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Hyper Object Data Model: A Simple Data Model for Handling Semi-Structured Data

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Emerging Trends in Computing and Communication

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 298))

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Abstract

This paper introduces a new data model based for handling semi-structured data extending the existing HyperFile data model that uses the hypertext notion of free-form objects connected by links. The HyperFile model provides flexibility to store semi-structured data which cannot be stored by relational database efficiently. However, the model suffers from some incompleteness in its definition towards proper representation and retrieval of stored objects. This makes it difficult to implement HyperFile data model towards storage and manipulation of data. The proposed data model, namely, HyperObject data model (HODM) overcomes this problem. An appropriate new query language, called HyperObject query language (HOQL) is also introduced to efficiently manipulate data stored using HODM. The paper also includes framework to implement the data model and its query language as a blade on top of the relational data model. This makes it easy to implement and solves the problem of handling heterogeneous semi-structured data at a higher level of abstraction on top of an underlying relational database.

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References

  1. Chakraborty S, Chaki N (2011) A survey on the semi-structured data models. In: Springer proceedings of the 10th international conference on computer information systems and industrial management applications (CISIM-2011), Kolkata, 14–16 Dec 2011, pp 257–266

    Google Scholar 

  2. Ni W, Ling TW (2003) GLASS: a graphical query language for semi-structured data. In: Proceedings of international conference on database systems for advanced applications (DASFAA)

    Google Scholar 

  3. Cao Z, Wu Z, Wang Y (2007) UMQL: a unified multimedia query language. In: Proceedings of the 3rd international IEEE conference on signal-image technologies and internet-based system (SITIS 2007), Shanghai, pp 109–115

    Google Scholar 

  4. Mendelzon A, Mihaila G, Milo T (1996) Querying the world wide web. In: Proceedings of the 1st international conference on parallel and distributed information system, pp 80–91

    Google Scholar 

  5. Arocena G, Mendelzon A (1998) WebOQL: restructuring documents, databases and webs. In: Proceedings of the international conference on data engineering. IEEE Computer Society, pp 24–33

    Google Scholar 

  6. Lakshmanan LVS, Sadri F, Subramanian IN (1996) A declarative language for querying and restructuring the web. In: Proceedings of the 6th international workshop on research issues in data engineering

    Google Scholar 

  7. Buneman P, Davidson S, Hilebrand G, Suciu D (1996) A query language and optimization techniques for unstructured data. In: Proceedings of the ACM SIG-MOD international conference on management of data, pp 505–516

    Google Scholar 

  8. Shmueli O, Konopnicki D (1995) W3QS: a query system for the world-wide web. In: Proceedings of the international conference on very large data bases, Zurich, Switzerland. Morgan Kaufmann Publishers, Inc., pp 54–65

    Google Scholar 

  9. Cardelli L, Ghelli G (2004) TQL: a query language for semistructured data based on the ambient logic. Math Struct Comput Sci 14:285–327

    Article  MATH  MathSciNet  Google Scholar 

  10. Abiteboul S, Quass D, McHugh J, Widom J, Wiener JL (1997) The Lorel query language for semistructured data. Int J Digit Libr 1(1):68–88

    Article  Google Scholar 

  11. Himmeroder R, Lausen G, Ludascher B, Schlepphorst C (1997) On a declarative semantics for web queries. In: Proceedings of the international conference on deductive and object-oriented databases, Switzerland. Springer LNCS, pp 386–398

    Google Scholar 

  12. Tseng F, Chen C (2005) Integrating heterogeneous data warehouses using XML technologies. J Inf Sci 31(3):209–229

    Article  Google Scholar 

  13. Niemi T, Niinimäki M, Nummenmaa J, Thanisch P (2002) Constructing an OLAP cube from distributed XML data. In: Proceedings of 5th ACM international workshop data warehousing and OLAP (DOLAP 2002), pp 22–37

    Google Scholar 

  14. Motro A, Rakov I (1996) Estimating the quality of data in relational databases. In Proceedings of the 1996 conference on information quality, pp 94–106

    Google Scholar 

  15. Liu M, Ling TW (2000) A data model for semistructured data with partial and inconsistent information. In: Proceedings of the international conference on advances in database technology (EDBT 2000), Konstanz, Germany, 27–31 March 2000, pp 317–331

    Google Scholar 

  16. Bancilhon F, Khoshafian S (1989) A calculus for complex objects. J Comput Syst Sci 38(2):326–340

    Article  MATH  MathSciNet  Google Scholar 

  17. Clifton C, Garcia-Molina H, Bloom D (1995) HyperFile: a data and query model for documents. VLDB J 4(1):45–86

    Article  Google Scholar 

  18. Angles R, Gutierrez C (2008) Survey of graph database models. ACM Comput Surv (CSUR) 40(1):1–39

    Article  Google Scholar 

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Correspondence to Nabendu Chaki .

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Pandit, D., Chaki, N., Chattopadhyay, S. (2014). Hyper Object Data Model: A Simple Data Model for Handling Semi-Structured Data. In: Sengupta, S., Das, K., Khan, G. (eds) Emerging Trends in Computing and Communication. Lecture Notes in Electrical Engineering, vol 298. Springer, New Delhi. https://doi.org/10.1007/978-81-322-1817-3_32

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  • DOI: https://doi.org/10.1007/978-81-322-1817-3_32

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-1816-6

  • Online ISBN: 978-81-322-1817-3

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