-
Stream
Mill. The complete
data stream management system must support relational
streams, XML streams, and languages more powerful than
SQL and XQuery--as required, e.g., for mining queries
and queries for finding patterns in data streams.
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- ArchIS. Poweful
Archival Information Systems
can be built by combining XML and relational DBs. XML supports
a temporally-grouped view of the transaction-time history
of the underlying DB, whereby powerful temporal queries
are expressed in XQuery (with no extension required). Internally,
RDBMSs support these temporal views and queries efficiently
via SQL/XML.
Web demo installed
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- ATLaS.
ATLaS allows users to define new aggregate and table functions
in SQL itself. This provides a native extensibility mechanism
for DBMS to overcome their current limitations with advanced
applications. ATLaS is Turing-complete, and supports efficiently
data mining and complex data-intensive applications.
ATLaS
1.4.6 Released--SQL/XML Supported as Built-in Aggregates/Functions!
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- DEIS.
Support for Design of Evolving Information
Systems. An NSF-IIS SGER, Science of Design, Collaborative
Research project. The objective is to develop the enabling
DB technology for information systems to gracefully adapt
to changes.
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ICAP.
Incorporating Change Management into Archival Processes.We
propose a uniform approach to archive and retrieve the history
of web documents using XML. The evolution history and past
versions of these documents can be queried using XML query
languages
Web demo installed
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- TBALL.
Technologically Based Assessment of
Language and Literacy: an interdisciplinary
project involving EE, CS, Linguistics, Education, and Neuroscience
departments from UCLA, UCB, USC and partnerships with local
elementary schools.
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