|
|
|
Dr. Leo Obrst |
|
MITRE |
|
Center for Innovative Computing &
Informatics |
|
Information Semantics |
|
Lobrst@mitre.org |
|
January 15, 2004 |
|
|
|
|
|
|
|
The Problem |
|
Tightness of Coupling & Explicit Semantics |
|
Semantic Integration Implies Semantic
Composition |
|
Dimensions of Interoperability & Integration |
|
Ontologies |
|
The Ontology Spectrum |
|
What are Ontologies? |
|
Levels of Ontology Representation |
|
What Problems do Ontologies Help Solve? |
|
Ontologies for Semantically Interoperable
Systems |
|
Enabling Semantic Interoperability |
|
Examples |
|
Visions |
|
What do We Want the Future to be? |
|
|
|
|
With the increasing complexity of our systems
and our IT needs, and the distance between systems, we need to go toward human
level interaction |
|
We need to maximize the amount of semantics we
can utilize and make it increasingly explicit |
|
From data and information level, we need to go
toward human semantic level interaction |
|
|
|
|
|
|
|
Tight coupling: applies to databases, systems |
|
Same address space, same process space, same
operating system, same machine |
|
Semantic compacts can be made because semantics
stays in the minds of the developers who agree |
|
Loose coupling |
|
Different platforms, networks, anywhere on
Internet |
|
Semantics must be explicit: agents, programs
need to interpret the semantics directly, to interoperate semantically |
|
Levels: systems of systems, enterprise,
community, value chains/pipes |
|
Ontologies (explicitly represented, logical
semantics): increasingly needed the higher you go |
|
|
|
|
|
|
|
|
|
|
|
To interoperate is to participate in a common
purpose |
|
Operation sets the context |
|
Purpose is the intention, the end to which
activity is directed |
|
Semantics is fundamentally interpretation |
|
Within a particular context |
|
From a particular point of view |
|
Semantic Interoperability/Integration is
fundamentally driven by communication of purpose |
|
Participants determined by interpreting capacity
to meet operational objectives |
|
Service obligations and responsibilities
explicitly contracted |
|
|
|
|
|
|
|
|
|
|
|
|
|
Heterogeneous database problem |
|
Different organizational units, Service
Needers/Providers have radically different databases |
|
Different syntactically: what’s the format? |
|
Different structurally: how are they structured? |
|
Different semantically: what do they mean? |
|
They all speak different languages (access,
description, schemas, meaning) |
|
Integration: rather than N2 problem,
with single, adequate Ontology reduces to N |
|
Enterprise-wide system interoperability problem |
|
Currently: system-of-systems, vertical
stovepipes |
|
Ontologies act as conceptual model representing
enterprise consensus semantics |
|
Relevant document retrieval/question-answering
problem |
|
What is the meaning of your query? |
|
What is the meaning of documents that would
satisfy your query? |
|
Can you obtain only meaningful, relevant
documents? |
|
|
|
|
|
|
|
|
|
Semantic Interoperability is enabled through: |
|
Establishing base semantic representation via
ontologies (class level) and their knowledge bases (instance level) |
|
Defining semantic mappings & transformations
among ontologies (and treating these mappings as individual theories just
like ontologies) |
|
Defining algorithms that can determine semantic
similarity and employing their output in a semantic mapping facility that
uses ontologies |
|
The use of ontologies & semantic mapping
software can reduce the loss of semantics (meaning) in information exchange
among heterogeneous applications, such as: |
|
Web Services |
|
E-Commerce, E-Business |
|
Enterprise architectures, infrastructures, and
applications |
|
Complex C4ISR systems-of-systems |
|
Integrated Intelligence analysis |
|
|
|
|
|
|
|
Multiple contexts, views, application & user
perspectives |
|
Multiple levels of precision, specification,
definiteness required |
|
Multiple levels of semantic model verisimilitude,
fidelity, granularity |
|
Multiple kinds of semantic mappings,
transformations needed: |
|
Entities, Relations, Properties, Ontologies,
Model Modules, Namespaces, Meta-Levels, Facets (i.e., properties of
properties), Units of Measure, Conversions, etc. |
|
|
|
|
|
System1 Instance of Concept: Date1 |
|
Attribute: YR = Int 1 |
|
Attribute: MO = String “Aug” |
|
Attribute: DY = Int 12 |
|
System2: Instance of Concept = Date2 |
|
Attribute: DayOfWeek = Sunday |
|
Attribute: ActualDate = |
|
String “12082001” |
|
Semantically Equivalent? Then How? |
|
|
|
|
|
|
|
|
|
System1 Instance of Concept: Location1 |
|
Attribute: SourceDeadReckoning = A |
|
Attribute: SourceDRLatitude = B |
|
Attribute: SourceDRLongitude = C |
|
Attribute: TargetDRBearingLine = D |
|
Attribute: TargetDRAltitude = E |
|
Attribute: ActualMeasuredAltitude = F |
|
Attribute: PositionLine = G |
|
System2: Instance of Concept:
Location2 |
|
Attribute: Address = H |
|
Attribute: City = I |
|
Attribute: StateProvince = J |
|
Attribute: Country = K |
|
Attribute: MailCode = L |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
An ontology allows for near linear semantic
integration (actually 2n-1) rather than near n2 (actually n2
- n) integration |
|
Each application/database maps to the
"lingua franca" of the ontology, rather than to each other |
|
|
|
|
|
|
|
|
|
|
2100 A.D: models, models, models |
|
There are no human-programmed programming
languages |
|
There are only Models |
|
|
|
|
|
Questions? lobrst@mitre.org |
|
Shameless Plug: |
|
The Semantic Web: The Future of XML, Web
Services, and Knowledge Management, -- Mike Daconta, Leo Obrst, & Kevin Smith, Wiley, June, 2003 |
|
http://www.amazon.com/exec/obidos/ASIN/0471432571/qid%3D1050264600/sr%3D11-1/ref%3Dsr%5F11%5F1/103-0725498-4215019 |
|
Contents: |
|
What is the Semantic Web? |
|
The Business Case for the Semantic Web |
|
Understanding XML and its Impact on the
Enterprise |
|
Understanding Web Services |
|
Understanding the Resource Description Framework |
|
Understanding the Rest of the Alphabet Soup |
|
Understanding Taxonomies |
|
Understanding Ontologies |
|
Crafting Your Company’s Roadmap to the Semantic
Web |
|
|
|
Notes
