skip to main content
10.1145/3131851.3131871acmotherconferencesArticle/Chapter ViewAbstractPublication PagesppdpConference Proceedingsconference-collections
research-article
Public Access

A core calculus for provenance inspection

Published:09 October 2017Publication History

ABSTRACT

Recent research has been devoting increasing attention to provenance, or information describing the origin, derivation, and history of data, due to its relevance to critical issues including transparency, privacy, and security. Engineering a software system to make it provenance-aware by means of ad-hoc instrumentation requires a substantial effort: the development of general-purpose infrastructure is thus very important to achieve the goal of making provenance widely available. In this article we describe a core functional language equipped with a provenance-aware semantics that is sufficiently generic to accomodate many notions of provenance proposed in the literature. While existing proposals typically treat provenance views and provenance extraction as second-class, extralinguistic mechanisms, in our work provenance views are expressed as standard programs and provenance data can be reflected into the language, allowing for programs that inspect their own provenance.

References

  1. U. A. Acar, A. Ahmed, J. Cheney, and R. Perera. 2013. A core calculus for provenance. Journal of Computer Security 21 (2013), 919--969. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. F. Bavera and E. Bonelli. 2015. Justification logic and audited computation. Journal of Logic and Computation (2015). Published online, June 19, 2015.Google ScholarGoogle Scholar
  3. David A. Bearman. 1985. The Power of the Principle of Provenance. Archivaria 21 (1985), 14âĂŞ27.Google ScholarGoogle Scholar
  4. Deepavali Bhagwat, Laura Chiticariu, Wang-Chiew Tan, and Gaurav Vijayvargiya. 2005. An annotation management system for relational databases. VLDB Journal 14, 4 (2005), 373--396.Google ScholarGoogle ScholarCross RefCross Ref
  5. Rajendra Bose and James Frew. 2005. Lineage retrieval for scientific data processing: a survey. ACM Comput. Surv. 37, 1 (2005), 1--28. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Uri Braun, Avraham Shinnar, and Margo I. Seltzer. 2008. Securing Provenance. In HotSec. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Peter Buneman, James Cheney, and Stijn Vansummeren. 2008. On the expressiveness of implicit provenance in query and update languages. ACM Transactions on Database Systems 33, 4 (November 2008), 28. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Peter Buneman, Sanjeev Khanna, and Wang-Chiew Tan. 2001. Why and Where: A Characterization of Data Provenance. In ICDT (LNCS). 316--330. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. J. Cheney. 2011. A formal framework for provenance security. In Proceedings of the 24th IEEE Computer Security Foundations Symposium (CSF). IEEE, 281--293. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. James Cheney, Amal Ahmed, and Umut a. Acar. 2011. Provenance As Dependency Analysis. Mathematical. Structures in Comp. Sci. 21, 6 (Dec. 2011), 1301--1337. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Yingwei Cui, Jennifer Widom, and Janet L. Wiener. 2000. Tracing the lineage of view data in a warehousing environment. ACM Trans. Database Syst. 25, 2 (2000), 179--227. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Susan B. Davidson and Juliana Freire. 2008. Provenance and Scientific Workflows: Challenges and Opportunities. In Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data (SIGMOD '08). ACM, New York, NY, USA, 1345--1350. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Susan B. Davidson, Sanjeev Khanna, Sudeepa Roy, and Sarah Cohen Boulakia. 2010. Privacy Issues in Scientific Workflow Provenance. In Proceedings of the 1st International Workshop on Workflow Approaches to New Data-centric Science (Wands '10). ACM, New York, NY, USA, Article 3, 6 pages. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Boris Glavic and Gustavo Alonso. 2009. Provenance for Nested Subqueries. In Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology (EDBT '09). ACM, New York, NY, USA, 982--993. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Boris Glavic, Renée J. Miller, and Gustavo Alonso. 2013. Using SQL for Efficient Generation and Querying of Provenance Information. In In Search of Elegance in the Theory and Practice of Computation. 291--320.Google ScholarGoogle Scholar
  16. Kwan Hee Han, Seock Kyu Yoo, and Bohyun Kim. 2009. Qualitative and Quantitative Analysis of Workflows Based on the UML Activity Diagram and Petri Net. WSEAS Trans. Info. Sci. and App. 6, 7 (July 2009), 1249--1258. http://dl.acm.org/citation.cfm?id=1639420.1639437 Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Ragib Hasan, Radu Sion, and Marianne Winslett. 2007. Introducing Secure Provenance: Problems and Challenges. In Proceedings of the 2007 ACM Workshop on Storage Security and Survivability (StorageSS '07). ACM, New York, NY, USA, 13--18. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Zachary Hensley, Jibonananda Sanyal, and Joshua New. 2013. Provenance in Sensor Data Management. Queue 11, 12, Article 50 (Dec. 2013), 14 pages. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Jan Hidders, Natalia Kwasnikowska, Jacek Sroka, Jerzy Tyszkiewicz, and Jan Van den Bussche. 2007. A Formal Model of Dataflow Repositories. In Proceedings of the 4th International Conference on Data Integration in the Life Sciences (DILS'07). Springer-Verlag, Berlin, Heidelberg, 105--121. http://dl.acm.org/citation.cfm?id=1768933.1768947 Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Wilmer Ricciotti and James Cheney. 2017. Strongly Normalizing Audited Computation. In 26th EACSL Annual Conference on Computer Science Logic (CSL 2017) (Leibniz International Proceedings in Informatics (LIPIcs)), Valentin Goranko and Mads Dam (Eds.), Vol. 82. Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik, Dagstuhl, Germany, 36:1--36:21.Google ScholarGoogle Scholar
  21. Wilmer Ricciotti, Jan Stolarek, Roly Perera, and James Cheney. 2017. Imperative functional programs that explain their work. In ICFP 2017. In press. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. T. R. Schellenberg. 1965. The Principle of Provenance and Modern Records in the United States. The American Archivist 28, 1 (1965), 39--41.Google ScholarGoogle ScholarCross RefCross Ref
  23. Yogesh Simmhan, Beth Plale, and Dennis Gannon. 2005. A survey of data provenance in e-science. SIGMOD Record 34, 3 (2005), 31--36. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. A core calculus for provenance inspection

        Recommendations

        Comments

        Login options

        Check if you have access through your login credentials or your institution to get full access on this article.

        Sign in
        • Published in

          cover image ACM Other conferences
          PPDP '17: Proceedings of the 19th International Symposium on Principles and Practice of Declarative Programming
          October 2017
          436 pages
          ISBN:9781450352918
          DOI:10.1145/3131851

          Copyright © 2017 ACM

          Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

          Publisher

          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 9 October 2017

          Permissions

          Request permissions about this article.

          Request Permissions

          Check for updates

          Qualifiers

          • research-article

          Acceptance Rates

          PPDP '17 Paper Acceptance Rate18of28submissions,64%Overall Acceptance Rate230of486submissions,47%

        PDF Format

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader