Composition of mappings given by embedded dependencies

Abstract.The Clio project provides tools that vastly simplify information integration. Information integration requires data conversions to bring data in different representations into a common form. Key contributions of Clio are the definition of non-procedural schema mappings to describe the relationship between data in heterogeneous schemas, a new paradigm in which we view the mapping creation process as one of query discovery, and algorithms for automatically generating queries for data transformation from the mappings. Clio provides algorithms to address the needs of two major information integration problems, namely, data integration and data exchange. In this chapter, we present our algorithms for both schema mapping creation via query discovery, and for query generation for data exchange. These algorithms can be used in pure relational, pure XML, nested relational, or mixed relational and nested contexts.

show abstract

“…A whole area of model management has focused on such issues as mapping composition [35,21,40] and mapping inverse [18,22].…”

Section: Related Workmentioning

confidence: 99%

Clio: Schema Mapping Creation and Data Exchange

Fagin¹,

Haas²,

Hernández³

et al. 2009

Conceptual Modeling: Foundations and Applications

165

118

View full text Add to dashboard Cite

show abstract

“…As shown in [28], the problem of computing the range of a mapping (or a view, as a special case) can be reduced to that of mapping composition. Composing mappings is very challenging [15,4].…”

Section: F Is Injective and Range(f ) ⊆ Range(g)mentioning

confidence: 99%

Compiling mappings to bridge applications and databases

Melnik

Adya

Bernstein

2008

ACM Trans. Database Syst.

Self Cite

View full text Add to dashboard Cite

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.

show abstract

“…Similary, goal directed resultion strategies are also used for solving schema mapping composition problems [13,20] as well as query rewriting problems in data integration/exchange settings, where the corresponding rewriting techniques can be understood as specialized versions of resolution [3], but for which certain termination and efficiency guarantees can be given (unlike for general resolution).…”

Section: Example 1 (Informal Annotation)mentioning

confidence: 99%

A Calculus for Propagating Semantic Annotations Through Scientific Workflow Queries

Bowers

Ludäscher

2006

Current Trends in Database Technology – EDBT 2006

View full text Add to dashboard Cite

Abstract. Scientific workflows facilitate automation, reuse, and reproducibility of scientific data management and analysis tasks. Scientific workflows are often modeled as dataflow networks, chaining together processing components (called actors) that query, transform, analyse, and visualize scientific datasets. Semantic annotations relate data and actor schemas with conceptual information from a shared ontology, to support scientific workflow design, discovery, reuse, and validation in the presence of thousands of potentially useful actors and datasets. However, the creation of semantic annotations is complex and time-consuming. We present a calculus and two inference algorithms to automatically propagate semantic annotations through workflow actors described by relational queries. Given an input annotation α and a query q, forward propagation computes an output annotation α ; conversely, backward propagation infers α from q and α .

show abstract

Composition of mappings given by embedded dependencies

Cited by 55 publications

References 19 publications

Clio: Schema Mapping Creation and Data Exchange

Clio: Schema Mapping Creation and Data Exchange

Compiling mappings to bridge applications and databases

A Calculus for Propagating Semantic Annotations Through Scientific Workflow Queries

Contact Info

Product

Resources

About