1. Dynamic Ontology Matching Pavel Shvaiko OpenKnowledge meetings 9 February, 13 March, 2006 Trento, Italy

2. OK 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

3. OK meetings, 9 February, 13 March, 2006, Trento, Italy 3 P2P scenario (match-oriented view)

4. 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

5. 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

6. 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

7. 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?

8. OK meetings, 9 February, 13 March, 2006, Trento, Italy 8 Discussion - III Alignment negotiation Explanation and argumentation

9. 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]

10. 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

11. 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)  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.Number of peers and connectivity 2.Size and shape of ontologies/data 3.Run-time vs offline: time response, mixed initiative 4.Memory limit (256 mb)

12. 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

13. 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.???

14. OK meetings, 9 February, 13 March, 2006, Trento, Italy 14 A potential example of DOM - 1 [Source: Bin He]

15. OK meetings, 9 February, 13 March, 2006, Trento, Italy 15 A potential example of DOM - 2 [Source: Bin He]

16. OK meetings, 9 February, 13 March, 2006, Trento, Italy 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