An Update Strategy for the WaterFowl RDF Data Store

Abstract : The WaterFowl RDF Store is characterized by its high compression rate and a self-indexing approach. Both of these characteristics are due to its underlying architecture. Intuitively, it is based on a stack composed of two forms of Succinct Data Structures, namely bitmaps and wavelet trees. The ability to efficiently retrieve information from these structures is performed via a set of operations, i.e., rank, select and access, which are used by our query processor. The nice properties, e.g. compactness and efficient data retrieval, we have observed on our first experimentations come at the price of poor performances when insertions or deletions are required. For instance, a naive approach has a dramatic impact on the capacity to handle ABox updates. In this paper, we address this issue by proposing an update strategy which uses an hybrid wavelet tree (using both pointer-based and pointerless sub-wavelet trees).
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Olivier Curé, Guillaume Blin. An Update Strategy for the WaterFowl RDF Data Store. 13th International Semantic Web Conference (ISWC 2014), 2014, Riva del Garda, Italy. ⟨hal-01740550⟩

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