NSF-OntoWeb Invitational Workshop on
DB-IS Research for
Semantic Web and Enterprises
Description and Agenda





Researchers and practitioners are making steady progress towards building solutions based on syntax, to representation and structure, to semantics [S98].  One of the recent unifying visions is that of Semantic Web [B99, BHL01, FM01, BSW], which proposed semantic annotation of data, so that programs can understand it, and help in making decisions.  Researchers have subsequently seen the value of using semantics to understand information and decision making needs of humans, so that data and human’s needs can be semantically intermediated. The scope of semantics-based solutions increasingly involve knowledge and learning based solutions, and has also moved from data and information to services and processes [ABH+01].

A review of active research funding and projects on Semantic Web shows extensive investigations based AI and knowledge representation branches of computer science [SW-1][SW-02][SWWS].  For example, logic-based descriptions and inferencing techniques are being extensively investigated as part of projects under the Semantic Web umbrella [SW]. This includes many projects funded by DARPA and EC 5th Framework Program, including the DAML and OntoWeb initiatives and programs [DAML,OW].  There is a visible dearth of investigations from the database and information systems community.  This workshop seeks to investigate relationships between challenges in developing semantic solutions for the Web and Enterprises, and the experience and expertise of the database and information systems community.

Semantics has not been new to the database and information systems community [S98, KS00, M01]. Semantics in data models was studied intensively in the 1980s, and applied to problems such as query processing, view management, schema transformation, schema integration and transaction processing.  Semantic heterogeneity and interoperability have been studied as part of all major information systems architectures during the last three decades, including federated, mediator, and information brokering architectures.  Many projects in information interoperability and integration have addressed semantic heterogeneity.  In addition to the study of semantics, we believe there are several important areas of expertise within the database and information systems community developed as part of successful database management, information interoperability, information retrieval and workflow management systems that will be important to build large scale, high performance and practical Semantic Web and Enterprise solutions.  A partial list of relevant technology for, e.g., semantic web services includes transaction management, query planning and optimization, distributed scheduling, exception handling, dynamic changes and adaptation, and security.

Research in database management and workflow management has an extensive history of achieving high impact through improving methods of other scientific endeavors as well as in developing new technologies leading to commercialization and in establishing new high-tech industry sectors. This workshop will investigate research directions that can lead to similar long term impact in Semantic Web and Enterprise solutions by our community. 



Of particular interest to the proposed workshop was the discussion during and after the panel “Semantic Web – Rehash or Research Goldmine,” panelists for which included Dieter Fensel, Robert Meersman, John Mylopoulous and Amit Sheth.  Some of the issues identified below (see Plan) were raised during and after this panel, and a majority of the participants are expected to attend the proposed workshop.  Background for this workshop is also provided by a number of relevant meetings, including

We expect that a significant majority of the organizers of the above events will participate in the proposed workshop. 



The workshop will be held for 2.5 days and will involve up to 25 invited participants to include some of the most influential researchers and leaders. Formal presentations are not planned, but discussions will be conducted through position papers and statements. A key output of the workshop will be either a white paper or a “manifesto”-style report authored by some of the active participants.  Presentations and position papers will be made available from the workshop’s Web site.

We expect to discuss and investigate a number of issues during the workshop that are targeted to define and improve the role of database and information systems research in semantic technology being developed for the Web and the Enterprises.  Despite several meetings [SW-1][SW-2][SWWS], we have not yet seen substantial focus on these topics.  A very preliminary list of topics includes the following (this list is sure to be revised and extended before the workshop in the process of setting up various discussion tracks): 

n       What types of semantics Semantic Web researchers are looking to support?

  • can we map model with real world, or support syntax, semantics, and world knowledge?

  • what can we learn from past research on semantic data models?

  • while we all know of tradeoff between expressiveness and computability, do you feel the current choices (or favored representation mechanisms) make right choices?

n       Ontology seems to be what provides semantic underpinning; what do we see as the assumptions behind how ontologies are created and maintained (have we learned from experiments and efforts to create and maintain large ontologies such as Cyc and UMLS)? (also see [Cir])

  • What can we learn from substantial past relationships between database and ontology research [M01]?

  • Have we learned to deal with inevitable need to deal with multiple ontologies and inter ontological relationships?) [MIKS00, KS00, WAD+01, MWD01]; What does database management provide for managing (storing and searching) large ontologies—especially assertional components of ontologies, large RDF files, etc.? What can we learn from schema translation, schema adaptation, schema integration, metadata and model mapping techniques?

  • Does the principle of data independence apply to distinct management approaches to definitional and assertional components of ontologies, and how does that compare with techniques to manage large numbers of tuples or data in AI-based approaches? Can relational, O-O and XML data management systems be used for ontology storage and management?

  • What can database and knowledge base techniques do for the difficult problem of creating and maintaining ontologies?

n       Are the reasoning/inferencing mechanisms currently being investigated flexible enough? Does database query specification and execution techniques provide an alternative? Should database engine be extended to support restricted and efficient form of inferencing? Are main memory database technologies relevant and can they scale?  [Sco]

n       How can we support complex relationships [TSP01], ambiguities, incompleteness, and uncertainty that naturally occur in the real world and are critical for supporting real world semantics? Can database query processing be adapted to consider semantics of relationships? Can fuzzy logic techniques step up [FLINT]?

n       Web and enterprises involve structured, semi-structured and unstructured content, accessed in push as well as pull methods. What do traditional and semi-structured data management offer in providing integrated access and management of heterogeneous content? [Sco]

n       How does metadata management and extraction relate to ontology management (specification, creation, maintenance)? How do new industry and application specific metadata standards relate to ontology specification? [BSW, Sco]

n       What can Semantic Web, especially service composition aspects as envisaged with DAML-S [ABH+01] learn from research in database and workflow management? How do issues of distributed workflow scheduling and execution relate with that of multi-agent systems for Web services composition and execution?  What about the issues of QoS, transactional properties, reliability, exception handling, and others that have not seen much attention by multi-agent systems used to prototype Semantic Web and Web services examples?  Should services and state information be handled in DBMSs?

n       What are lessons from earlier experience with logic based systems, KR, or AI learned or are mistakes are being repeated—especially with respect to their adoption (or lack thereof)? Do we risk going the way Question-Answer systems go? Are we applying the results/successes where we have found them?

The workshop will be organized by Amit Sheth (University of Georgia) as a PI of the effort sponsored by NSF CISE-IIS and co-organized by Robert Meersman (VUB, Brussels) with co-sponsorship from the EU Thematic Network OntoWeb. Large Scale Distributed Information Systems Lab of the University of Georgia will provide local organization support.  Current plan is to hold the workshop during the first week of April at a lodge in an isolated and beautiful State park that is easily accessible from the Atlanta airport.



[ABH+01] A. Ankolekar, M. Burstein, J. Hobbs, O. Lassila, D. Martin, S. McIlraith, S. Narayanan, M. Paolucci, T. Payne, K. Sycara, H. Zeng, DAML-S: Semantic Markup for Web Services, 2001, http://www.daml.org

[B99] Tim Berners-Lee (with Mark Fischetti), Weaving the Web, The original design and ultimate destiny of the World Wide Web, Harper, 1999.

[BHL01] T. Berners-Lee, J. Hendler, and O. Lassila, “The Semantic Web: A new form of Web content that is meaningful to computers will unleash a revolution of new possibilities,” Scientific American, May 2001.

[BSW] http://business.semanticweb.org

[Cir] CIRCA technology, Applied Semantics, www.appliedsemantics.com

[DAML] http://www.daml.org

[FLINT] Proceedings of FLINT 2001, New Directions in Enhancing the Power of the Internet, August 14-18, 2001; UC Berkeley. Also see http://www.abo.fi/~rfuller/fuzs.html

[FM01] D. Fensel and M. Musen, Eds. “The Semantic Web: A Brain for Humankind,” IEEE Intelligent Systems, March/April 2001.

[KS00] V. Kashyap and A. Sheth, Information Brokering, Kluwer Academic Publishers, 2000. Also see V. Kashyap and A. Sheth, “Semantics based Information Brokering,” Proceedings of the 3rd Intl. Conf. on Information and Knowledge Systems, November 1994.

[M01] R. Meersman, Ontologies and Databases: More than a Fleeting Resemblance, Proceedings of the OES-SEO 2001 Rome Workshop", A. d'Atri and M. Missikoff (eds), LUISS Publications, 2001.

[MIKS00] E. Mena, A. Illarramendi, V. Kashyap and A. Sheth, “OBSERVER: An Approach for Query Processing in Global Information Systems based on Interoperation across Pre-existing Ontologies”, International Journal Distributed and Parallel Databases (DAPD), Vol. 8, No. 2, pp. 223-271, April 2000.

 [MWD01] P. Mitra, G. Wiederhold and S. Decker, A Scalable Framework for Interoperation of Information Sources, The first Semantic Web Working Symposium, July 30 - August 31, 2001.

[OW] http://www.ontoweb.org

[S98] A. Sheth, “Changing Focus on Interoperability in Information Systems: From System, Syntax, Structure to Semantics”, in Interoperating Geographic Information Systems.  M. F. Goodchild, M. J. Egenhofer, R. Fegeas, and C. A. Kottman (eds.), Kluwer, Academic Publishers, 1998, pp. 5-30.

[Sco] SCORE technology, Content Enhancement and Semantic Engine, Taalee/Voquette, www.taalee.com or www.voquette.com

[SW] http://www.semanticweb.org

[SW-1] Proceedings of the Workshop on Semantic Web: Models, Architectures and Management, Lisbon, September 21, 2000.

[SW-2] Proceedings of the Second International Workshop on the Semantic Web – SemWeb’2001 at WWW10, Hongkong, May 1, 2001.

[SWWS] Proceedings of the International Semantic Web Workshop: Infrastructure and Applications for the Semantic Web, Stanford, July 30-31, 2001. Also see reports.

[TSP01] S. Thacker, A. Sheth and S. Patel, “Complex Relationships for the Semantic Web,” Creating the Semantic Web, D. Fensel, J. Hendler, H. Liebermann, and W. Wahlster (eds.) MIT Press, 2002 (to appear).

[WAD+01] G. Wiederhold, S. Agarwal, S. Decker, J. Janninck, P. Mitra, et al. Scalable Knowledge Composition, 2001, http://www-db.stanford.edu/pub/gio/personal/SKCsynopsis.ppt.

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