Storing massive Resource Description Framework (RDF) data: a survey

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The Resource Description Framework (RDF) and RDF Schema (RDFS) recommended by World Wide Web Consortium (W3C) have been used for meta‐data management on the Web. With the rapid development of Web‐based applications, the growth of RDF(S) data is increasing dramatically. In the context of open Web, uncertainty naturally arises in RDF and RDFS (RDF(S) in short). To manage large‐scale fuzzy RDF(S) data efficiently and effectively, we propose, in this paper, a fuzzy RDF(S) storage schema with fuzzy HBase databases (FHDBs). On the basis, we investigate how to query in FHDBs. We propose a set of query algorithms. We implement a prototype system to demonstrate the feasibility of our approach.

Section: Introductionmentioning

confidence: 99%

Storing and querying fuzzy RDF(S) in HBase databases

Fan

2020

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“…In contrast to the centralized RDF data management, the distributed RDF data management provides scalable service and storage capacity, which hashes partition triples across multiple machines and parallelizes query processing (e.g., 4store and YARS2, SHARD, HadoopRDF, JenaHBase, Trinity.RDF, GraphPartition, WARP, DARQ, and FedX). An overview of current work in RDF data management is provided in Ma, Capretz, and Yan . RDF(S) management needs to deal with two primary problems, which are the storage and queries of RDF(S), respectively.…”

Section: Introductionmentioning

confidence: 99%

“…RDF(S) management needs to deal with two primary problems, which are the storage and queries of RDF(S), respectively. RDF(S) storage is the infrastructure of implementing RDF(S) management . Currently, there are many efforts in RDF data storage.…”

Section: Introductionmentioning

confidence: 99%

Mapping fuzzy RDF(S) into fuzzy object‐oriented databases

Fan

2019

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The Resource Description Framework (RDF) and RDF Schema (RDFS), being a recommendation of World Wide Web Consortium (W3C), have been widely used to exchange and reason information about resources on the web. It is a common case that information about resources may be uncertain under an environment of open web. To deal with uncertainties in resource information, we propose, in this paper, a general fuzzy RDF(S) model, which contains a fuzzy RDFS layer and a fuzzy RDF layer. In particular, we investigate how to formally map the fuzzy RDF(S) model to the fuzzy object‐oriented database model in the paper. We develop mapping rules and implement a prototype system to demonstrate the feasibility of our approach.

“…While originally designed to encode knowledge in the Semantic Web, RDF has found its way out of the Semantic Web community and entered the wider discourse of Computer Science, in particular, to the rise of linked data on the Web and the profusion of domains where networked objects have to be handled. Coming along with its application in other areas, an increasing amount of RDF data has been becoming available in RDF format . However, information is often vague or ambiguous in real‐world applications.…”

Section: Introductionmentioning

confidence: 99%

A method for fuzzy quantified querying over fuzzy Resource Description Framework graph

2019

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Vagueness (or imprecision) naturally arises in real‐world Resource Description Framework (RDF) data. The way we query RDF data is a crucial subject because of the vagueness and the wide connectivity of such data. Fuzzy quantified queries have been studied over several types of data and allow to sum up large volumes of data in a very intuitive manner. However, there are a few works that have been led on RDF graph database. In this study, we dealt with a specific type of fuzzy quantified queries in the context of a (fuzzy) RDF graph database. We first show how these queries can be expressed and interpreted in a quantified graph pattern, which is an extension of graph patterns by supporting linguistic quantifier on edges. A query processing strategy based on subgraph matching queries is also proposed. Then, we develop an algorithm for evaluating quantified RDF graph patterns, that is, enumerating all RDF isomorphism from the given RDF graph patterns into the data graph. The algorithm is based on a backtracking strategy, which incrementally finds partial solutions by adding joinable candidate vertices or abandoning them when it determines they cannot be completed. Finally, we perform some experiments to study its performances. The results of these experiments show that the method of dealing with fuzzy quantification in a query is feasible.