Pay-as-you-go Data Integration

Primary supervisor

Additional supervisors

  • Alvaro Fernandes
  • Suzanne Embury

Additional information

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Other projects with the same supervisor

Funding

  • Competition Funded Project (European/UK Students Only)
This research project is one of a number of projects at this institution. It is in competition for funding with one or more of these projects. Usually the project which receives the best applicant will be awarded the funding. The funding is available to citizens of a number of European countries (including the UK). In most cases this will include all EU nationals. However full funding may not be available to all applicants and you should read the full department and project details for further information.

Project description

The vision of pay-as-you-go data integration has been articulated as providing various of the benefits of classical data integration, but with reduced up-front costs, combined with opportunities for incremental refinement, enabling a "pay as you go" approach. In a typical pay-as-you-go proposal, there is an initial automatic integration phase that produces rather poor quality results, and the integration is revised in the light of feedback from end-users, database experts, or from crowd sourcing.

Classically, data integration involves tasks such as identifying sources to integrate, finding matches between these sources, developing executable mappings between sources, and identifying duplicates among instances. In principle, all of these steps can benefit from a pay-as-you-go approach. Furthermore, pay-as-you-go techniques can be applied in different settings, from personal information management to web scale data access, and we have recently been working on linked open data.Research opportunities are available on a range of topics relating to pay-as-you-go data integration, including crowd sourcing for data integration, cost-effective feedback collection, and integrating data instances. PhD projects in this area at Manchester could involve Norman Paton, Alvaro Fernandes and Suzanne Embury, who work on different challenges and techniques. For initial enquiries, please approach Norman Paton (npaton@manchester.ac.uk).

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