Skip to main content
SpringerLink
Log in

Towards Efficient Data Access Through Multiple Relationship in Graph-Structured Digital Archives

  • Conference paper
  • First Online:
From Born-Physical to Born-Virtual: Augmenting Intelligence in Digital Libraries (ICADL 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13636))

Included in the following conference series:

  • 684 Accesses

Abstract

The research field of digital libraries mainly deals with data with graph structure. Graph database management systems (GDBMSs) are suitable for managing data in the digital library because the data size is large and its structure is complex. However, when performing a non-simple search or analysis on a graph, GDBMSs cannot avoid reaching already-scanned nodes from different starting nodes by repeatedly traversing edges such as property paths pattern in SPARQL. Therefore, when a GDBMS reaches high degree nodes, the number of graph traversals increases in proportion to the number of its adjacent nodes. Consequently, the cost of traversing multiple paths extremely increases affected by nodes connected enormous the number of edges in conventional GDBMSs. In this paper, we propose a data access approach by repeatedly traversing edges belonging to a specific relationship or anything one while distinguishing between high degree nodes and low degree ones. Finally, a result of our experiment indicated our approach can increase the speed of repeat traversals by a factor of a maximum of ten.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 79.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 99.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Angles, R., et al.: G-CORE: a core for future graph query languages. In: Proceedings of the 2018 International Conference on Management of Data, SIGMOD 2018, pp. 1421–1432. ACM (2018). https://doi.org/10.1145/3183713.3190654

  2. Barabási, A.L., Pósfai, M.: Network Science. University Press, Cambridge (2016)

    Google Scholar 

  3. Barabási, A.L., Frangos, J.: Linked: The New Science of Networks Science of Networks. Perseus Books Group, New York (2002)

    Google Scholar 

  4. Candela, G., Escobar, P., Carrasco, R.C., Marco-Such, M.: Evaluating the quality of linked open data in digital libraries. J. Inf. Sci. 48(1), 21–43 (2022). https://doi.org/10.1177/0165551520930951

    Article  Google Scholar 

  5. DB-Engines: Ranking of Graph DBMS. https://db-engines.com/en/ranking/graph+dbms. Accessed 8 Aug 2022

  6. Erling, O., et al.: The LDBC social network benchmark: interactive workload. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, SIGMOD 2015, pp. 619–630. ACM (2015). https://doi.org/10.1145/2723372.2742786

  7. Francis, N., et al.: Cypher: an evolving query language for property graphs. In: Proceedings of the 2018 International Conference on Management of Data, SIGMOD 2018, pp. 1433–1445. ACM (2018). https://doi.org/10.1145/3183713.3190657

  8. Haris, M., Farfar, K.E., Stocker, M., Auer, S.: Federating scholarly infrastructures with GraphQL. In: Ke, H.-R., Lee, C.S., Sugiyama, K. (eds.) ICADL 2021. LNCS, vol. 13133, pp. 308–324. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-91669-5_24

    Chapter  Google Scholar 

  9. Hogan, A., et al.: Knowledge graphs. ACM Comput. Surv. 54(4), 1–37 (2021). https://doi.org/10.1145/3447772

    Article  Google Scholar 

  10. Kusu, K., Hatano, K.: A hub-based graph management for efficient repetition path traversing. In: 2021 IEEE International Conference on Big Data and Smart Computing (BigComp), pp. 188–191. IEEE (2021). https://doi.org/10.1109/BigComp51126.2021.00043

  11. LDBC: ldbc/ldbc_snb_datagen.git. https://github.com/ldbc/ldbc_snb_datagen. Accessed 8 Aug 2022

  12. LDBC: LDBC’s HP. http://ldbcouncil.org/. Accessed 8 Aug 2022

  13. LDBC: ldbc_snb_implementations.git. https://github.com/ldbc/ldbc_snb_implementations. Accessed 8 Aug 2022

  14. Lissandrini, M., Brugnara, M., Velegrakis, Y.: Beyond macrobenchmarks: microbenchmark-based graph database evaluation. Proc. VLDB Endow. 12(4), 390–403 (2018). https://doi.org/10.14778/3297753.3297759

    Article  Google Scholar 

  15. Neo4j Inc: Neo4j’s HP. https://neo4j.com/. Accessed 8 Aug 2022

  16. Newman, M.: Networks: An Introduction. Oxford University Press, Oxford (2010)

    Book  MATH  Google Scholar 

  17. Pareto, V.F.D.: La courbe des revenus. In: Cours d’Èconomie Politique, vol. \(\rm (II)\), chap. \(\rm (\, I\,)\), pp. 299–345. Librairie Droz (1964)

    Google Scholar 

  18. van Rest, O., Hong, S., Kim, J., Meng, X., Chafi, H.: PGQL: a property graph query language. In: Proceedings of the Fourth International Workshop on Graph Data Management Experiences and Systems, GRADES 2016, pp. 1–6. ACM (2016). https://doi.org/10.1145/2960414.2960421

  19. Robinson, I., Webber, J., Eifrem, E.: Graph Databases. O’Reilly Media, Inc., Sebastopol (2015)

    Google Scholar 

  20. Rodriguez, M.A., Neubauer, P.: The graph traversal pattern. In: Sakr, S., Pardede, E. (eds.) Graph Data Management: Techniques and Applications, chap. 2, pp. 29–46. IGI Global (2012). https://doi.org/10.4018/978-1-61350-053-8.ch002

  21. Sakr, S., Al-Naymat, G.: The overview of graph indexing and querying techniques. In: Sakr, S., Pardede, E. (eds.) Graph Data Management: Techniques and Applications, chap. 4, pp. 71–88. IGI Global (2012). https://doi.org/10.4018/978-1-61350-053-8.ch004

  22. Sakr, S., Pardede, E.: Graph Data Management: Techniques and Applications. IGI Global, Hershey (2011)

    Google Scholar 

  23. Seaborne, A.: SPARQL 1.1 Property Paths. World Wide Web Consortium (W3C). https://www.w3.org/TR/sparql11-property-paths/

  24. THE GQL MANIFESTO: GQL Is Now a Global Standards Project alongside SQL. https://gql.today/. Accessed 8 Aug 2022

Download references

Acknowledgment

This research was partially supported by the Grants-in-Aid for Academic Promotion, Graduate School of Culture and Information Science, Doshisha University, and JSPS KAKENHI Grant Number JP21H03555 and JP22H03594.

Author information

Authors and Affiliations

  1. Doshisha University, Kyotanabe, Kyoto, Japan

    Kazuma Kusu & Kenji Hatano

  2. Nagoya University, Nagoya, Aichi, Japan

    Takahiro Komamizu

Authors
  1. Kazuma Kusu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Takahiro Komamizu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Kenji Hatano
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kazuma Kusu .

Editor information

Editors and Affiliations

  1. National Taiwan Normal University, Taipei, Taiwan

    Yuen-Hsien Tseng

  2. Doshisha University, Kyoto, Japan

    Marie Katsurai

  3. VNU University of Engineering and Technology, Hanoi, Vietnam

    Hoa N. Nguyen

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Kusu, K., Komamizu, T., Hatano, K. (2022). Towards Efficient Data Access Through Multiple Relationship in Graph-Structured Digital Archives. In: Tseng, YH., Katsurai, M., Nguyen, H.N. (eds) From Born-Physical to Born-Virtual: Augmenting Intelligence in Digital Libraries. ICADL 2022. Lecture Notes in Computer Science, vol 13636. Springer, Cham. https://doi.org/10.1007/978-3-031-21756-2_29

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-21756-2_29

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-21755-5

  • Online ISBN: 978-3-031-21756-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation