Efficiently updating materialized views

Blakeley, José A.; Larson, Per-Åke; Tompa, Frank Wm.

doi:10.1145/16894.16861

Cited by 263 publications

(113 citation statements)

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“…-Caching. We apply the view maintenance technique [6] with a repository storing intermediate results along the process. The rationale behind is that collaborative reconciliation is incremental as a change (insertion or removal) only affects some arguments.…”

Section: Technical Challengesmentioning

confidence: 99%

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Collaborative Schema Matching Reconciliation

Nguyen

Luong

Miklós

et al. 2013

On the Move to Meaningful Internet Systems: OTM 2013 Conferences

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Abstract. Schema matching is the process of establishing correspondences between the attributes of database schemas for data integration purpose. Although several schema matching tools have been developed, their results are often incomplete or erroneous. To obtain correct attribute correspondences, in practice, human experts edit the mapping results and fix the mapping problems. As the scale and complexity of data integration tasks have increased dramatically in recent years, the reconciliation phase becomes more and more a bottleneck. Moreover, one often needs to establish the correspondences in not only between two but a network of schemas simultaneously. In such reconciliation settings, it is desirable to involve several experts. In this paper, we propose a tool that supports a group of experts to collaboratively reconcile a set of matched correspondences. The experts might have conflicting views whether a given correspondence is correct or not. As one expects global consistency conditions in the network, the conflict resolution might require discussion and negotiation among the experts to resolve such disagreements. We have developed techniques and a tool that allow approaching this reconciliation phase in a systematic way. We represent the expert's views as arguments to enable formal reasoning on the assertions of the experts. We detect complex dependencies in their arguments, guide and present them the possible consequences of their decisions. These techniques thus can greatly help them to overlook the complex cases and work more effectively.

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Section: Technical Challengesmentioning

confidence: 99%

“…Many thanks to SAP 6 and MOM 7 for providing use cases and data sets as well as evaluating our tool.…”

Section: Acknowledgmentmentioning

confidence: 99%

Collaborative Schema Matching Reconciliation

Nguyen

Luong

Miklós

et al. 2013

On the Move to Meaningful Internet Systems: OTM 2013 Conferences

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“…Our query views correspond to get, while update and merge views combined define putback. One of our key distinguishing contributions is a technique for propagating updates incrementally using view maintenance [6,20], which is critical for practical deployment. Another one is a fundamentally different mechanism for obtaining the views, by compiling them from mappings, which allows describing complex mapping scenarios in an elegant way.…”

Section: Related Workmentioning

confidence: 99%

Compiling mappings to bridge applications and databases

Melnik

Adya

Bernstein

2008

ACM Trans. Database Syst.

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Translating data and data access operations between applications and databases is a longstanding data management problem. We present a novel approach to this problem, in which the relationship between the application data and the persistent storage is specified using a declarative mapping, which is compiled into bidirectional views that drive the data transformation engine. Expressing the application model as a view on the database is used to answer queries, while viewing the database in terms of the application model allows us to leverage view maintenance algorithms for update translation. This approach has been implemented in a commercial product. It enables developers to interact with a relational database via a conceptual schema and an object-oriented programming surface. We outline the implemented system and focus on the challenges of mapping compilation, which include rewriting queries under constraints and supporting non-relational constructs.

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“…There has been substantial work on incremental query and view maintenance in databases (e.g., [1,15,16]) and rule-based systems (e.g., Datalog [4,5]). While related, our work addresses a more expressive formalism; further, traditionally in database systems the problem of incremental maintenance is considered with respect to data (corresponding to DL ABoxes) and not with respect to the database schema (corresponding to DL TBoxes).…”

Section: Related Workmentioning

confidence: 99%

History Matters: Incremental Ontology Reasoning Using Modules

2007

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Abstract. The development of ontologies involves continuous but relatively small modifications. Existing ontology reasoners, however, do not take advantage of the similarities between different versions of an ontology. In this paper, we propose a technique for incremental reasoning-that is, reasoning that reuses information obtained from previous versions of an ontology-based on the notion of a module. Our technique does not depend on a particular reasoning calculus and thus can be used in combination with any reasoner. We have applied our results to incremental classification of OWL DL ontologies and found significant improvement over regular classification time on a set of real-world ontologies.

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Efficiently updating materialized views

Cited by 263 publications

References 0 publications

Collaborative Schema Matching Reconciliation

Collaborative Schema Matching Reconciliation

Compiling mappings to bridge applications and databases

History Matters: Incremental Ontology Reasoning Using Modules

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