Provenance compression scheme based on graph patterns for large RDF documents

Provenance data are metadata that represent the source information or modification history of various data. Provenance information can be a few dozen times greater in amount than the original data because it is continuously increased whenever the source data are modified. Therefore, schemes for efficiently compressing large-capacity provenance data are required. In this paper, we proposed a new resource description framework (RDF) provenance compression scheme that considers graph patterns. The proposed scheme reduces the space occupied by string data by converting the provenance data into numeric data through a dictionary encoding process. Unlike existing provenance compression schemes, in the proposed scheme, some RDF documents manage the source RDF documents on the semantic web to track changes in the provenance data. The proposed scheme reduces the storage space by compressing the source RDF documents by considering their patterns. It also compresses the provenance data by considering the patterns of active nodes in the PROV model. This improves the compression performance through a compression based on the provenance flow. The excellence of the proposed scheme was verified based on the compression rate and processing time determined from a performance evaluation.

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