Compose

Schema mapping evolution through composition and inversion

Authors: 
Fagin, R; Kolaitis, PG; Popa, L; Tan, WC
Year: 
2011
Venue: 
Schema matching and mapping

Mappings between different representations of data are the essential building blocks for
many information integration tasks. A schema mapping is a high-level specification
of the relationship between two schemas, and represents a useful abstraction that specifies
how the data from a source format can be transformed into a target format. The development
of schema mappings is laborious and time-consuming, even in the presence of tools that facilitate
this development. At the same time, schema evolution inevitably causes the invalidation of

Schema matching and mapping

Authors: 
Bellahsène, Z; Bonifati, A; Rahm, E
Year: 
2011
Venue: 
Springer

The book edited by Bellahsene, Bonifati and Rahm provides an overview of the ways in which the schema and ontology matching and mapping tools have addressed the above requirements and points to the open technical challenges. The contributions from leading experts are structured into three parts: large-scale and knowledge-driven schema matching, quality-driven schema mapping and evolution, and evaluation and tuning of matching tasks.

GOMMA: A Component-based Infrastructure for managing and analyzing Life Science Ontologies and their Evolution

Authors: 
Kirsten, T.; Gross, A.; Hartung, M.; Rahm, E.
Year: 
2011
Venue: 
Journal of Biomedical Semantics 2011, 2:6

Background
Ontologies are increasingly used to structure and semantically describe entities of domains, such as genes and proteins in life sciences. Their increasing size and the high frequency of updates resulting in a large set of ontology versions necessitates efficient management and analysis of this data.

Results

E ffective Mapping Composition for Biomedical Ontologies

Authors: 
Hartung, M.; Gross, A.; Kirsten, T.; Rahm, E.
Year: 
2012
Venue: 
Semantic Interoperability in Medical Informatics @ ESWC 2012

There is an increasing need to interconnect biomedical ontologies. We investigate a simple but promising approach to generate mappings between ontologies by reusing and composing existing mappings across intermediate ontologies. Such an approach is especially promising for highly interconnected ontologies such as in the life science domain. There may be many ontologies that can be used for composition so that the problem arises to fi nd the most suitable ones providing the best results.

Mapping Composition for Matching Large Life Science Ontologies

Authors: 
Gross, A.; Hartung, M.; Kirsten, T.; Rahm, E.
Year: 
2011
Venue: 
2nd International Conference on Biomedical Ontology (ICBO)

There is an increasing need to interrelate different life science ontologies in order to facilitate data integration or semantic data analysis. Ontology matching aims at a largely automatic generation of mappings between ontologies mostly by calculating the linguistic and structural similarity of their concepts. In this paper we investigate an indirect computation of ontology mappings that composes and thus reuses previously determined ontology mappings that involve intermediate ontologies. The composition approach promises a fast computation of new mappings with reduced manual effort.

Generic Schema Mappings for Composition and Query Answering

Authors: 
Kensche, David; Quix, Christoph; Li, Xiang; Li, Yong; Jarke, Matthias
Year: 
2009
Venue: 
Data & Knowledge Engineering, volume 68, issue 7, pp. 599-621, 2009

In this article we present extensional mappings, that are based on second order tuple generating dependencies between models in our Generic Role-based Metamodel GeRoMe. Our mappings support data translation between heterogeneous models, such as XML Schemas, relational schemas, or OWL ontologies. The mapping language provides grouping functionalities that allow for complete restructuring of data, which is necessary for handling object oriented models and nested data structures such as XML. Furthermore, we present algorithms for mapping composition and optimization of the composition result.

Reducing the Cost of Validating Mapping Compositions by Exploiting Semantic Relationships

Authors: 
Dragut, E.; Lawrence, R.
Year: 
2006
Venue: 
LNCS 4275

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.

Composing Schema Mappings: Second-Order Dependencies to the Rescue

Authors: 
Fagin, R.; Kolaitis, P.G.; Popa, L.; Tan, W.C.
Year: 
2004
Venue: 
PODS 2004, TODS 2005

A schema mapping is a specification that describes how data structured under one schema (the
source schema) is to be transformed into data structured under a different schema (the target
schema). A fundamental problem is composing schema mappings: given two successive schema
mappings, derive a schema mapping between the source schema of the first and the target schema
of the second that has the same effect as applying successively the two schema mappings.
In this paper, we give a rigorous semantics to the composition of schema mappings and investigate

Composition of Mappings Given by Embedded Dependencies

Authors: 
Bernstein, P.A.; Melnik, S.; Nash, A.
Year: 
2005
Venue: 
PODS 2005

Composition of mappings between schemas is essential to support
schema evolution, data exchange, data integration, and other data
management tasks. In many applications, mappings are given by
embedded dependencies. In this paper, we study the issues involved
in composing such mappings.
Our algorithms and results extend those of Fagin et al. [8] who
studied composition of mappings given by several kinds of constraints.
In particular, they proved that full source-to-target tuplegenerating
dependencies (tgds) are closed under composition, but

Implementing Mapping Composition

Authors: 
Bernstein, P.A.; Green, T.J.; Melnik, S.; Nash, A.
Year: 
2006
Venue: 
Prov. VLDB06

Mapping composition is a fundamental operation in metadata
driven applications. Given a mapping over schemas S1 and S2 and
a mapping over schemas S2 and S3, the composition problem is
to compute an equivalent mapping over S1 and S3. We describe
a new composition algorithm that targets practical applications. It
incorporates view unfolding. It eliminates as many S2 symbols as
possible, even if not all can be eliminated. It covers constraints
expressed using arbitrary monotone relational operators and, to a
lesser extent, non-monotone operators. And it introduces the new

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