Supported different reasoners and reasoning configuration in parallel
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Dealing with big data reasoning
� Reasoning with big data is performed by means of jobs through HTTP services
� A job is associated to an ID
� The status of a job can be queried through REST API
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Reasoners REST services
� Services for classification, consistency checking and enrichment � /reasoners/rdfs: based on RDFS � /reasoners/owlmini: by default based on Jena OWLMini
reasoner. � /reasoners/owl: by default based on Jena OWL reasoner.
� Refactoring services � /refactor/apply
� Managing reasoning jobs � /jobs/{jid}
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About adoption � Netlab
� Adoption of the Ontology Manager and Rules for storing ontologies and enabling reasoning
� InSideOut10 � WordLift plug-in for WordPress based on Rules for
enabling schema.org compliant content
� Acuity Unlimited � KR&R enables reasoning services to assist Fedora
Commons repository managers acquire and manage semantic metadata about their contents
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DEMO
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Thank you
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