Data contracts for cloud-based data marketplaces

  • Authors:

  • Hong-Linh Truong;Marco Comerio;Flavio De Paoli;G. R. Gangadharan;Schahram Dustdar

  • Affiliations:

  • Distributed Systems Group, Argentinierstrasse 8/184-1, A-1040 Vienna, Austria.;Department of Informatics, Systems and Communication, University of Milano-Bicocca, viale Sarca 336/14, 20126, Milano, Italy.;Department of Informatics, Systems and Communication, University of Milano-Bicocca, viale Sarca 336/14, 20126, Milano, Italy.;Institute for Development and Research in Banking Technology, Castle Hills, Road No. 1, Masab Tank, Hyderabad-500057 India.;Distributed Systems Group, Argentinierstrasse 8/184-1, A-1040 Vienna, Austria

  • Venue:
  • International Journal of Computational Science and Engineering
  • Year:
  • 2012

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Abstract

Currently, rich and diverse data types have been increasingly provided using the data-as-a-service (DaaS) model, a form of cloud computing services and the core element of data marketplaces. This facilitates the on-the-fly data composition and utilisation for several dataintensive applications in e-science and business domains. However, data offered by DaaS are constrained by several data concerns that, if not automatically being reasoned properly, will lead to a wrong way of using them. In this paper, we support the view that data concerns should be explicitly modelled and specified in data contracts to support concern-aware data selection and utilisation. We perform a detailed analysis of current techniques for data contracts in the cloud. Instead of relying on a specific representation of data contracts, we introduce an abstract model for data contracts that can be used to build different types of data contracts for specific types of data. Based on the abstract model, we propose several techniques for evaluating data contracts that can be integrated into data service selection and composition frameworks. We also illustrate our approach with some real-world scenarios and show how data contracts can be integrated into data agreement exchange services in the cloud.