Revealing species communities in a spatial and temporal overlap

Storing physical and chemical values, optical spectra and sediment granulometry is already a cumbersome task; dealing with biological data even falls into a different category. Biologists tend to focus their attention to species of their interest while other specimens in the same sample are often underestimated. Meanwhile taxonomists are continuously revising the taxonomy resulting in a complete new set of relations between these taxa. Keeping track with both and meanwhile having a dataset up to date seems endless. At the Belgian Marine Data Centre we tried to think outside the box and came up with a solution to content both biologists and data managers. The last thing we aimed at is to create another web index to refer species, therefore we hooked up with the existing web based referencing systems. The need to get data about different food webs in a spatial and temporal overlap is answered by our hierarchical storage of taxa which allows selecting a predator at species level and at the same time selecting different prey species at lower taxonomic levels. As these species, and also the scientists, usually are not confined into ‘latitude longitude squares’ we elaborated the spatial selection tool which defines user specific polygons to base the selection of data upon. We will briefly present the structure of our relational database but specific attention will go out to the taxonomic and spatial parts. Incentives and discomforts to organize the data in this way, and our current web interface, will be demonstrated

Multi-way R-tree joins using indirect predicates

Since spatial join processing consumes much time, several algorithms have been proposed to improve spatial join performance. Spatial join has been processed in two steps, called filter step and refinement step. The M-way R-tree join (MRJ) is a filter step join algorithm, which synchronously traverses M R-trees. In this paper, we introduce indirect predicates which do not directly come from the multi-way join conditions but are indirectly derived from them. By applying indirect predicates as well as direct predicates to MRJ, we can quickly remove the minimum bounding rectangle (MBR) combinations which do not satisfy the direct predicates or the indirect predicates at the parent level. Hence we can reduce the intermediate MBR combinations for the input to the child level processing and improve the performance of MRJ. We call such a multi-way R-tree join algorithm using indirect predicates indirect predicate filtering (IPF). Through experiments using synthetic data and real data, we show that IPF significantly improves the performance of MRJ. q 2004 Elsevier B.V. All rights reserved. Keywords: Spatial databases; Spatial join; M-way R-tree join; Indirect predicate