Feedback-based annotation, selection and refinement of schema mappings for dataspaces

Khalid Belhajjame; Norman W. Paton; Suzanne M. Embury; Alvaro A A Fernandes; Cornelia Hedeler

doi:10.1145/1739041.1739110

Feedback-based annotation, selection and refinement of schema mappings for dataspaces

Khalid Belhajjame, Norman W. Paton, Suzanne M. Embury, Alvaro A A Fernandes, Cornelia Hedeler

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

The specification of schema mappings has proved to be time and resource consuming, and has been recognized as a critical bottleneck to the large scale deployment of data integration systems. In an attempt to address this issue, dataspaces have been proposed as a data management abstraction that aims to reduce the up-front cost required to setup a data integration system by gradually specifying schema mappings through interaction with end users in a pay-as-you-go fashion. As a step in this direction, we explore an approach for incrementally annotating schema mappings using feedback obtained from end users. In doing so, we do not expect users to examine mapping specifications; rather, they comment on results to queries evaluated using the mappings. Using annotations computed on the basis of user feedback, we present a method for selecting from the set of candidate mappings, those to be used for query evaluation considering user requirements in terms of precision and recall. In doing so, we cast mapping selection as an optimization problem. Mapping annotations may reveal that the quality of schema mappings is poor. We also show how feedback can be used to support the derivation of better quality mappings from existing mappings through refinement. An evolutionary algorithm is used to efficiently and effectively explore the large space of mappings that can be obtained through refinement. The results of evaluation exercises show the effectiveness of our solution for annotating, selecting and refining schema mappings. Copyright 2010 ACM.

Original language	English
Title of host publication	Advances in Database Technology - EDBT 2010 - 13th International Conference on Extending Database Technology, Proceedings\|Adv. Database Technol. - EDBT - Int. Conf. Extending Database Technol., Proc.
Publisher	Association for Computing Machinery
Pages	573-584
Number of pages	11
ISBN (Print)	9781605589459
DOIs	https://doi.org/10.1145/1739041.1739110
Publication status	Published - 2010
Event	13th International Conference on Extending Database Technology: Advances in Database Technology - EDBT 2010 - Lausanne Duration: 1 Jul 2010 → …

Conference

Conference	13th International Conference on Extending Database Technology: Advances in Database Technology - EDBT 2010
City	Lausanne
Period	1/07/10 → …

Keywords

Data integration
Dataspaces
Mapping annotation
Mapping refinement
Mapping selection
Pay-as-you-go
User feedback

Access to Document

10.1145/1739041.1739110

Cite this

Belhajjame, K., Paton, N. W., Embury, S. M., Fernandes, A. A. A., & Hedeler, C. (2010). Feedback-based annotation, selection and refinement of schema mappings for dataspaces. In Advances in Database Technology - EDBT 2010 - 13th International Conference on Extending Database Technology, Proceedings|Adv. Database Technol. - EDBT - Int. Conf. Extending Database Technol., Proc. (pp. 573-584). Association for Computing Machinery. https://doi.org/10.1145/1739041.1739110

Belhajjame, Khalid ; Paton, Norman W. ; Embury, Suzanne M. et al. / Feedback-based annotation, selection and refinement of schema mappings for dataspaces. Advances in Database Technology - EDBT 2010 - 13th International Conference on Extending Database Technology, Proceedings|Adv. Database Technol. - EDBT - Int. Conf. Extending Database Technol., Proc.. Association for Computing Machinery, 2010. pp. 573-584

@inproceedings{d13c4bd8e36d43d0a79fd4d9e9207b43,

title = "Feedback-based annotation, selection and refinement of schema mappings for dataspaces",

abstract = "The specification of schema mappings has proved to be time and resource consuming, and has been recognized as a critical bottleneck to the large scale deployment of data integration systems. In an attempt to address this issue, dataspaces have been proposed as a data management abstraction that aims to reduce the up-front cost required to setup a data integration system by gradually specifying schema mappings through interaction with end users in a pay-as-you-go fashion. As a step in this direction, we explore an approach for incrementally annotating schema mappings using feedback obtained from end users. In doing so, we do not expect users to examine mapping specifications; rather, they comment on results to queries evaluated using the mappings. Using annotations computed on the basis of user feedback, we present a method for selecting from the set of candidate mappings, those to be used for query evaluation considering user requirements in terms of precision and recall. In doing so, we cast mapping selection as an optimization problem. Mapping annotations may reveal that the quality of schema mappings is poor. We also show how feedback can be used to support the derivation of better quality mappings from existing mappings through refinement. An evolutionary algorithm is used to efficiently and effectively explore the large space of mappings that can be obtained through refinement. The results of evaluation exercises show the effectiveness of our solution for annotating, selecting and refining schema mappings. Copyright 2010 ACM.",

keywords = "Data integration, Dataspaces, Mapping annotation, Mapping refinement, Mapping selection, Pay-as-you-go, User feedback",

author = "Khalid Belhajjame and Paton, {Norman W.} and Embury, {Suzanne M.} and Fernandes, {Alvaro A A} and Cornelia Hedeler",

year = "2010",

doi = "10.1145/1739041.1739110",

language = "English",

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pages = "573--584",

booktitle = "Advances in Database Technology - EDBT 2010 - 13th International Conference on Extending Database Technology, Proceedings|Adv. Database Technol. - EDBT - Int. Conf. Extending Database Technol., Proc.",

publisher = "Association for Computing Machinery",

address = "United States",

note = "13th International Conference on Extending Database Technology: Advances in Database Technology - EDBT 2010 ; Conference date: 01-07-2010",

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Belhajjame, K, Paton, NW , Embury, SM, Fernandes, AAA & Hedeler, C 2010, Feedback-based annotation, selection and refinement of schema mappings for dataspaces. in Advances in Database Technology - EDBT 2010 - 13th International Conference on Extending Database Technology, Proceedings|Adv. Database Technol. - EDBT - Int. Conf. Extending Database Technol., Proc.. Association for Computing Machinery, pp. 573-584, 13th International Conference on Extending Database Technology: Advances in Database Technology - EDBT 2010, Lausanne, 1/07/10. https://doi.org/10.1145/1739041.1739110

Feedback-based annotation, selection and refinement of schema mappings for dataspaces. / Belhajjame, Khalid; Paton, Norman W.; Embury, Suzanne M. et al.
Advances in Database Technology - EDBT 2010 - 13th International Conference on Extending Database Technology, Proceedings|Adv. Database Technol. - EDBT - Int. Conf. Extending Database Technol., Proc.. Association for Computing Machinery, 2010. p. 573-584.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Feedback-based annotation, selection and refinement of schema mappings for dataspaces

AU - Belhajjame, Khalid

AU - Paton, Norman W.

AU - Embury, Suzanne M.

AU - Fernandes, Alvaro A A

AU - Hedeler, Cornelia

PY - 2010

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N2 - The specification of schema mappings has proved to be time and resource consuming, and has been recognized as a critical bottleneck to the large scale deployment of data integration systems. In an attempt to address this issue, dataspaces have been proposed as a data management abstraction that aims to reduce the up-front cost required to setup a data integration system by gradually specifying schema mappings through interaction with end users in a pay-as-you-go fashion. As a step in this direction, we explore an approach for incrementally annotating schema mappings using feedback obtained from end users. In doing so, we do not expect users to examine mapping specifications; rather, they comment on results to queries evaluated using the mappings. Using annotations computed on the basis of user feedback, we present a method for selecting from the set of candidate mappings, those to be used for query evaluation considering user requirements in terms of precision and recall. In doing so, we cast mapping selection as an optimization problem. Mapping annotations may reveal that the quality of schema mappings is poor. We also show how feedback can be used to support the derivation of better quality mappings from existing mappings through refinement. An evolutionary algorithm is used to efficiently and effectively explore the large space of mappings that can be obtained through refinement. The results of evaluation exercises show the effectiveness of our solution for annotating, selecting and refining schema mappings. Copyright 2010 ACM.

AB - The specification of schema mappings has proved to be time and resource consuming, and has been recognized as a critical bottleneck to the large scale deployment of data integration systems. In an attempt to address this issue, dataspaces have been proposed as a data management abstraction that aims to reduce the up-front cost required to setup a data integration system by gradually specifying schema mappings through interaction with end users in a pay-as-you-go fashion. As a step in this direction, we explore an approach for incrementally annotating schema mappings using feedback obtained from end users. In doing so, we do not expect users to examine mapping specifications; rather, they comment on results to queries evaluated using the mappings. Using annotations computed on the basis of user feedback, we present a method for selecting from the set of candidate mappings, those to be used for query evaluation considering user requirements in terms of precision and recall. In doing so, we cast mapping selection as an optimization problem. Mapping annotations may reveal that the quality of schema mappings is poor. We also show how feedback can be used to support the derivation of better quality mappings from existing mappings through refinement. An evolutionary algorithm is used to efficiently and effectively explore the large space of mappings that can be obtained through refinement. The results of evaluation exercises show the effectiveness of our solution for annotating, selecting and refining schema mappings. Copyright 2010 ACM.

KW - Data integration

KW - Dataspaces

KW - Mapping annotation

KW - Mapping refinement

KW - Mapping selection

KW - Pay-as-you-go

KW - User feedback

U2 - 10.1145/1739041.1739110

DO - 10.1145/1739041.1739110

M3 - Conference contribution

SN - 9781605589459

SP - 573

EP - 584

BT - Advances in Database Technology - EDBT 2010 - 13th International Conference on Extending Database Technology, Proceedings|Adv. Database Technol. - EDBT - Int. Conf. Extending Database Technol., Proc.

PB - Association for Computing Machinery

T2 - 13th International Conference on Extending Database Technology: Advances in Database Technology - EDBT 2010

Y2 - 1 July 2010

ER -

Belhajjame K, Paton NW , Embury SM, Fernandes AAA, Hedeler C. Feedback-based annotation, selection and refinement of schema mappings for dataspaces. In Advances in Database Technology - EDBT 2010 - 13th International Conference on Extending Database Technology, Proceedings|Adv. Database Technol. - EDBT - Int. Conf. Extending Database Technol., Proc.. Association for Computing Machinery. 2010. p. 573-584 doi: 10.1145/1739041.1739110

Feedback-based annotation, selection and refinement of schema mappings for dataspaces

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