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International Journal on Digital Libraries | 1997

The Lorel Query Language for Semistructured Data

Serge Abiteboul; Dallan Quass; Jason McHugh; Jennifer Widom; Janet L. Wiener

Lorel language, designed for querying semistructured data. Semistructured data is becoming more and more prevalent, e.g., in structured documents such as HTML and when performing simple integration of data from multiple sources. Traditional data models and query languages are inappropriate, since semistructured data often is irregular: some data is missing, similar concepts are represented using different types, heterogeneous sets are present, or object structure is not fully known. Lorel is a user-friendly language in the SQL/OQL style for querying such data effectively. For wide applicability, the simple object model underlying Lorel can be viewed as an extension of the ODMG data model and the Lorel language as an extension of OQL. The main novelties of the Lorel language are: (i) the extensive use of coercion to relieve the user from the strict typing of OQL, which is inappropriate for semistructured data; and (ii) powerful path expressions, which permit a flexible form of declarative navigational access and are particularly suitable when the details of the structure are not known to the user. Lorel also includes a declarative update language. Lorel is implemented as the query language of the Lore prototype database management system at Stanford. Information about Lore can be found at http://www-db.stanford.edu/lore. In addition to presenting the Lorel language in full, this paper briefly describes the Lore system and query processor. We also briefly discuss a second implementation of Lorel on top of a conventional object-oriented database management system, the O2 system.


international conference on management of data | 1997

Lore: a database management system for semistructured data

Jason McHugh; Serge Abiteboul; Roy Goldman; Dallas Quass; Jennifer Widom

Lore (for Lightweight Object Repository) is a DBMS designed specifically for managing semistructured information. Implementing Lore has required rethinking all aspects of a DBMS, including storage management, indexing, query processing and optimization, and user interfaces. This paper provides an overview of these aspects of the Lore system, as well as other novel features such as dynamic structural summaries and seamless access to data from external sources.


international conference on management of data | 1997

Integrating dynamically-fetched external information into a DBMS for semistructured data

Jason McHugh; Jennifer Widom

We describe the external data manager component of the Lore database system for semistructured data. Lores external data manager enables dynamic retrieval and integration of data from arbitrary, heterogeneous external sources during query processing. The distinction between Lore-resident and external data is invisible to the user. We introduce a flexible notion of arguments that limits the amount of data fetched from an external source, and we have incorporated optimizations to reduce the number of calls to an external source.


very large data bases | 1999

Query Optimization for XML

Jason McHugh; Jennifer Widom


international workshop on the web and databases | 1999

From Semistructured Data to XML: Migrating the Lore Data Model and Query Language

Roy Goldman; Jason McHugh; Jennifer Widom


very large data bases | 1998

Incremental Maintenance for Materialized Views over Semistructured Data

Serge Abiteboul; Jason McHugh; Michael Rys; Vasilis Vassalos; Janet L. Wiener


Archive | 1998

Indexing Semistructured Data

Jason McHugh; Jennifer Widom; Serge Abiteboul; Qingshan Luo; Anand Rajaraman


advances in databases and information systems | 1997

Semistructured data: the TSIMMIS experience

Joachim Hammer; Jason McHugh; Hector Garcia-Molin


Archive | 1997

Wiener: The Lorel Query Language for Semistructured Data

Serge Abiteboul; Dallan Quass; Jason McHugh; Jennifer Widom; L Janet


international conference on management of data | 1996

LORE: a Lightweight Object REpository for semistructured data

Dallan Quass; Jennifer Widom; Roy Goldman; Kevin Haas; Qingshan Luo; Jason McHugh; Svetlozar Nestorov; Anand Rajaraman; Hugo Rivero; Serge Abiteboul; Jeffrey D. Ullman; Janet L. Wiener

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Serge Abiteboul

École normale supérieure de Cachan

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Vasilis Vassalos

Athens University of Economics and Business

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