An Algorithm for Extracting Shape Expression Schemas from Graphs

ABSTRACT

Unlike traditional data such as relational databases and XML documents, most of graphs do not have their own schema. However, schema is a concise representation of a graph, and if we can extract a "good" schema from a graph, we can take advantage of the extracted schema for effective graph data management. In this paper, we focus on Shape Expression Schemas (ShEx) and consider extracting ShEx schemas from RDF/graph data. To manage both efficiency and quality of extracted schema, our algorithm consists of two schema extraction steps: (i) edge-label based clustering and (ii) type-merge method for target nodes of outgoing edges. We made preliminary experiments, which result suggests that our algorithm can extract ShEx schemas appropriately.

References

1. Shape expressions (ShEx) primer. http://shexspec.github.io/primer/.
2. Balmin, A., Hristidis, V., and Papakonstantinou, Y. ObjectRank: authority-based keyword search in databases. In Proceedings of the Thirtieth International Conference on Very Large Data Bases (2004), pp. 564--575.
3. Bizer, C., and Schultz, A. The berlin SPARQL benchmark. International Journal on Semantic Web & Information Systems (2009), 1--24.
4. Chidlovskii, B. Schema extraction from XML collections. In Proceedings of the 2nd ACM/IEEE-CS joint conference on Digital libraries (2002), pp. 291--292.
5. Garofalakis, M. N., Gionis, A., Rastogi, R., Seshadri, S., and Shim, K. XTRACT: A system for extracting document type descriptors from XML documents. In Proceedings of the 2000 ACM SIGMOD International Conference on Management of Data (2000), pp. 165--176.
6. Goldman, R., and Widom, J. DataGuides: enabling query formulation and optimization in semistructured databases. In Proceedings of 23rd International Conference on Very Large Data Bases (VLDB '97) (1997), pp. 436--445.
7. Hegewald, J., Naumann, F., and Weis, M. XStruct: efficient schema extraction from multiple and large XML documents. In Proceedings of the 22nd International Conference on Data Engineering Workshops, ICDE 2006 (2006), p. 81.
8. Kellou-Menouer, K., and Kedad, Z. Schema discovery in RDF data sources. In Proceedings of 34th International Conference on Conceptual Modeling (ER 2015) (2015), pp. 481--495.
9. Nestorov, S., Abiteboul, S., and Motwani, R. Extracting schema from semistructured data. In Proceedings ACM SIGMOD International Conference on Management of Data (1998), pp. 295--306.
10. Schmidt, M., Hornung, T., Lausen, G., and Pinkel, C. SP2Bench: a SPARQL Performance Benchmark. In Proceedings of the IEEE 25th International Conference on Data Engineering (ICDE'09) (2009), IEEE, pp. 222--233.
11. Sekine, Y., and Suzuki, N. An algorithm for extracting schemas from external memory graphs. In Proceedings of the first workshop on Big Network Analytics (in conjunction with CIKM 2016) (2016).
12. Staworko, S., Boneva, I., Gayo, J. E. L., Hym, S., Prud'Hommeaux, E. G., and Solbrig, H. Complexity and expressiveness of ShEx for RDF. In Proceedings of 18th International Conference on Database Theory (ICDT 2015) (2015), p. 17.
13. Šejla Čebirić, Franccois Goasdoué, I. M. Query-oriented summarization of RDF graphs. In Proceedings of the VLDB Endowment (2015), pp. 2012--2015.
14. Wang, Q. Y., Yu, J. X., and Wong, K.-F. Approximate graph schema extraction for semi-structured data. In Proceedings of 7th International Conference on Extending Database Technology (EDBT 2000) (2000), pp. 302--316.

Index Terms

• Applied computing

  • Document management and text processing

    • Document management

• Information systems

  • Data management systems

    • Database design and models

      • Graph-based database models