Journal article
Balancing expressiveness and inexpressiveness in view design
- Abstract:
- We study the design of data publishing mechanisms that allow a collection of autonomous distributed data sources to collaborate to support queries. A common mechanism for data publishing is via views: functions that expose derived data to users, usually specified as declarative queries. Our autonomy assumption is that the views must be on individual sources, but with the intention of supporting integrated queries. In deciding what data to expose to users, two considerations must be balanced. The views must be sufficiently expressive to support queries that users want to ask—the utility of the publishing mechanism. But there may also be some expressiveness restrictions. Here, we consider two restrictions, a minimal information requirement, saying that the views should reveal as little as possible while supporting the utility query, and a non-disclosure requirement, formalizing the need to prevent external users from computing information that data owners do not want revealed. We investigate the problem of designing views that satisfy both expressiveness and inexpressiveness requirements, for views in a restricted information systems - query languages (conjunctive queries), and for arbitrary views.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
-
-
(Preview, Accepted manuscript, 712.6KB, Terms of use)
-
- Publisher copy:
- 10.1145/3488370
Authors
+ Engineering and Physical Sciences Research Council
More from this funder
- Grant:
- EP/M005852/1
- EP/T022124/1
- Publisher:
- Association for Computing Machinery
- Journal:
- ACM Transactions on Database Systems More from this journal
- Volume:
- 46
- Issue:
- 4
- Article number:
- 15
- Publication date:
- 2021-11-15
- Acceptance date:
- 2021-09-01
- DOI:
- EISSN:
-
1557-4644
- ISSN:
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0362-5915
- Language:
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English
- Keywords:
- Pubs id:
-
1196712
- Local pid:
-
pubs:1196712
- Deposit date:
-
2021-10-04
Terms of use
- Copyright holder:
- Association for Computing Machinery.
- Copyright date:
- 2021
- Rights statement:
- © 2021 Association for Computing Machinery.
- Notes:
- This is the accepted manuscript version of the article. The final version is available from Association for Computing Machinery at https://doi.org/10.1145/3488370
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