What would you use an ontology for?

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15 Νοε 2013 (πριν από 3 χρόνια και 4 μήνες)

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What would you use an
ontology for?

Web Service model framework


Semantic web services


Semantic Grid services



Domain for escience


Services themselves


Link to UDDI, WSDL and other technologies


Processes and ontologies (controlled vocab. For
processes).

What are they used for taster


A community reference.


Support for community practice.


Specification of database or database content.


Controlled vocabulary for annotation.


Application & database interoperability.


Consensual vocabulary.


Searching, query formation & indexing.


Classification, interface/portal driving.


Agent or service metadata management.


Grid services description, advert, discover.

What are they used for taster


Support for knowledge intensive applications.


Text extraction, decision support, resource
planning, intelligent interfaces.


Knowledge repository structure.


Knowledge acquisition.

GO used for


Controlled annotation


quality
consistency


Mediation & navigation through content




Classification / query / index

InterPro

SWISS
-
PROT

BLAST

Ontology as content map


Relies on the
Gene Ontology’s
taxonomy.


Lack of
semantics and
rigour begins to
be problematic.

Four Roles of
Terminology/Ontologies


Content of Databases and Patient Records


Structural linkage within EPR/EHR & messages


Content of EPR/EHR & messages


Capturing information
-

the user interface



Linkage between domains


Health and Bio Sciences


Macro, Micro, and Molecular scales


Contexts: Normal / abnormal; species;
stage of development


Healthcare delivery and Clinical research


Patient Records and Decision Support


Indexing Information


Metadata and the semantic web


www.semanticweb.org www.w3c.org



No one universal semantics > semantic
interoperability


Ontology reconciliation


Ontology merging


Server based Web
-
> peer to peer interactions


Peer discovery


Languages for p2pconversations


Mediated communications


Coordinating protocosl


Tightly coupl,ed components
-
> loose coupled


Static workflows
-
> dynamic distributed
composition


Flexible distributed control


Partial failures


Execution monitoring


Efficient computations


Intermitent comms


Estab partnerships
-
> on the fly discovery


Partner discovery


Estab trust
-
> trust on the fly



Information based
-
> action at a distance


Role of human?


Eyeball web
-
> sw
-
>ssw
-
> agents web


Goal directed.

Semantic interoperation

objects

transport

packet

data link

physical

metamodels

ontologies

views/queries

process

objects

transport

packet

data link

physical

metamodels

ontologies

views/queries

process

Data

exchange

Semantic

interoperation

Web Service

Descriptions


=> Automated


Discovery & Search


Selection


Matching


Composition & Interoperation


Invocation


Execution monitoring

Machine processable
Knowledge on the Web


Annotating services requires a shared
vocabulary


Ontologies
:


a vocabulary of terms,


a precise and principled specification of their meaning


structure on the domain of the terms


constrain the possible interpretations of terms


Inference applies the knowledge in the
metadata and the ontology to create new
metadata and new knowledge

The Web Services Stack

XML

HTTP

TCP/IP

SOAP

WSDL

UDDI

Transport

Message syntax

Message protocol

Service connection

Adverts:
Description and discovery

WFDL

Workflow


Ontology



What do Ontologies offer?


Knowledge discovery


Knowledge
-
acquisition tools


Decision Support


Hypothesis generation


RiboWeb, Ingenuity

Control + Semantics + Inference


“The technical advantages of knowledge
modeling are obvious. Knowledge bases can be
automatically checked for consistency; they
support inference mechanisms which derive
data which have not been explicitly stored; they
also offer extensive request and navigation
facilities. However, the most immediate benefit
of knowledge base design lies in the modeling
process itself, through the effort of explication,
organization and structuration [sic] of the
knowledge it requires.”

Editorial, Bioinformatics, July 2000

Scale =>

Reasoning & Inference

1.
Keeping the classification together

2.
Expressing constraints and sticking to ‘em


Ontology design


Creation, extension, maintenance


Large, multiply authored evolving ontologies


Ontology integration


Merging


Ontology deployment


Determining consistency of description & instances


Query validation/refinement/containment & Service
matching

Ontologies and the Grid


Domain Ontologies


For eScience applications



Service and Task Ontologies


For Web/OGSA services


Semantic Web Services.



Service capabilities


The Semantic Web

Knowledge Technologies

for the Grid


Ability to store and retrieve huge volumes of data


Ability to effectively process large volumes of data



Ability to capture, enrich, classify and structure
knowledge about


Domains


Organisations


Individuals


Research Collaborations


Experiments


Results


Services

Semantics: A Many
-

Splendored Thing (from mike)


“Semantics” means [the study of] meaning.


What has semantics? Where are they?


What do they look like? How are they used?



Kinds of Semantics:


Real
-

world Semantics


Axiomatic Semantics


Model
-

theoretic Semantics


Denotational, Procedural, Operational …
Semantics

Semantic “Networking”

It is crucial for the interoperability layer to migrate from

the syntactic to the semantic!





User Query/

Information Request

User Query/

Information Request

User Query/

Information Request

Distributed Computing Infrastructure (J2EE, .NET, CORBA, Agents
)

Inter
-
Ontology

Relationships Manager

Ontology

Server

Ontology

Server

The Semantic Web / Grid Fabric:

A Collection of Metadata Descriptions and Ontologies

...

DATA REPOSITORIES

Metadata

Server

Metadata

Repository

Metadata

Server

Metadata

Repository

...

DATA REPOSITORIES

Components of the Semantic
Web Fabric


Bootstrapping, Creation and Maintenance of
Semantic Knowledge


Collaborative and Sociological Processes, Statistical
Techniques


Ontology Building, Maintenance and Versioning Tools


Re
-
use of Existing Semantic Knowledge
(Ontologies)


Annotation/Association/Extraction of Knowledge
with/from Underlying Data


Information Retrieval and Analysis (Distributed
Querying/Search/Inference Middleware)


Semantic Discovery and Composition of Services


Distributed Computing/Communication
Infrastructures


Component based technologies, Agent based
systems, Web Services


Repositories for managing data and semantic
knowledge


Relational Databases, Content Management Systems,
Knowledge Base Systems

What are the missing gaps ?


Ontology Integration/Interoperation


Need to address “semantics” of relationships such as
“synonyms”, “hyponyms”, etc.


Ontology Impedance/Mismatch


Relax the requirements of consistency and completeness


Should be able to characterize the “information error/loss” that
occurs..


Dynamic Ontologies


Need to relax the assumption of the “staticness”


Inferences based on Semantics of the Data


Performance/Scalability


re
-
use of pre
-
existing data models/schemas/ontologies
that describes the content of information sources…




http://www
-
ksl.stanford.edu/knowledge
-
sharing/ontologies/html/bibliographic
-
data/



Bibliography Data Ontology:
The
Blue

Ontology

Biblio
-
Thing

Document

Book

Edited
-
Book

Technical
-
Report

Periodical
-
Publication

Journal

Magazine

Newspaper

Miscellaneous
-
Publication

Technical
-
Manual

Computer
-
Program

Multimedia
-
Document

Artwork

Cartographic
-
Map

Thesis

Doctoral
-
Thesis

Master
-
Thesis

Proceedings

Conference

Agent

Person

Author

Organization

Publisher

University



A subset of WordNet
1.5: The
Red

Ontology

Instructions

Reference
-
Manual

Print
-
Media

Press

Publication

Journalism

Newspaper

Magazine

Book

Periodical

Trade
-
Book

Brochure

TextBook

Reference
-
Book

SongBook

PrayerBook

Pictorial

Series

Journals

CookBook

Instruction
-
Book

WordBook

HandBook

Directory

Annual

Encyclopedia


Manual

Bible

GuideBook

http://www.cogsci.princeton.edu/~wn/w3wn.html

Ontology architecture


KAON?


myGrid?