The Semantic Web: Suppliers and Customers
Description
The notion of the Semantic Web can be coined as a Web of data when bringing database content to the Web or as a Web of enriched human-readable content when encoding the semantics of web-resources in a machine-interpretable form.
It has been clear from the beginning that realizing the Semantic Web vision will require interdisciplinary research. At this the fifth ISWC, it is time to re-examine the extent to which interdisciplinary work has played and can play a role in Semantic Web research, and even how Semantic Web research can contribute to other disciplines. Core Semantic Web research has drawn from various disciplines, such as knowledge representation and formal ontologies, reusing and further developing their techniques in a new context.
| Slides | |
| 1:25 | Semantic Web: Customers and Suppliers |
| 2:34 | ISWC: Looking Back |
| 3:49 | ISWC: Connecting Communities |
| 4:52 | Agenda |
| 5:47 | IJCAI, KR |
| 6:44 | VLDB, SIGMOD/PODS |
| 7:45 | ACL, SIGIR, ECML, ICML |
| 8:31 | ICSE, SEKE |
| 9:31 | Customers and Suppliers |
| 10:38 | Agenda |
| 11:04 | Knowledge Representation (KR) |
| 12:39 | KR as Customer |
| 14:14 | KR as Customer |
| 15:16 | KR as Supplier |
| 18:16 | Integrating DLs and Logic Programming Acknowledgements: Boris Motik, Riccardo Rosati |
| 20:30 | Databases (DB) |
| 21:27 | Databases vs. Semantic Web |
| 23:54 | Trends in Databases Acknowledgement: Alon Halevy |
| 28:40 | Example: Personal Information Management |
| 29:18 | DB as Customer: Challenge 1 Integration in Dataspaces |
| 31:46 | DB as Customer: Challenge 2 Semantic Mappings |
| 33:13 | DB as Customer Challenge 3: Uncertainty and Inconsistency |
| 34:07 | DB as Supplier: Deductive Database Techniques in KAON2 |
| 37:06 | Software Engineering |
| 38:00 | Ontologies vs. Models Acknowledgements: Colin Atkinson |
| 39:59 | Ontology Definition Metamodel |
| 42:11 | SE as Supplier: MOF-based Ontology Development |
| 43:53 | SE as Customer: MOF and Semantic Web Acknowledgements: Elisa F. Kendall |
| 45:29 | Natural Language Processing (NLP) |
| 46:14 | NLP as Customer |
| 48:00 | NLP as Customer |
| 48:58 | NLP as Supplier |
| 50:26 | NLP for Ontology Evaluation |
| 53:28 | AEON – Architecture |
| 54:00 | Machine Learning (ML) |
| 54:50 | ML as Customer |
| 56:19 | ML as Supplier |
| 57:25 | Disclaimer |
| 57:45 | Agenda |
| 57:53 | The Semantic Technology Market Offers High Growth Potential |
| 59:40 | Market Estimation |
| 60:38 | Information Integrator |
| 62:16 | A Look at REAL Customers Acknowledgement: Richard Benjamins, iSOCO |
| 64:15 | Agenda |
| 64:20 | Take Home Messages |
| 65:25 | Trends |
| 65:29 | Trends |
| 67:13 | Semantic MediaWiki |
| 68:14 | Semantic MediaWiki |
| 69:04 | slide51 |
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iswc06_studer_sc_01.ppt (7.3 MB)
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