Motivated by the ongoing success of Linked Data and the growing amount of semantic data sources available on the Web, new challenges to query processing are emerging. Especially in distributed settings that require joining data provided by multiple sources, sophisticated optimization techniques are necessary for efficient query processing. We propose novel join processing and grouping techniques to minimize the number of remote requests, and develop an effective solution for source selection in the absence of preprocessed metadata. We present FedX, a practical framework that enables efficient SPARQL query processing on heterogeneous, virtually integrated Linked Data sources. In experiments, we demonstrate the practicability and efficiency of our framework on a set of real-world queries and data sources from the Linked Open Data cloud. With FedX we achieve a significant improvement in query performance over state-of-the-art federated query engines.
We study fundamental aspects related to the efficient processing of the SPARQL query language for RDF, proposed by the W3C to encode machine-readable information in the Semantic Web. Our key contributions are (i) a complete complexity analysis for all operator fragments of the SPARQL query language, which -as a central result -shows that the SPARQL operator OPTIONAL alone is responsible for the PSPACE-completeness of the evaluation problem, (ii) a study of equivalences over SPARQL algebra, including both rewriting rules like filter and projection pushing that are wellknown from relational algebra optimization as well as SPARQLspecific rewriting schemes, and (iii) an approach to the semantic optimization of SPARQL queries, built on top of the classical chase algorithm. While studied in the context of a theoretically motivated set semantics, almost all results carry over to the official, bag-based semantics and therefore are of immediate practical relevance.
Aims. We study the spectrum of the cosmic X-ray background (CXB) in energy range ∼5−100 keV. Methods. Early in 2006 the INTEGRAL observatory performed a series of four 30 ks observations with the Earth disk crossing the field of view of the instruments. The modulation of the aperture flux due to occultation of extragalactic objects by the Earth disk was used to obtain the spectrum of the Cosmic X-ray Background (CXB). Various sources of contamination were evaluated, including compact sources, Galactic Ridge emission, CXB reflection by the Earth atmosphere, cosmic ray induced emission by the Earth atmosphere and the Earth auroral emission. Results. The spectrum of the cosmic X-ray background in the energy band 5−100 keV is obtained. The shape of the spectrum is consistent with that obtained previously by the HEAO-1 observatory, while the normalization is ∼10% higher. This difference in normalization can (at least partly) be traced to the different assumptions on the absolute flux from the Crab Nebulae. The increase relative to the earlier adopted value of the absolute flux of the CXB near the energy of maximum luminosity (20−50 keV) has direct implications for the energy release of supermassive black holes in the Universe and their growth at the epoch of the CXB origin.
Abstract-Recently, the SPARQL query language for RDF has reached the W3C recommendation status. In response to this emerging standard, the database community is currently exploring efficient storage techniques for RDF data and evaluation strategies for SPARQL queries. A meaningful analysis and comparison of these approaches necessitates a comprehensive and universal benchmark platform. To this end, we have developed SP 2 Bench, a publicly available, language-specific SPARQL performance benchmark. SP 2 Bench is settled in the DBLP scenario and comprises both a data generator for creating arbitrarily large DBLP-like documents and a set of carefully designed benchmark queries. The generated documents mirror key characteristics and social-world distributions encountered in the original DBLP data set, while the queries implement meaningful requests on top of this data, covering a variety of SPARQL operator constellations and RDF access patterns. As a proof of concept, we apply SP 2 Bench to existing engines and discuss their strengths and weaknesses that follow immediately from the benchmark results.
The linear scale invariance of the multivariate alteration detection (MAD) transformation is used to obtain invariant pixels for automatic relative radiometric normalization of time series of multispectral data. Normalization by means of ordinary least squares regression method is compared with normalization using orthogonal regression. The procedure is applied to Landsat TM images over Nevada, Landsat ETM+ images over Morocco, and SPOT HRV images over Kenya. Results from this new automatic, combined MAD/orthogonal regression method, based on statistical analysis of test pixels not used in the actual normalization, compare favorably with results from normalization from manually obtained time-invariant features.
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