The Price Is Right

Models and Algorithms for Pricing Data
  • Ruiming Tang
  • Huayu Wu
  • Zhifeng Bao
  • Stéphane Bressan
  • Patrick Valduriez
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8056)


Data is a modern commodity. Yet the pricing models in use on electronic data markets either focus on the usage of computing resources, or are proprietary, opaque, most likely ad hoc, and not conducive of a healthy commodity market dynamics. In this paper we propose a generic data pricing model that is based on minimal provenance, i.e. minimal sets of tuples contributing to the result of a query. We show that the proposed model fulfills desirable properties such as contribution monotonicity, bounded-price and contribution arbitrage-freedom. We present a baseline algorithm to compute the exact price of a query based on our pricing model. We show that the problem is NP-hard. We therefore devise, present and compare several heuristics. We conduct a comprehensive experimental study to show their effectiveness and efficiency.


Approximation Algorithm Price Model Price Strategy Query Result Price Function 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Ruiming Tang
    • 1
  • Huayu Wu
    • 2
  • Zhifeng Bao
    • 3
  • Stéphane Bressan
    • 1
  • Patrick Valduriez
    • 4
  1. 1.School of ComputingNational University of SingaporeSingapore
  2. 2.Institute for Infocomm ResearchSingapore
  3. 3.IDMINational University of SingaporeSingapore
  4. 4.INRIA & LIRMMMontpellierFrance

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