Session 48 - Principles of Semantic metadata management
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    Session 48 - Principles of Semantic metadata management Session 48 - Principles of Semantic metadata management Presentation Transcript

    • Principles and Foundations of Ontologies and Semantic Grids Session 48. July 15th, 2009 Oscar Corcho (Universidad Politécnica de Madrid) Work distributed under the license Creative Commons Attribution-Noncommercial-Share Alike 3.0
    • Overview • Motivation – Introduction – What is the Semantic Web – Semantic Web Technologies • RDF, RDF Schema and OWL • Semantic-OGSA (S-OGSA) – S-OGSA Reference Model and Capabilities – S-OGSA Mechanisms and Interaction Patterns – Sample Deployments of S-OGSA • Credits
    • A Satellite Scenario Space Segment SATELLITE FILES: Ground DMOP files Segment Product files 3
    • A Sample File in the Satellite Domain METADATA DATA
    • Metadata can be present in file names…  Namefile (Product): RA2_MW__1PNPDK20060201_120535_0000000 62044_00424_20518_0349.N1" Corresponds to: 5
    • …and in file headers FILE ; DMOP (generated by FOS Mission Planning System) RECORD fhr RECORD ID FILENAME="DMOP_SOF__VFOS20060124_103709_00000000_00001215_20060131_01 4048_20060202_035846.N1" DESTINATION="PDCC" PHASE_START=2 CYCLE_START=44 REL_START_ORBIT=404 RECORD parameters ABS_START_ORBIT=20498 ENDRECORD fhr ................................ RECORD dmop_er RECORD dmop_er_gen_part RECORD gen_event_params RECORD parameters EVENT_TYPE=RA2_MEA corresponding to other RECORD EVENT_ID="RA2_MEA_00000000002063" structure. NB_EVENT_PR1=1 NB_EVENT_PR3=0 ORBIT_NUMBER=20521 ELAPSED_TIME=623635 DURATION=41627862 ENDRECORD gen_event_params ENDRECORD dmop_er ENDLIST all_dmop_er ENDFILE
    • Metadata in Workflows ID MURA_BACSU STANDARD; PRT; 429 AA. DE PROBABLE UDP-N-ACETYLGLUCOSAMINE 1-CARBOXYVINYLTRANSFERASE DE (EC 2.5.1.7) (ENOYLPYRUVATE TRANSFERASE) (UDP-N-ACETYLGLUCOSAMINE DE ENOLPYRUVYL TRANSFERASE) (EPT). GN MURA OR MURZ. OS BACILLUS SUBTILIS. OC BACTERIA; FIRMICUTES; BACILLUS/CLOSTRIDIUM GROUP; BACILLACEAE; OC BACILLUS. KW PEPTIDOGLYCAN SYNTHESIS; CELL WALL; TRANSFERASE. FT ACT_SITE 116 116 BINDS PEP (BY SIMILARITY). FT CONFLICT 374 374 S -> A (IN REF. 3). SQ SEQUENCE 429 AA; 46016 MW; 02018C5C CRC32; MEKLNIAGGD SLNGTVHISG AKNSAVALIP ATILANSEVT IEGLPEISDI ETLRDLLKEI GGNVHFENGE MVVDPTSMIS MPLPNGKVKK LRASYYLMGA MLGRFKQAVI GLPGGCHLGP RPIDQHIKGF EALGAEVTNE QGAIYLRAER LRGARIYLDV VSVGATINIM LAAVLAEGKT IIENAAKEPE IIDVATLLTS MGAKIKGAGT NVIRIDGVKE LHGCKHTIIP DRIEAGTFMI
    • Metadata and workflows • Metadata for describing workflow entities – What is the value added of a given workflow? – What is the task a given service performs? – What are the services that can be associated with a processor? • Metadata for describing workflow provenance – How did the execution of a given workflow go? – What this the semantics of a data product? – How many invocations of a given service failed?
    • Workflow Lifecycle Workflow Reuse and Component Libraries Data, Data Products Metadata Catalogs Populate Adapt, Workflow with data Modify Template Workflow Data, Metadata, Instance Provenance Information Executable Map to Execute Workflow available Resource, resources Application Component Compute, Descriptions Storage and Network Resources Slide from Gaurang Mehta (presented at ISSGC2008 session 44
    • What can we do with metadata?
    • Metadata is everywhere • We can attach metadata almost to anything – Events, notifications, logs – Services and resources – Schemas and catalogue entries – People, meetings, discussions, conference talks – Scientific publications, recommendations, quality comments – Models, codes, builds, workflows, – Data files and data streams – Sensors and sensor data • But..., what do we mean by metadata???
    • What is the metadata of this HTML fragment? Based on Dublin Core The contributor and creator is the flight booking service “www.flightbookings.com”. The date would be January 1st, 2003, in case that the HTML page has been generated on that specific date. The description would be something like “flight details for a travel between Madrid and Seattle via Chicago on February 8th, 2004”. The document format is “HTML”. The document language is “en”, which stands for English Based on thesauri Madrid is a reference to the term with ID 7010413 in the thesaurus, which refers to the city of Madrid in Spain. Spain is a reference to the term with ID 1000095, which refers to the kingdom of Spain in Europe. Chicago is a reference to the term with ID 7013596, which refers to the city of Chicago in Illinois, US. United States of America is a reference to the term “United States” with ID 7012149, which refers to the US nation. Seattle is a reference to the term with ID 7014494, which refers to the city of Seattle in Washington, US. Based on ontologies Concept instances relate a part of the document to one or several concepts in an ontology. For example, “Flight details” may represent an instance of the concept Flight, and can be named as AA7615_Feb08_2003, although concept instances do not necessarily have a name. Attribute values relate a concept instance with part of the document, which is the value of one of its attributes. For example, “American Airlines” can be the value of the attribute companyName. Relation instances that relate two concept instances by some domain-specific relation. For example, the flight AA7615_Feb08_2003 and the location Madrid can be connected by the relation departurePlace
    • Need to Add “Semantics” • External agreement on meaning of annotations – E.g., Dublin Core for annotation of library/bibliographic information • Use Ontologies to specify meaning of annotations – Ontologies provide a vocabulary of terms, plus – a set of explicit assumptions regarding the intended meaning of the vocabulary. • Almost always including concepts and their classification • Almost always including properties between concepts • Similar to an object oriented model – Meaning (semantics) of terms is formally specified – Can also specify relationships between terms in multiple ontologies • Thus, an ontology describes a formal specification of a certain domain: – Shared understanding of a domain of interest – Formal and machine manipulable model of a domain of interest
    • Types of vocabularies. Formality Lassila O, McGuiness D. The Role of Frame-Based Representation on the Semantic Web. Technical Report. Knowledge Systems Laboratory. Stanford University. KSL-01-02. 2001. 14
    • Some metadata about a workflow Reference Ontology1 Metadata content RDF annotations A scientific workflow Reference Ontology2 Social Tags annotations Reference Controlled vocabulary Free-text annotations
    • Overview • Motivation – Introduction – What is the Semantic Web – Semantic Web Technologies • RDF, RDF Schema and OWL • Semantic-OGSA (S-OGSA) – S-OGSA Reference Model and Capabilities – S-OGSA Mechanisms and Interaction Patterns – Sample Deployments of S-OGSA • Credits
    • What is the Semantic Web • An extension of the current Web… – … where information and services are given well-defined and explicitly represented meaning, … – … so that it can be shared and used by humans and machines, ... – ... better enabling them to work in cooperation • How? – Promoting information exchange by tagging web content with machine processable descriptions of its meaning. – And technologies and infrastructure to do this
    • Overview • Motivation (45 minutes) – Introduction – What is the Semantic Web – Semantic Web Technologies • RDF, RDF Schema and OWL • Semantic-OGSA (S-OGSA) (45 minutes) – S-OGSA Reference Model and Capabilities – S-OGSA Mechanisms and Interaction Patterns – Sample Deployments of S-OGSA • Credits
    • Ontology Languages • Work on Semantic Web has concentrated on the definition of a collection or “stack” of languages. – Used to support the representation and use of metadata – Basic machinery that we can use to represent the extra semantic information needed for the Semantic Web Inference OWL Integration Integration RDFS RDF(S) Annotation RDF Reasoning over the information we have Could be light-weight (taxonomy) XML Could be heavy-weight (logic-style) Integrating information sources Associating metadata to resources (bindings)
    • RDF • RDF stands for Resource Description Framework • It is a W3C Recommendation – http://www.w3.org/RDF • RDF is a graphical formalism ( + XML syntax + semantics) – for representing metadata – for describing the semantics of information in a machine- accessible way • Provides a simple data model based on triples.
    • The RDF Data Model • Statements are <subject, predicate, object> triples: – <Oscar,presents,Session48> • Can be represented as a graph: presents Oscar Session48 • Statements describe properties of resources • A resource is any object that can be pointed to by a URI – The generic set of all names/addresses that are short strings that refer to resources – a document, a picture, a paragraph on the Web, http://www.dia.fi.upm.es/~ocorcho/index.html, a book in the library, a real person, isbn://0141184280 – Do not mistake them for Grid resources, though they could be the same, as we will see later in this talk!! • Properties themselves are also resources (URIs)
    • Linking Statements • The subject of one statement can be the object of another • Such collections of statements form a directed, labeled graph “Oscar Corcho” hasName presents Oscar Session48 preparedBy hasHomePage preparedBy Pinar http://www.iceage-eu.org/issgc09 • The object of a triple can also be a “literal” (a string)
    • RDF Syntax • RDF has an XML syntax that has a specific meaning: • Every Description element describes a resource • Every attribute or nested element inside a Description is a property of that Resource • We can refer to resources by URIs <rdf:Description rdf:about="some.uri/person#ocorcho"> <o:presents rdf:resource="some.uri/session#Session48"/> <o:hasName rdf:datatype="&xsd;string">Oscar Corcho</o:hasName> </rdf:Description> <rdf:Description rdf:about="some.uri/session#Session48"> <o:hasHomePage>http://www.iceage-eu.org/issgc09/programme.cfm </o:hasHomePage> <o:preparedBy rdf:resource=“some.uri/person#ocorcho"> <o:preparedBy rdf:resource=“some.uri/person#pinar_alper"> </rdf:Description>
    • What does RDF give us? • Single (simple) data model. • Syntactic consistency between names (URIs). • A mechanism for annotating data and resources. • Low level integration of data. Inference OWL Integration Integration RDFS RDF(S) Annotation RDF XML
    • What doesn’t RDF give us? • RDF does not give any special meaning to vocabulary – Such as subClassOf or type (supporting OO-style modelling) • So, what’s the difference between this graph... “Oscar Corcho” hasName presents Oscar Session48 preparedBy • ... and this one? “Oscar Corcho” isAlsoKnownAs talksIn Oscar Session48 presentedBy
    • RDFS: RDF Schema • RDF Schema is another W3C Recommendation – http://www.w3.org/TR/rdf-schema/ • It extends RDF with a schema vocabulary that allows you to define basic vocabulary terms and the relations between those terms – Class, type, subClassOf, – Property, subPropertyOf, range, domain – it gives “extra meaning” to particular RDF predicates and resources – this “extra meaning”, or semantics, specifies how a term should be interpreted • The combination of RDF and RDF Schema is normally known as RDF(S)
    • RDFS simple example <?xml version="1.0" encoding="UTF-8"?> <rdf:RDF xml:base="http://www.ontogrid.net/StickyNote#" xmlns="http://www.ontogrid.net/StickyNote#" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#"> <rdfs:Class rdf:ID="Event"> <rdfs:subClassOf rdf:resource="http://www.w3.org/2002/07/owl#Thing"/> </rdfs:Class> <rdfs:Class rdf:ID="Local_Event"> <rdfs:subClassOf rdf:resource="#Event"/> </rdfs:Class> eventDate xsd:date <rdfs:Class rdf:ID="Regional_Event"> <rdfs:subClassOf rdf:resource="#Event"/> </rdfs:Class> Event <rdfs:Class rdf:ID="Personal_Event"> subClassOf subClassOf <rdfs:subClassOf rdf:resource="#Event"/> subClassOf </rdfs:Class> <rdfs:Class rdf:ID="Person"> Personal_Event Local_Event Regional_Event <rdfs:subClassOf rdf:resource="http://www.w3.org/2002/07/owl#Thing"/> </rdfs:Class> <rdfs:Class rdf:ID="Professor"> <rdfs:subClassOf rdf:resource="#Person"/> </rdfs:Class> involves <rdfs:Class rdf:ID="Researcher"> Person <rdfs:subClassOf rdf:resource="#Person"/> subClassOf subClassOf </rdfs:Class> <rdf:Property rdf:ID="involves"> <rdfs:domain rdf:resource="#Personal_Event"/> Professor Researcher <rdfs:range rdf:resource="#Person"/> </rdf:Property> <rdf:Property rdf:ID="eventDate"> <rdfs:domain rdf:resource="#Event"/> <rdfs:range rdf:resource="http://www.w3.org/2001/XMLSchema#date"/> </rdf:Property> </rdf:RDF>
    • RDF(S) Inference rdfs:Class rdf:type Person rdf:type rdfs:subClassOf rdf:type Academic rdfs:subClassOf rdf:subClassOf Lecturer
    • RDF(S) Inference rdfs:Class rdf:type Academic rdf:type rdfs:subClassOf Lecturer rdf:type rdf:type Oscar
    • What does RDFS give us? • Ability to use simple schema/vocabularies to describe our resources • Consistent vocabulary use and sharing • Simple inference • Query mechanisms: SPARQL, SeRQL, RDQL, … – SELECT N FROM {N} rdf:type {sti:Event} USING NAMESPACE sti=<http://www.ontogrid.net/StickyNote#> • Examples – CS AktiveSpace • Lightweight schema to integrate data from University sites – myExperiment • Workflow descriptions for e-Science
    • What doesn’t RDFS give us? • RDFS is too weak to describe resources in sufficient detail – No localised range and domain constraints • Can’t say that the range of hasEducationalMaterial is Slides when applied to TheoreticalSession and Code when applied to HandsonSession – TheoreticalSession hasEducationalMaterial Slides – HandsonSession hasEducationalMaterial Code – No existence/cardinality constraints • Can’t say: – Sessions must have some EducationalMaterial – Sessions have at least one Presenter – No transitive, inverse or symmetrical properties • Can’t say that presents is the inverse property of isPresentedBy
    • The OWL Family Tree DAML RDF/RDF(S) DAML-ONT Joint EU/US Committee DAML+OIL OWL Frames OIL W3C OntoKnowledge+Others Description Logics
    • OWL • W3C Recommendation (February 2004) • A family of Languages – OWL Full – OWL DL – OWL Lite • Moving into a new W3C Recommendation (OWL 2) • Formal semantics – Description Logics (DL/Lite) – Relationship with RDF
    • OWL Ontology Example BioPAX Biochemical Reaction OWL Instances (schema) (Individuals) (data) Courtesy Joanne Luciano phosphoglucose isomerase 5.3.1.9 K Wolstencroft, A Brass, I Horrocks, P. Lord, U Sattler, R Stevens, D Turi A little semantics goes a long way in Biology Proc 4th ISWC 2005
    • OWL Basics (on top of RDF and RDFS) • Set of constructors for concept expressions – Booleans: and/or/not • A Session is a TheoreticalSession or a HandsonSession • Slides are not the same as Code – Quantification: some/all • Sessions must have some EducationalMaterial • Sessions can only have Presenters that have developed Grid applications or Grid middleware • Axioms for expressing constraints – Necessary and Sufficient conditions on classes • A Session that hasEducationalMaterial Code is a HandsonSession. – Disjointness • TheoreticalSessions are disjoint with HandsonSessions – Property characteristics: transitivity, inverse
    • Reasoning Tasks • OWL DL based on a well understood Description Logic (SHOIN(Dn)) – Formal properties well understood (complexity, decidability) – Known reasoning algorithms – Implemented systems (highly optimised) • Because of this, we can reason about OWL ontologies – Subsumption reasoning • Allows us to infer when one class is a subclass of another • Can then build concept hierarchies representing the taxonomy. • This is classification of classes. – Satisfiability reasoning • Tells us when a concept is unsatisfiable – i.e. when it is impossible to have instances of the class. • Allows us to check whether our model is consistent. – Instance Retrieval/Instantiation • What are the instances of a particular class C? • What are the classes that x is an instance of?
    • Reasoning Tasks. Classification
    • What does OWL give us? • Ability to use complex schema/vocabularies to describe our resources. • Consistent vocabulary use and sharing. • Robust data integration techniques • Complex inference and several reasoning functions • Query mechanisms: OWL QL
    • Overview • Motivation – Introduction – What is the Semantic Web – Semantic Web Technologies • RDF, RDF Schema and OWL • Semantic-OGSA (S-OGSA) – S-OGSA Reference Model and Capabilities – S-OGSA Mechanisms and Interaction Patterns – Sample Deployments of S-OGSA • Credits
    • The motivation behind S-OGSA • Metadata deserves a better treatment – In most cases it appears together with files or other resources – It is difficult to deal with – What about trying to query about all the files that deal with instrument X and where the information was taken from time T1 to T2? Our goal: Let’s make metadata a FIRST-CLASS CITIZEN in our systems And let’s make it FLEXIBLE to changes
    • Introduction. Semantic-OGSA • Semantic-OGSA (S-OGSA) is... – A Semantic Grid architecture – A low-impact extension of OGSA • Mixed ecosystem of Grid and Semantic Grid services – Services ignorant of semantics – Services aware of semantics but unable to process them – Services aware of semantics and able to process (part of) them • Everything is OGSA compliant – Defined by • Information model Model – New entities provide/ • Capabilites expose consume – New functionalities • Mechanisms – How it is delivered Capabilities Mechanisms use
    • S-OGSA Model
    • S-OGSA Model Example METADATA as Semantic Annotations
    • S-OGSA Model. Grid Entities • We can attach Semantic Bindings to anything – Events, notifications, logs – Services and resources – Schemas and catalogue entries – People, meetings, discussions, conference talks – Scientific publications, recommendations, quality comments – Models, codes, builds, workflows, – Data files and data streams – Sensors and sensor data … • To make it more useful, we should agree on – Controlled vocabularies / Ontologies • Resource description models • Grid Resource Ontologies • Application domain vocabularies
    • S-OGSA Model. Knowledge Entities Foundational Grid Ontology OGSA Ontology S-OGSA Ontology Unicore Globus Ontology Ontology Satellite Ontology OWL-DL ontology 45 http://www.unigrids.org/ontology.html
    • S-OGSA Model. A sample Grid Ontology
    • S-OGSA Model. A sample Data Mining Ontology • http://www.admire-project.eu/
    • S-OGSA Capabilities Application 1 Application N Security Optimization Semantic-OGSA OGSA Data Semantic Provisioning Services Execution Management Semantic binding Semantic Ontology Metadata Knowledge Provisioning Services Resource Reasoning Annotation management Information Management Infrastructure Services
    • OntoKit: An implementation of S-OGSA
    • OntoKit: An implementation of S-OGSA Annotation Metadata Reasoning Ontology Semantic
    • S-OGSA Mechanisms. Patterns Ontology Service Metadata Service Refers to Access/Query Metadata Properties Lifetime Metadata Resource Resource Seeking properties Client Others…. Service A semantic ignorant service
    • S-OGSA Mechanisms. Patterns Ontology Service Metadata Access/Query Semantic Service Refers to Bindings 2 Properties Lifetime Metadata 1 Get Semantic Binding Pointers Resource Resource Seeking properties Client Others… Service A semantic aware service, but incapable of processing semantics
    • S-OGSA Mechanisms. Patterns Ontology Service Metadata Service Farm out request 1.1 Properties Lifetime Metadata 1 Access/Query Semantic Bindings Semantics Resource Seeking Client Others… Service A semantic aware service, capable of processing semantics
    • S-OGSA Metadata Access/Management Semantic Binding Service Suite create WS-Addressing: epr SB Factory create WS-RP: Get/Set/Query Properties SB query SB Client WS-Notif: Subscribe / Notify SB Inspect- RDF WS-RL: Destroy , SetTerminationTime Semantic props . . . Binding WS-RL ++: archive Query w/o Inference, UpdateContent Query( over unified view) query Metadata Query
    • Semantic Binding Service. Lifetime Specification • What happens if... – ...any or all of the Grid entities it refers to disappears? • Instrument and planning files for satellites do not disappear • Insurance contracts, cars, repair companies, etc., may disappear – ...the Knowledge entities disappear or evolve? • Ontologies may change – ... a SB is no longer available (its content is not useful any more)? • Damage claims: add witness reports, improve info about location, create new hypothesis... • When do/should SBs become invalid? How often should this be checked? • What is the status of the content of a SB (e.g., content checked, stable, unchecked, etc.)? • Is a SB always active or can it be archived after a period of time? – Satellite data that is not used after some time
    • Semantic Binding Service. WS-SBResourceLifetime • SB Housekeeping service Stable Client Client Client WS-Notif. subscribe [state] Query-RP [state] Semantic Binding Service GE KE changed changed subscribe subscribe Stale WS-Notif [lastModificationTime] Knowledge Grid Entity Entity Archived Deleted
    • Ontology management: WS-DAIOnt-RDF(S) Resources RDF(S) Grid Access Bridge Repository Grid Compliant SelectorService WS-DAIOnt-RDF(S) Specification RDF(S) Ontology Access Mechanism RepositoryService Resource Class Property Statement Service Service Service Service Container List Alt Service Service Service Final Review, Manchester, July 17th 2007 57
    • Ontology management: WS-DAIOnt-RDF(S) • Two-tier architecture: WS-DAIOnt-RDF(S) Implementation Architecture – Web Service tier, different layers according to access granularity Upper Upper Repository service layer service layer SelectorService • Upper layer: management of multiple repositories Web Service Tier Internediate Internediate • Intermediate layer: service layer service layer RepositoryService management of a single repository Resource Class Property Statement • Lower layer: management of Service Service Service Service knowledge elements of a given repository Lower Lower service layer Container List Alt service layer Service Service Service – RDF(S) access tier: • Abstracts the interaction with RDFSConnector specific RDF(S) storages RDF(S) Storage Layer Sesame Jena Oracle Connector Connector Connector ... Sesame Jena Oracle RDF Storage RDF Storage RDF Storage
    • Overview • Motivation – Introduction – What is the Semantic Web – Semantic Web Technologies • RDF, RDF Schema and OWL • Semantic-OGSA (S-OGSA) – S-OGSA Reference Model and Capabilities – S-OGSA Mechanisms and Interaction Patterns – Sample Deployments of S-OGSA • Credits
    • Generating files in RDF FILE ; DMOP (generated by FOS Mission Planning System) RECORD fhr RECORD ID FILENAME="DMOP_SOF__VFOS20060124_103709_00000000_000 01215_20060131_014048_20060202_035846.N1" DESTINATION="PDCC" PHASE_START=2 RECORD CYCLE_START=44 parameters REL_START_ORBIT=404 ABS_START_ORBIT=20498 ENDRECORD fhr ................................ RECORD dmop_er RECORD dmop_er_gen_part RECORD gen_event_params RECORD parameters EVENT_TYPE=RA2_MEA corresponding to other EVENT_ID="RA2_MEA_00000000002063" NB_EVENT_PR1=1 RECORD structure. NB_EVENT_PR3=0 ORBIT_NUMBER=20521 <?xml version='1.0' encoding='ISO-8859-1'?><rdf:RDF ELAPSED_TIME=623635 xmlns:rdf='http://www.w3.org/1999/02/22-rdf-syntax-ns#' DURATION=41627862 xmlns:rdfs='http://www.w3.org/2000/01/rdf-schema#' ENDRECORD gen_event_params xmlns:NS0='http://protege.stanford.edu/kb#' > ENDRECORD dmop_er <rdf:Description rdf:about='http://protege.stanford.edu/kb#10822'> ENDLIST all_dmop_er <rdf:type rdf:resource='http://protege.stanford.edu/kb#Instrument_mode'/> ENDFILE <NS0:instrument_mode_id>MS</NS0:instrument_mode_id> </rdf:Description> <rdf:Description rdf:about='http://protege.stanford.edu/kb#11224'> <rdf:type rdf:resource='http://protege.stanford.edu/kb#DMOP_ER'/> <NS0:event_id>&quot;GOM_OCC_00000000541299&quot;</NS0:event_id> <NS0:duration rdf:datatype='http://www.w3.org/2001/XMLSchema#int'>53000</NS0:duration> <NS0:orbit_number rdf:datatype='http://www.w3.org/2001/XMLSchema#int'>20552</NS0:orbit_number> <NS0:elapsed_time rdf:datatype='http://www.w3.org/2001/XMLSchema#int'>2452293</NS0:elapsed_time> <NS0:event_type rdf:resource='http://protege.stanford.edu/kb#10713'/> </rdf:Description>
    • 1 Ontology 1 reference ontology for annotating all files RDF files are distributed Distributed Distributed Metadata for <RDF triple> Metadata for <RDF triple> Planning files <RDF triple> Product files <RDF triple> <RDF triple> <RDF triple> <RDF triple> <RDF triple> <RDF triple> <RDF triple> <RDF triple> <RDF triple> <RDF triple> <RDF triple> The product The planning files files
    • Satellite Use Case: Technical issues 62
    • Satellite Use Case (System Infrastructure): S-OGSA Scenario Planning file Product file server server GT4 GT4 Store (start-time, stop-time, gen-time, EPR) 8 Germany Italy OverlapChecking ONTO-DSI ONTO-DSI Service 3 Annotate file Get file summaries Grid-KP File directory 2 Spain Destroy (if RDF File 5 1a Get file names needed) Upload 9 Select files to be 4 1 annotated Obtain ontology Annotation WebDAV front-end XML Summary File WS-DAIOnt Create6 2’ Upload XML Summary file 1 SatelliteDomain SemanticBinding Ontology Input Service criteria 7 Store 8 3 Query MetadataQuery Notify (start- QUARC-SG client time, stop-time) JSP Service Metadata generation process RD Atlas RD Metadata querying process F F 63
    • Metadata queries in SPARQL PREFIX suc: <http://www.ontogrid.net/OWL/Satellite_Use_Case#> SELECT ?PRODUCT ?P_T1 ?P_T2 WHERE { ?PRODUCT suc:sensing_start ?P_T1 ; suc:sensing_stop ?P_T2 ; suc:represents_event ?PRODUCT_EVENT_TYPE . ?PRODUCT_EVENT_TYPE suc:plan_event_id ?PRODUCT_EVENT_ID . FILTER(REGEX(?PRODUCT_EVENT_ID, ".*RA.*") && ?P_T2 >= 192067200 && ?P_T1 <= 197247599 ) } http://www.youtube.com/watch?v=TSbb_8vmKvk 64
    • A simple Authorisation Scenario • A role-based Access Control Scenario in the insurance domain. • What? – Role based Access Control Policy is: • “Good Reputation Drivers are allowed to ask for an insurance policy. Bad Reputation ones are not.” • How? – VO ontology based on • KaOS ontologies (Actors, Groups and Actions) – Role definitions • Extend ontology with domain-specific classes and properties • Define roles wrt these extensions – E.g., a blacklistedDriver is a driver that has had at least 3 accident claims in the past – E.g., a goodReputationDriver is a driver that has been insured at least by one trusted company and that has had at most 2 accident claims – The Access Control Function uses an OWL classifier to obtain roles of a Subject.
    • S-OGSA Scenario. Authorisation /C=GB/O=PERMIS/CN=User0 1 getInsurancePolicy CarFraudService (PEP) PIP PDP 8 Result or Exception Proxy Proxy XACML XACML AuthZ AuthZ Request Response 3 7 Lookup whether the ROLE that is inferred permits or not 6 XACML_AuthZService 2 Mapping (PDP) Obtain Semantic Role Op Bindings of John Doe Atlas 4 Obtain all classes Classify John Doe RD that are subclass of ROLE wrt VO ont 5 F John Doe has had 2 distinct accidents VO Ontology Class Hierarchy -RDFS Pellet Reasoner WS-DAIOnt VO Ontology OWL
    • S-OGSA Scenario. Authorisation 1 CarFraudService (PEP) getInsurancePolicy PIP PDP 8 Result or Exception Proxy Proxy XACML XACML AuthZ AuthZ Request Response 3 7 Lookup whether the ROLE that is inferred permits or not 6 XACML_AuthZService 2 Mapping (PDP) Obtain Semantic Role Op Bindings of John Doe Atlas 4 Obtain all classes Classify John Doe RD that are subclass of ROLE wrt VO ont 5 F John Doe has had 2 distinct accidents VO Ontology Class Hierarchy -RDFS Pellet Reasoner WS-DAIOnt VO Ontology OWL
    • S-OGSA Scenario. Authorisation 1 CarFraudService (PEP) getInsurancePolicy PIP PDP 8 Result or Exception Proxy Proxy XACML XACML AuthZ AuthZ Request Response 3 7 Lookup whether the ROLE that is inferred permits or not 6 XACML_AuthZService 2 Mapping (PDP) Obtain Semantic Role Op Bindings of John Doe Atlas 4 Obtain all classes Classify John Doe RD that are subclass of ROLE wrt VO ont 5 F John Doe has had 2 distinct accidents VO Ontology Class Hierarchy -RDFS Pellet Reasoner WS-DAIOnt VO Ontology OWL
    • S-OGSA Scenario. Authorisation 1 CarFraudService (PEP) getInsurancePolicy PIP PDP 8 Result or Exception Proxy Proxy XACML XACML AuthZ AuthZ Request Response 3 7 Lookup whether the ROLE that is inferred permits or not 6 XACML_AuthZService 2 Mapping (PDP) Obtain Semantic Role Op Bindings of John Doe Atlas 4 Obtain all classes Classify John Doe RD that are subclass of ROLE wrt VO ont 5 F John Doe has had 2 distinct accidents VO Ontology Class Hierarchy -RDFS Pellet Reasoner WS-DAIOnt VO Ontology OWL
    • S-OGSA Scenario. Authorisation 1 CarFraudService (PEP) getInsurancePolicy PIP PDP 8 Result or Exception Proxy Proxy XACML XACML AuthZ AuthZ Request Response 3 7 Lookup whether the ROLE that is inferred permits or not 6 XACML_AuthZService 2 Mapping (PDP) Obtain Semantic Role Op Bindings of John Doe Atlas 4 Obtain all classes Classify John Doe RD that are subclass of ROLE wrt VO ont 5 F John Doe has had 2 distinct accidents VO Ontology Class Hierarchy -RDFS Pellet Reasoner WS-DAIOnt VO Ontology OWL
    • S-OGSA Scenario. Authorisation 1 CarFraudService (PEP) getInsurancePolicy PIP PDP 8 Result or Exception Proxy Proxy XACML XACML AuthZ AuthZ Request Response 3 7 Lookup whether the ROLE that is inferred permits or not 6 2 http://www.youtube.com/watch?v=Z_Jac2H0H3w Obtain Semantic XACML_AuthZService (PDP) Mapping Role Op Bindings of John Doe Atlas 4 Obtain all classes Classify John Doe RD that are subclass of ROLE wrt VO ont 5 F John Doe has had 2 distinct accidents VO Ontology Class Hierarchy -RDFS Pellet Reasoner Ignorant of semantics WS-DAIOnt VO Ontology Semantic aware but incapable of processing semantics OWL Semantic aware and capable of processing semantics Semantic provisioning services
    • Overview • Motivation (45 minutes) – Introduction – What is the Semantic Web – Semantic Web Technologies • RDF, RDF Schema and OWL • Semantic-OGSA (S-OGSA) (45 minutes) – S-OGSA Reference Model and Capabilities – S-OGSA Mechanisms and Interaction Patterns – Sample Deployments of S-OGSA • Credits
    • Summary • Metadata appears in most of the resources that we manage in Grid applications – It is often hidden – … or mixed with data – … or simply IMPLICIT • We can get many advantages by making metadata EXPLICIT – Decoupling data and metadata – Managing it with appropriate services – Relying on existing languages and technologies that make our life easier (RDF, RDF Schema, OWL) • S-OGSA supports this vision and provides basic tools – Use it as much as you want…
    • S-OGSA Future Work Application 1 Application N AuthZ and Trust over WS-DAIOnt-OWL metadata models Security Optimization Semantic-OGSA Authz over ontology models OGSA Data Semantic Provisioning Services Execution Management Semantic binding Semantic Ontology Metadata Knowledge Provisioning Services Resource Reasoning Annotation management Information Distribution of reasoning Management Stateful reasoning support Infrastructure Services Automation, automation, automation… (plus other features)
    • Credits • This tutorial is based on contributions from many authors. I hope to acknowledge all of them... • Sean Bechhofer, Carole Goble and David de Roure – Section “Ontologies and the Semantic Web”, based on Semantic Grid 101 presented at GGF16 in February 2006 • The OntoGrid team @ Manchester: Pinar Alper, Ioannis Kotsiopoulos, Paolo Missier, Sean Bechhofer, Carole Goble – S-OGSA work • Many others whose names appear on the slides • This tutorial has been funded in part by the European Commission, under the projects OntoGrid and RSSGRID
    • More information • Publications – An overview of S-OGSA: a Reference Semantic Grid Architecture. Corcho O, Alper P, Kotsiopoulos I, Missier P, Bechhofer S, Goble C. Journal of Web Semantics 4(2):102-115. June 2006 – Accessing RDF(S) data resources in service-based Grid infrastructures. Miguel Esteban Gutiérrez, Isao Kojima, Said Mirza Pahlevi, Óscar Corcho, Asunción Gómez-Pérez. Concurrency and Computation: Practice and Experience 21(8): 1029-1051 (2009) – Requirements and Services for Metadata Management. Missier P, Alper P, Corcho O, Dunlop I, Goble C. IEEE Internet Computing 11(5): 16-24 • Source code – http://www.ontogrid.eu/, For Downloading Distributions
    • The Semantic Web Vision • The Web was made possible through established standards – TCP/IP for transporting bits down a wire – HTTP & HTML for transporting and rendering hyperlinked text • Applications able to exploit this common infrastructure – Result is the WWW as we know it • Generations – 1st generation web mostly handwritten HTML pages – 2nd generation (current) web often machine generated/active The Syntactic Web • Both intended for direct human processing/interaction – In the next generation web, resources should be more accessible to automated processes • To be achieved via semantic markup • Metadata annotations that describe content/function The Semantic Web
    • Where we are Today: the Syntactic Web Resource href href href Resource Resource Resource Resource href href href href Resource href href href Resource Resource Resource href href Resource • A place where computers do the presentation (easy) and people do the linking and interpreting (hard). • Why not get computers to do more of the hard work?
    • Hard Work using the Syntactic Web… Find images of Oscar Corcho …Malcolm Atkinson … David Fergusson …
    • What’s the Problem? • Typical web page markup consists of: • Rendering information (e.g., font size and colour) • Hyper-links to related content • Semantic content is accessible to humans but not (easily) to computers…
    • Information we can see… International Summer School on Grid Computing (ISSGC2007) Semantic Grid practical Pinar Alper, Oscar Corcho Project logos… (sponsors/related projects/…?) OntoGrid, RSSGRID, Globus Student Exercises Structured in seven chapters Setup chapter Instructions for each chapter Code inside Description of code Material to change Additional material …
    • Information a machine can see…                       …   …
    • Solution: XML markup with “meaningful” tags? <name> </ name> <date></date> <location> </location> <introduction>      … </introduction> <speaker> <bio> </bio> </speaker> <speaker> <bio> </bio> </speaker> <registration>     
    • But What About…? <conf> </ conf> <date></date> <place> </place> <introduction>      … </introduction> <speaker> <bio> </bio> </speaker> <speaker> <bio> </bio> </speaker> <registration>     
    • Still the Machine only sees… <> < > <></> <> <> <>      … </> <> <> </> </> <> <> </> </> <>     
    • Seamark Demo: Keywords.rdf GO2Keyword.rdf ProbeSet.rdf ID new drug candidates for BRKCB-1 Keyword GO2UniProt.rdf GO2OMIM.rdf Probe Protein Gene MIM Id OMIM.rdf IntAct.rdf GO.rdf UniProt.rdf Enzyme GO2Enzyme.rdf Organism Citation Compound Taxonomy.rdf PubMed.xml Enzymes.rdf KEGG.rdf Pathway Courtesy Joanne Luciano http://139.91.183.30:9090/RDF/VRP/Examples/schema_go.rdf http://139.91.183.30:9090/RDF/VRP/Examples/go.rdf
    • OWL Ontology Example. BioPAX ontology • http://www.biopax.org/release/biopax-level2.owl
    • The Semantic Grid “The Semantic Grid is an extension of the current Grid in which information and services are given well-defined and explicitly represented meaning, so that it can be shared and used by humans and machines, better enabling computers and people to work in cooperation” D. De Roure, et. al Semantics in and on the Grid • Web Sites – www.semanticgrid.org – Setting up the www.semanticgridcafe.org • GGF Semantic Grid Research Group (SEM-RG) – Mailing List: sem-grd@gridforum.org
    • Motivation. Metadata Matters • Particularly for the following activities: – Information provision and resource discovery – Data integration – Provenance – Systems Configuration – Policy representation and reconciliation • Using: – Open, flexible and extensible self describing schemas that don’t have to be nailed down • “Let’s describe my data set, or the output format of this tool” • Lightweight schemas • Decoupled, interoperable systems, which resist to syntactic changes – Open world • “This metadata is no longer valid because...” – Data integration across different data models (e.g. RDF) • Like policy or resource models – Formalization & Reasoning support
    • SDK Semantic Grid history Demonstration Phase Efforts Systematic Investigation Phase Specific experiments Part of the Architecture Combe Dagstuhl Schloss Seminar Chem Pioneering Phase Grid Resource Ontology Ad-hoc experiments, early pioneers Many projects SRB GGF Semantic Grid Implicit Semantics Research Group OGSA generation Many workshops Implicit Semantics 1st generation Time
    • Semantic Grid: Use Cases • Semantic Grid for Annotation of Data – Already seen before in the cases of BioPAX and Gene Ontology • Semantic Grid in Workflows – Service description and discovery (myGrid) • Semantic Grid in Data Integration – www.godatabase.org – GEON – S-OGSA-DAI • Semantic Grid in Authorisation – We will see an example later
    • Data Integration in GO www.godatabase.org Gene Symbol Function Locus Name Function ASA1 tryptophan biosynthesis F15D2.31 tryptophan biosynthesis Courtesy Chris Wroe
    • Data Integration in GEON S iO2 is an instance of class AnalyticalOxideConcentration and has all information about the element S i Planetary Material Ontology CYBERINFRASTRUCTURE FOR THE GEOSCIENCES A.K.Sinha, Virginia Tech, 2005
    • S-OGSA-DAI • Low impact extension to OGSA-DAI - OntoGrid Insurance Use Case – Based on OGSA-DAI extensibility points WSI Client Extended – New OGSA-DAI activities • • RDQL Query Client Semantic Bindings • GetSemanticBinding (to get Client mappings) • RDQLQueryStatementActivity • SPARQLQueryStatementActivity • Query languages: – RDQL – SPARQL • Deployed on Apache Tomcat OGSA-DAI Core Extended Aditional functionality • Generation of • RDQL Query • Semantic Bindings – Query results directly – Semantic Bindings (in progress)
    • ActOn-based EGEE Information Service S-OGSA Service DGAS Domain Metadata Cache Ontology Distributed Information Sources <<uses>> User query Metadata Scheduler Wrapper RGMA Infomation Source BDII Selector InfoSource Ontology W.Xing, O. Corcho, C.Goble, M.Dikaiakos, An ActOn-based Semantic Information Service for EGEE, the 8th IEEE/ACM International Conference on Grid Computing. Nominated to best paper
    • From the pioneering phase to the systematic investigation phase • In the pioneering phase... – Ontologies and their associated technologies are not completely integrated in the Grid applications • They are used as in Semantic Web applications – But there are distinctive features of Grid applications • Distribution of resources • Scale • Resource management and state • ... (non exhaustive and non compulsory list) • In the systematic investigation phase – We have to take these features into account – And incorporate semantics as another Grid resource – Our proposal is: S-OGSA