View maintenance is a problem in data management that arises whenever a view is materialized over a source that changes over time. When the source is large, or when the source and view reside on different hosts, it is not practical to recompute the view and retransmit it over the network each time the source is updated. A better idea, commonly used in systems built with view maintenance in mind, is to translate source updates to ones that can be applied to the view directly. The cost of calculating, transmitting, and applying a translated update is typically dramatically less than the cost of recomputing and retransmitting the entire view. This paper addresses the problem of maintaining XQuery views over XML data. The core algorithm translates updates through queries as expressed in the tree algebra used internally in the Galax engine. This algorithm extends previous work on maintenance for relational views, although there are significant complications due to the data model, which is both ordered and nested. To overcome these obstacles, we propose a scheme for storing auxiliary data that guides the translation of updates in this more complicated setting. A novel aspect of our approach compared to previous work is that the amount and content of annotations can be controlled by users, making it possible to balance the tradeoffs between the size of the auxiliary data and the quality of translated updates. We have built a prototype implementation to test these ideas. Our system extends Galax, and handles a core set of operators and built-in functions capable of expressing many typical firstorder queries. Its design is fully compositional, so it can easily be extended to new operators. We present preliminary results of experiments run on benchmark queries from the XMark suite.

Abstract. Effective revision tracking is important to maintain and use Semantic Web data for both publishers and readers. Information related to revisions in this setting often contains basic context information, semantic difference summary, and rationale summary. In this work, we present a general architecture for modeling and publishing revision history of social semantic Web data. This model has been implemented as an extension to an existing infrastructure, namely Semantic MediaWiki. We show a variety of applications that can be built using the framework, including provenance tracking, statistics, temporal reasoning and explanation. 1