I Know Where to Find What You Want: Semantic Data Map from Silos

  • Sungmin YiEmail author
  • Soo-Hyung KimEmail author
  • Jungho ParkEmail author
  • Taeho Hwang
  • Jaehun Lee
  • Yunsu Lee
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11762)


Data-driven analysis is critically important for creating new insights and values; however, data silos prevent a full utilization of existing data. To overcome this issue, we propose Semantic Data MAP (SD-MAP). SD-MAP utilizes a virtual graph and conceptual groups to bypass a physical integration of databases while allowing users to access data using intuitive queries. In order to show our system’s effectiveness, we introduce a plausible scenario with a data structure from real world. A demonstration video of SD-MAP is available at:


Virtual graph Data integration Silo effect Semantic Data Map Intuitive queries SPARQL 


  1. 1.
    Tiwari, S., Wee, H., Daryanto, Y.: Big data analytics in supply chain management between 2010 and 2016: insights to industries. Comput. Ind. Eng. 115, 319–330 (2018)CrossRefGoogle Scholar
  2. 2.
    Dong, X.L., Halevy, A., Yu, C.: Data integration with uncertainty. VLDB J. 18(2), 469–500 (2009)CrossRefGoogle Scholar
  3. 3.
    Calvanese, D., et al.: Ontop: answering SPARQL queries over relational databases. Semant. Web 8(3), 471–487 (2017)CrossRefGoogle Scholar
  4. 4.
    Renée, M., Laura, H., Mauricio, H.: Schema mapping as query discovery. In: Proceedings of the 26th International Conference on Very Large Data Bases, VLDB 2000, pp. 77–88 (2000)Google Scholar
  5. 5.
    Shen, W., Wang, J., Han, J.: Entity linking with a knowledge base: issues, techniques, and solutions. IEEE Trans. Knowl. Data Eng. 27(2), 443–460 (2015)CrossRefGoogle Scholar
  6. 6.
    vis.js Homepage.
  7. 7.
    Teiid Homepage.

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Samsung Research, Samsung ElectronicsSeoulSouth Korea

Personalised recommendations