Generating permission-based security policies
Xin Li, Hua Vy Le Thanh, et al.
DSA 2018
Efficient storage and querying of RDF data is of increasing importance, due to the increased popularity and widespread acceptance of RDF on the web and in the enterprise. In this paper, we describe a novel storage and query mechanism for RDF which works on top of existing relational representations. Reliance on relational representations of RDF means that one can take advantage of 35+ years of research on efficient storage and querying, industrial-strength transaction support, locking, security, etc. However, there are significant challenges in storing RDF in relational, which include data sparsity and schema variability. We describe novel mechanisms to shred RDF into relational, and novel query translation techniques to maximize the advantages of this shredded representation. We show that these mechanisms result in consistently good performance across multiple RDF benchmarks, even when compared with current state-of-the-art stores. This work provides the basis for RDF support in DB2 v.10.1. Copyright © 2013 ACM.
Xin Li, Hua Vy Le Thanh, et al.
DSA 2018
Vivek Kumar, Julian Dolby, et al.
PPPJ 2016
Jason Ellis, Achille Fokoue, et al.
SIGMOD Record
Jinqiu Yang, Erik Wittern, et al.
MSR/ICSE 2018