Merging Models Based on Given Correspondences

Pottinger, Rachel; Bernstein, Philip A.

doi:10.1016/b978-012722442-8/50081-1

Cited by 182 publications

(152 citation statements)

References 9 publications

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“…For instance, the composition between IsA, IsA −1 , Equality and NoRel are presented in [6] and some of the composition outcomes between IsA, Contains and HasA are reported in [17].…”

Section: Definition 2 Consider Two Modelsmentioning

confidence: 99%

“…[2,17] have also been defined for use in model management [2]. In this case, a mapping between two models A and B can be expressed by using a model, map, and two morphisms, one between A and map and the other between map and B.…”

Section: Introductionmentioning

confidence: 99%

“…It uses the elements and the relationships within the helper model to relate sets of objects in A and B (see [2] for a comprehensive description). A mapping composition algorithm is presented in [2,17] for use in model management. This composition algorithm is imperfect as it does not exploit relationships in the helper model to yield a more accurate composition result.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Reducing the Cost of Validating Mapping Compositions by Exploiting Semantic Relationships

Dragut

Lawrence

2006

On the Move to Meaningful Internet Systems 2006: CoopIS, DOA, GADA, and ODBASE

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Abstract. Defining and composing mappings are fundamental operations required in any data sharing architecture (e.g. data warehouse, data integration). Mapping composition is used to generate new mappings from existing ones and is useful when no direct mapping is available. The complexity of mapping composition depends on the amount of syntactic and semantic information in the mapping. The composition of mappings has proven to be inefficient to compute in many situations unless the mappings are simplified to binary relationships that represent "similarity" between concepts. Our contribution is an algorithm for composing metadata mappings that capture explicit semantics in terms of binary relationships. Our approach allows the hard cases of mapping composition to be detected and semi-automatically resolved, and thus reduces the manual effort required during composition. We demonstrate how the mapping composition algorithm is used to produce a direct mapping between schemas from independently produced schema-to-ontology mappings. An experimental evaluation shows that composing semantic mappings results in a more accurate composition result compared to composing mappings as morphisms.

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“…For instance, the composition between IsA, IsA −1 , Equality and NoRel are presented in [6] and some of the composition outcomes between IsA, Contains and HasA are reported in [17].…”

Section: Definition 2 Consider Two Modelsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Reducing the Cost of Validating Mapping Compositions by Exploiting Semantic Relationships

Dragut

Lawrence

2006

On the Move to Meaningful Internet Systems 2006: CoopIS, DOA, GADA, and ODBASE

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“…In Clio [PVM + 02], a user specifies a set of correspondences between items in two structurally heterogeneous schemas, and using the constraints of the schemas, the system attempts to fill in, or generate, a complete mapping. Similarly, Pottinger and Bernstein [PB03] use simple correspondences to merge structurally heterogeneous schemas for data integration.…”

Section: Related Workmentioning

confidence: 99%

An Ontology-Driven Framework for Data Transformation in Scientific Workflows

Bowers

Ludäscher

2004

Lecture Notes in Computer Science

106

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Abstract. Ecologists spend considerable effort integrating heterogeneous data for statistical analyses and simulations, for example, to run and test predictive models. Our research is focused on reducing this effort by providing data integration and transformation tools, allowing researchers to focus on "real science," that is, discovering new knowledge through analysis and modeling. This paper defines a generic framework for transforming heterogeneous data within scientific workflows. Our approach relies on a formalized ontology, which serves as a simple, unstructured global schema. In the framework, inputs and outputs of services within scientific workflows can have structural types and separate semantic types (expressions of the target ontology). In addition, a registration mapping can be defined to relate input and output structural types to their corresponding semantic types. Using registration mappings, appropriate data transformations can then be generated for each desired service composition. Here, we describe our proposed framework and an initial implementation for services that consume and produce XML data.

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“…For example, correspondences can be used to relate one element of a given schema to one element of another schema, e.g., Sint .Staff , S1 .Employee , or to relate multiple elements of one schema to one element of another schema, e.g., the correspondence Sint .Staff , {S1 .Employee, S1 .Department} states that the relation Staff in the integration schema is semantically equivalent to some combination of the relations Employee and Department of the source schema S 1 . There are several models for drawing schematic correspondences in the literature [17,7,14,12], of which the model proposed by Kim et al [12] is perhaps the most comprehensive. In the second phase of mapping specification, the views that implement the mappings necessary for rewriting the queries issued against the integration schema into queries over the schemas of the sources are specified.…”

Section: Introductionmentioning

confidence: 99%

Defining and Using Schematic Correspondences for Automatically Generating Schema Mappings

Belhajjame

Paton

et al. 2009

Notes on Numerical Fluid Mechanics and Multidisciplinary Design

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Abstract. Mapping specification has been recognised as a critical bottleneck to the large scale deployment of data integration systems. A mapping is a description using which data structured under one schema are transformed into data structured under a different schema, and is central to data integration and data exchange systems. In this paper, we argue that the classical approach of correspondence identification followed by (manual) mapping generation can be simplified through the removal of the second step by judicious refinement of the correspondences captured. As a step in this direction, we present in this paper a model for schematic correspondences that builds on and extends the classification proposed by Kim et al. to cater for the automatic derivation of mappings, and present an algorithm that shows how correspondences specified in the model proposed can be used for deriving schema mappings. The approach is illustrated using a case study from integration in proteomics.

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Merging Models Based on Given Correspondences

Cited by 182 publications

References 9 publications

Reducing the Cost of Validating Mapping Compositions by Exploiting Semantic Relationships

Reducing the Cost of Validating Mapping Compositions by Exploiting Semantic Relationships

An Ontology-Driven Framework for Data Transformation in Scientific Workflows

Defining and Using Schematic Correspondences for Automatically Generating Schema Mappings

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