The Design of Arbitrage-Free Data Pricing Schemes

Authors Shaleen Deep, Paraschos Koutris

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Shaleen Deep
Paraschos Koutris

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Shaleen Deep and Paraschos Koutris. The Design of Arbitrage-Free Data Pricing Schemes. In 20th International Conference on Database Theory (ICDT 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 68, pp. 12:1-12:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)


Motivated by a growing market that involves buying and selling data over the web, we study pricing schemes that assign value to queries issued over a database. Previous work studied pricing mechanisms that compute the price of a query by extending a data seller’s explicit prices on certain queries, or investigated the properties that a pricing function should exhibit without detailing a generic construction. In this work, we present a formal framework for pricing queries over data that allows the construction of general families of pricing functions, with the main goal of avoiding arbitrage. We consider two types of pricing schemes: instance-independent schemes, where the price depends only on the structure of the query, and answer-dependent schemes, where the price also depends on the query output. Our main result is a complete characterization of the structure of pricing functions in both settings, by relating it to properties of a function over a lattice. We use our characterization, together with information-theoretic methods, to construct a variety of arbitrage-free pricing functions. Finally, we discuss various tradeoffs in the design space and present techniques for efficient computation of the proposed pricing functions.
  • data pricing
  • determinacy
  • arbitrage


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  1. Serge Abiteboul and Oliver M. Duschka. Complexity of answering queries using materialized views. In PODS, pages 254-263. ACM Press, 1998. URL:
  2. Magdalena Balazinska, Bill Howe, and Dan Suciu. Data markets in the cloud: An opportunity for the database community. PVLDB, 4(12), 2011. Google Scholar
  3. Tugkan Batu, Sanjoy Dasgupta, Ravi Kumar, and Ronitt Rubinfeld. The complexity of approximating the entropy. SIAM J. Comput., 35(1):132-150, 2005. URL:
  4. S. Boztas. Entropies, guessing and cryptography. Technical Report 6, Department of Mathematics, Royal Melbourne Institute of Technology, 1999. Google Scholar
  5. Federal Trade Commission et al. Data brokers: A call for transparency and accountability. Policy Reports, Commission and Staff Reports, May 2014. Google Scholar
  6. Kenneth Cukier and Viktor Mayer-Schoenberger. Rise of big data: How it’s changing the way we think about the world, the. Foreign Aff., 92:28, 2013. Google Scholar
  7. Nilesh N. Dalvi, Christopher Ré, and Dan Suciu. Probabilistic databases: diamonds in the dirt. Commun. ACM, 52(7):86-94, 2009. URL:
  8. Shaleen Deep and Paraschos Koutris. The design of arbitrage-free data pricing schemes. arXiv preprint arXiv:1606.09376, 2016. Google Scholar
  9. Cynthia Dwork. A firm foundation for private data analysis. Commun. ACM, 54(1):86-95, 2011. URL:
  10. Cynthia Dwork, Frank McSherry, Kobbi Nissim, and Adam Smith. Calibrating noise to sensitivity in private data analysis. In Shai Halevi and Tal Rabin, editors, TCC 2006, volume 3876, pages 265-284. Springer, 2006. URL:
  11. Arpita Ghosh and Aaron Roth. Selling privacy at auction. Games and Economic Behavior, 2013. Google Scholar
  12. Sanjay Jain and P. K. Kannan. Pricing of information products on online servers: Issues, models, and analysis. Management Science, 48(9):1123-1142, 2002. Google Scholar
  13. Boris Köpf and David Basin. An information-theoretic model for adaptive side-channel attacks. In CCS, pages 286-296. ACM, 2007. Google Scholar
  14. Boris Köpf and Andrey Rybalchenko. Approximation and randomization for quantitative information-flow analysis. In CSF, 2010, pages 3-14. IEEE, July 2010. Google Scholar
  15. Paraschos Koutris, Prasang Upadhyaya, Magdalena Balazinska, Bill Howe, and Dan Suciu. Query-based data pricing. In Michael Benedikt, Markus Krötzsch, and Maurizio Lenzerini, editors, PODS, pages 167-178. ACM, 2012. URL:
  16. Paraschos Koutris, Prasang Upadhyaya, Magdalena Balazinska, Bill Howe, and Dan Suciu. Querymarket demonstration: Pricing for online data markets. PVLDB, 5(12):1962-1965, 2012. Google Scholar
  17. Paraschos Koutris, Prasang Upadhyaya, Magdalena Balazinska, Bill Howe, and Dan Suciu. Toward practical query pricing with querymarket. In Kenneth A. Ross, Divesh Srivastava, and Dimitris Papadias, editors, ACMSIGMOD 2013, pages 613-624. ACM, 2013. URL:, URL:
  18. C. Li and G. Miklau. Pricing aggregate queries in a data marketplace. In WebDB, 2012. Google Scholar
  19. Chao Li, Daniel Yang Li, Gerome Miklau, and Dan Suciu. A theory of pricing private data. ACM Trans. Database Syst., 39(4):34:1-34:28, 2014. URL:
  20. Bing-Rong Lin and Daniel Kifer. On arbitrage-free pricing for general data queries. PVLDB, 7(9):757-768, 2014. URL:
  21. J.L. Massey. Guessing and entropy. In Information Theory, 1994, page 204, Jun 1994. URL:
  22. Frank McSherry. Privacy integrated queries: an extensible platform for privacy-preserving data analysis. In Ugur Çetintemel, Stanley B. Zdonik, Donald Kossmann, and Nesime Tatbul, editors, ACM SIGMOD 2009, pages 19-30. ACM, 2009. URL:
  23. Alan Nash, Luc Segoufin, and Victor Vianu. Determinacy and rewriting of conjunctive queries using views: A progress report. In ICDT, pages 59-73, 2007. URL:
  24. Alan Nash, Luc Segoufin, and Victor Vianu. Views and queries: Determinacy and rewriting. ACM Trans. Database Syst., 35(3), 2010. URL:
  25. A. Renyi. On measures of information and entropy. In Berkeley Symposium on Mathematics, Statistics and Probability, pages 547-561, 1960. URL:
  26. Geoffrey Smith. On the foundations of quantitative information flow. In Luca de Alfaro, editor, FOSSACS 2009, LNCS, pages 288-302. Springer, 2009. URL:
  27. Constantino Tsallis. Possible generalization of boltzmann-gibbs statistics. Journal of Statistical Physics, 52(1-2):479-487, 1988. URL: