Session 48 - Principles of Semantic metadata management

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

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

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

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 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


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


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

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>"GOM_OCC_00000000541299"</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>

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

1 CarFraudService (PEP)
getInsurancePolicy

PIP PDP

XACML XACML
AuthZ AuthZ
Request Response
3 7
Lookup whether the
permits or not
6
XACML_AuthZService
2 Mapping
(PDP)
Obtain Semantic Role Op
Bindings of John
Doe

Atlas
ROLE wrt VO ont 5
F
John Doe has
had 2 distinct

WS-DAIOnt
VO Ontology
OWL

1 CarFraudService (PEP)
getInsurancePolicy

PIP PDP

XACML XACML
AuthZ AuthZ
Request Response
3 7
Lookup whether the
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
ROLE wrt VO ont 5
F
John Doe has
had 2 distinct

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

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…

<>
<
>
<></>
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

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

Session 48 - Principles of Semantic metadata management

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Session 48 - Principles of Semantic metadata management