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12 OK meetings, 9 February, 13 March, 2006, Trento, Italy

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Dynamic Ontology Matching
Pavel Shvaiko
OpenKnowledge meetings
9 February, 13 March, 2006
Trento, Italy
2
Introduction (Trento view)
Information sources (e.g., catalogs) can be viewed as graph-like structures
containing terms and their inter-relationships
Matching takes two graph-like structures and produces a mapping between
the nodes of the graphs that correspond semantically to each other
OK meetings, 9 February, 13 March, 2006, Trento, Italy
3
P2P scenario (match-oriented view)
OK meetings, 9 February, 13 March, 2006, Trento, Italy
4
P2P scenario: more details
Peers are autonomous
•
•
They appear and disappear on the network
They use different terminology
Matching (on-the-fly)
•
•
•
Determine the relationships between peer schemas
Use these relationships for query answering
An assumption that all peers rely on one global schema,
as in data integration, can not be made, because the
global schema might need to be updated any time the
system evolves
OK meetings, 9 February, 13 March, 2006, Trento, Italy
5
Requirements
Input size of ontologies
At most 100 entinties per ontology
Domains of interest
Bioinformatics and GIS Emergency response
Matching Performance
At most 2 seconds per matching task
Memory limit: 256Mb
Matching Quality
Mistakes are acceptable
OK meetings, 9 February, 13 March, 2006, Trento, Italy
6
Discussion - I
Input
OWL, RDF, XML
Will the instances be available?
Quality/charachteristics of entities
Partial vs Complete ontology matching
Perhaps we might not need to have a complete alignment
to answer a query
Quality/Efficiency trade off
QOM example
Online vs Offline vs Mixed match and QA
OK meetings, 9 February, 13 March, 2006, Trento, Italy
7
Discussion - II
What is in the alignment ?
1-1, 1-n, n-m
Is any relation suitable?
Output format
Test cases
The sooner we have them, the better
Matching quality measures
User/task related measures
What is more important in the application:
Precision or recall or both?
OK meetings, 9 February, 13 March, 2006, Trento, Italy
8
Discussion - III
Alignment negotiation
Explanation and argumentation
OK meetings, 9 February, 13 March, 2006, Trento, Italy
9
A comparison of techniques for dynamic ontology matching
1.
Introduction [2p] All
2.
The dynamic ontology matching problem [19p] Pavel
1. P2P information management systems [3p] Ilya
2. Motivating scenarios (2 our applications) [12p] Maurizio+Marco + Marta?
3. Requirements (functional vs non-functional) [2p]Pavel + Marta?
4. Problem statement [2p] Pavel+Ilya
1. why is it different from previous works
3.
A conceptual basis for comparison of dynamic matching techniques [13p] Marco
1. The framework + taxonomy [4+3p] Marco+Pavel+Mikalai
2. Ontology matching (standard) [3p]Pavel+Mikalai
3. Plausible DOM methods (transitivity) [3p]Pavel+Mikalai
4.
Systems and evaluation [10p] Mikalai
1. State of the art prototypes [2p]Pavel
2. Evaluation methodology [3p]Mikalai
3. Comarative evaluation results [5p]Mikalai
5.
Discussion/Open Issues and challenges towards DOM [3p] All
6.
Conclusions [2p]
OK meetings, 9 February, 13 March, 2006, Trento, Italy
10
A comparison of techniques for dynamic ontology matching
Index solid: Feb 17 (DONE)
Parallel 2,3,4: March 10 (DONE)
Use case + details of what should be matched by Fiona (March 22)
A first draft (circulated to partners): April 5
Trento
Feedback by April 19
Second draft (circulated to parnters):
Barcelona
Feedback by
Final version by mid May?
Trento
OK meetings, 9 February, 13 March, 2006, Trento, Italy
11
Motivating scenarios (P2P + 2 our applications)
1. Intuitive description (environment, actors, operations for the
system) [1p]
2. Requirements (Tropos) [2p + 1 fig]
domain description (Peers and peer goals)
use case
QA (functional requirements)
1. Measure quality (GEA) пѓ Trade quality for speed?
2. Transitivity in GEA
3. Logical architecture (organization of users and C/S Ps) [1p+1fig]
4. Physical architecture (bioinformatics=logical arcitechture)
5. Non-functional requirements [1p] P2P
1.
2.
3.
4.
Number of peers and connectivity
Size and shape of ontologies/data
Run-time vs offline: time response, mixed initiative
Memory limit (256 mb)
OK meetings, 9 February, 13 March, 2006, Trento, Italy
12
Conceptual Framework (Marco->March) [m6]
1. Introduction
2. P2P …
1. P2P information management systems
2. Motivating examples
3. Basic notation, terminology
4. Ontology Matching
1. Running examples (semantic matching + IF-MAP)
5. DOM
1. Dynamics (peers, ontologies, …)
2. Transitivity (compositionality of mappings and queries)
3. The basic theorem
6. DOM interaction model
7. Formalizing motivating examples
OK meetings, 9 February, 13 March, 2006, Trento, Italy
13
Methodological Framework (Trento->March)
1. Routing / Navigation / Search Ilya + Maxym [m6]
1. Basic operations
1. Node matching
2. Navigation
3. Query answering (substeps: rewriting)
2. Composite operations
1. Matching
2. QA
3. Interaction models for the above 2
4. Two case studies
2. Approximation / Quality [m12]
1. ???
OK meetings, 9 February, 13 March, 2006, Trento, Italy
14
A potential example of DOM - 1
OK meetings, 9 February, 13 March, 2006, Trento, Italy
[Source: Bin He]
15
A potential example of DOM - 2
OK meetings, 9 February, 13 March, 2006, Trento, Italy
[Source: Bin He]
16
DOM: open questions
1. What do we technically mean by dynamic?
ontology matching
2. Business cases & technical use cases
3. Technically, what do we match in our scenarios?
1. Messages between agents
2. Functionalities of web services
3. Classifications/Ontologies
OK meetings, 9 February, 13 March, 2006, Trento, Italy
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