An Approach to Characterizing RDF Documents through Conceptual Schemas
Abstract
A suitable storage model for RDF depends on a set of data characteristics and the knowledgment of its schema. This paper aims to contribute in this context on providing a method to extract conceptual schemas from RDF documents. The goal is to characterize an RDF data structure through an entity-relationship schema and its constructors. The proposed method is evaluated by a case study which demonstrates that the conceptual schemas generated are valid according to the model proposed by a benchmark for RDF.
Keywords:
RDF, conceptual schema, document characterization, schema extraction
References
Bizer, C. and Schultz, A. (2009). The Berlin SPARQL Benchmark. Int. J. Semantic Web Inf. Syst., 5(2):1–24.
Duan, S., Kementsietsidis, A., S., K., and U., O. (2011). Apples and oranges: A Comparison of RDF Benchmarks and Real RDF Datasets. In SIGMOD, pages 145–156.
Neumann, T. and Weikum, G. (2010). The RDF-3X Engine for Scalable Management of RDF Data. The VLDB Journal, 19(1):91–113.
Pham, M.-D., Passing, L., Erling, O., and Boncz, P. (2015). Deriving an Emergent Relational Schema from RDF Data. In WWW, pages 864–874.
Ramanujam, S., Gupta, A., Khan, L., Thuraisingham, B., and Seida, S. (2009). R2D: Extracting Relational Structure from RDF Stores. In International Joint Conference on Web Intelligence and Intelligent Agent Technology, pages 361–366.
Scabora, L. C., Oliveira, P. H., dos Santos Kaster, D., Traina, A. J. M., and Traina, C. (2017). Relational graph data management on the edge: Grouping vertices’ neighborhood with Edge-k. In Simpósio Brasileiro de Banco de Dados, pages 124–135.
Zeng, K., Yang, J., Wang, H., Shao, B., and Wang, Z. (2013). A Distributed Graph Engine for Web Scale RDF Data. Proceedings of the VLDB Endowment, 6(4):265–276.
Duan, S., Kementsietsidis, A., S., K., and U., O. (2011). Apples and oranges: A Comparison of RDF Benchmarks and Real RDF Datasets. In SIGMOD, pages 145–156.
Neumann, T. and Weikum, G. (2010). The RDF-3X Engine for Scalable Management of RDF Data. The VLDB Journal, 19(1):91–113.
Pham, M.-D., Passing, L., Erling, O., and Boncz, P. (2015). Deriving an Emergent Relational Schema from RDF Data. In WWW, pages 864–874.
Ramanujam, S., Gupta, A., Khan, L., Thuraisingham, B., and Seida, S. (2009). R2D: Extracting Relational Structure from RDF Stores. In International Joint Conference on Web Intelligence and Intelligent Agent Technology, pages 361–366.
Scabora, L. C., Oliveira, P. H., dos Santos Kaster, D., Traina, A. J. M., and Traina, C. (2017). Relational graph data management on the edge: Grouping vertices’ neighborhood with Edge-k. In Simpósio Brasileiro de Banco de Dados, pages 124–135.
Zeng, K., Yang, J., Wang, H., Shao, B., and Wang, Z. (2013). A Distributed Graph Engine for Web Scale RDF Data. Proceedings of the VLDB Endowment, 6(4):265–276.
Published
2018-08-25
How to Cite
MAIA, Alisson S.; PAGOTTI, Vagner; SCHROEDER, Rebeca.
An Approach to Characterizing RDF Documents through Conceptual Schemas. In: BRAZILIAN SYMPOSIUM ON DATABASES (SBBD), 33. , 2018, Rio de Janeiro.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2018
.
p. 223-228.
ISSN 2763-8979.
DOI: https://doi.org/10.5753/sbbd.2018.22234.
