Synthesis Lectures on Data Management is edited by Tamer Özsu of the University of Waterloo. The series will publish 50-to 125 page publications on topics pertaining to data management. The scope will largely follow the purview of premier information and computer science conferences, such as ACM SIGMOD, VLDB, ICDE, PODS, ICDT, and ACM KDD. Potential topics include, but not are limited to: query languages, database system architectures, transaction management, data warehousing, XML and databases, data stream systems, wide scale data distribution, multimedia data management, data mining, and related subjects.

This paper introduces U-relations, a succinct and purely relational representation system for uncertain databases. U-relations support attribute-level uncertainty using vertical partitioning. If we consider positive relational algebra extended by an operation for computing possible answers, a query on the logical level can be translated into, and evaluated as, a single relational algebra query on the U-relational representation. The translation scheme essentially preserves the size of the query in terms of number of operations and, in particular, number of joins. Standard techniques employed in off-the-shelf relational database management systems are effective for optimizing and processing queries on U-relations. In our experiments we show that query evaluation on U-relations scales to large amounts of data with high degrees of uncertainty.

Gender differences in brain activation during working memory tasks were examined with fMRI. Seventeen right-handed subjects (nine males, eight females) were studied with four different verbal working memory tasks of varying difficulty using whole brain echo-planar fMRI. Consistent with prior studies, we observed activation of the lateral prefrontal cortices (LPFC), the parietal cortices (PC), and additionally, caudate activation in both sexes. The volume of activated brain tissue increased with increasing task difficulty. For all four tasks, the male subjects showed bilateral activation or right-sided dominance (LPFC, PC and caudate), whereas females showed activation predominantly in the left hemisphere. The task performance data demonstrated higher accuracy and slightly slower reaction times for the female subjects. Our results show a highly significant (p < 0.001) gender differences in the functional organization of the brain for working memory. These gender-specific differences in functional organization of the brain may be due to gender-differences in problem solving strategies or the neurodevelopment. Therefore, gender matching or stratification is required for studies of brain function using imaging techniques.

We present a decomposition-based approach to managing incomplete information. We introduce world-set decompositions (WSDs), a space-efficient and complete representation system for finite sets of worlds. We study the problem of efficiently evaluating relational algebra queries on world-sets represented by WSDs. We also evaluate our technique experimentally in a large census data scenario and show that it is both scalable and efficient.

Central to any XML query language is a path language such as XPath which operates on the tree structure of the XML document. We demonstrate in this paper that the tree structure can be effectively compressed and manipulated using techniques derived from symbolic model checking. Specifically, we show first that succinct representations of document tree structures based on sharing subtrees are highly effective. Second, we show that compressed structures can be queried directly and efficiently through a process of manipulating selections of nodes and partial decompression. We study both the theoretical and experimental properties of this technique and provide algorithms for querying our compressed instances using node-selecting path query languages such as XPath. We believe the ability to store and manipulate large portions of the structure of very large XML documents in main memory is crucial to the development of efficient, scalable native XML databases and query engines.