Experience with relational systems has shown that distribution is an effective way of improving the scalability of query evaluation. In this paper, we show how distributed query evaluation can be performed in a vertically partitioned XML database system. We propose a novel technique for constructing distributed execution plans that is independent of local query evaluation strategies. We then present a number of optimizations that allow us to further improve the performance of distributed query execution. Finally, we present a response time-based cost model that allows us to pick the best execution plan for a given query and database instance. Based on an implementation of our techniques within a native XML database system, we verify that our execution plans take advantage of the parallelism in a distributed system and that our cost model is effective at identifying the most advantageous plans.

Scientific research becomes increasingly reliant on collaborative effort among multiple institutions and interdisciplinary consortia, through sharing scientific experiments and data and collaboration on analysis of data and results. Besides information sharing, there is a growing need to create a framework to enable collaborative, cross-disciplinary research, which can facilitate a research community into a default mode of collaboration, including: i) enabling scientific researchers to dynamically interact with others, collaboratively author, annotate, review, comment on others' data, and discuss their research; ii) providing a dynamic collaboration environment by harnessing collective contributions from a group of researchers; and iii) facilitating broader participation of people into research projects. While traditional data management and integration systems put much focus on passively integrating existing data, the collaboration among data providers and users is quite limited. In this paper, we present a Web-based collaborative platform to dynamically integrate information for scientific research. Besides data integration, the system provides essential collaboration capabilities to boost user participation and collaboration. The system will not only enable users as active information contributors to bring significant new values to the data, but also provide an environment for scientific researchers to do collaborative research in a large research community.