On the logical foundations of schema integration and evolution in heterogeneous database systems

Lakshmanan, Laks V. S.; Sadri, Fereidoon; Subramanian, Iyer N.

doi:10.1007/3-540-57530-8_6

Cited by 57 publications

(28 citation statements)

References 17 publications

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“…Lakshmanan et al [11] argue that a uniform framework for schema integration and schema evolution is both desirable and possible, and this is our view also. They define a higher-order logic language, SchemaSQL, which handles both data integration and schema evolution in relational multi-database systems.…”

Section: Introductionmentioning

confidence: 77%

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Schema Evolution in Data Warehousing Environments – A Schema Transformation-Based Approach

Fan

Poulovassilis

2004

Lecture Notes in Computer Science

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Abstract. In heterogeneous data warehousing environments, autonomous data sources are integrated into a materialised integrated database. The schemas of the data sources and the integrated database may be expressed in different modelling languages. It is possible for either the data source schemas or the warehouse schema to evolve. This evolution may include evolution of the schema, or evolution of the modelling language in which the schema is expressed, or both. In such scenarios, it is important for the integration framework to be evolvable, so that the previous integration effort can be reused as much as possible. This paper describes how the AutoMed heterogeneous data integration toolkit can be used to handle the problem of schema evolution in heterogeneous data warehousing environments. This problem has been addressed before for specific data models, but AutoMed has the ability to cater for multiple data models, and for changes to the data model.

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Section: Introductionmentioning

confidence: 77%

“…Schema evolution within the relational data model has been discussed in previous work such as [11,12,18]. The approach in [18] uses a first-order schema in which all values in a schema of interest to a user are modelled as data, and other schemas can be expressed as a query over this first-order schema.…”

Section: Discussionmentioning

confidence: 99%

Schema Evolution in Data Warehousing Environments – A Schema Transformation-Based Approach

Fan

Poulovassilis

2004

Lecture Notes in Computer Science

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“…SchemaLog [Lakshmanan et al 1997[Lakshmanan et al , 1993 is another logic programming language supporting metadata querying and interoperability, in the vein of LDL and HiLog. Like HiLog, SchemaLog has a second-order syntax but first-order semantics.…”

Section: Schemalogmentioning

confidence: 99%

Relational languages for metadata integration

Wyss

Robertson

2005

ACM Trans. Database Syst.

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In this article, we develop a relational algebra for metadata integration, Federated Interoperable Relational Algebra (FIRA). FIRA has many desirable properties such as compositionality, closure, a deterministic semantics, a modest complexity, support for nested queries, a subalgebra equivalent to canonical Relational Algebra (RA), and robustness under certain classes of schema evolution. Beyond this, FIRA queries are capable of producing fully dynamic output schemas, where the number of relations and/or the number of columns in relations of the output varies dynamically with the input instance. Among existing query languages for relational metadata integration, only FIRA provides generalized dynamic output schemas, where the values in any (fixed) number of input columns can determine output schemas.Further contributions of this article include development of an extended relational model for metadata integration, the Federated Relational Data Model, which is strictly downward compatible with the relational model. Additionally, we define the notion of Transformational Completeness for relational query languages and postulate FIRA as a canonical transformationally complete language. We also give a declarative, SQL-like query language that is equivalent to FIRA, called Federated Interoperable Structured Query Language (FISQL).While our main contributions are conceptual, the federated model, FISQL/FIRA, and the notion of transformational completeness nevertheless have important applications to data integration and OLAP. In addition to summarizing these applications, we illustrate the use of FIRA to optimize FISQL queries using rule-based transformations that directly parallel their canonical relational counterparts. We conclude the article with an extended discussion of related work as well as an indication of current and future work on FISQL/FIRA.

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“…For ontology-rule synergy, OBDA and RBDA have been generalized to Knowledge-Based Data Access (KBDA). 4 While the earlier logic-database combinations, e.g. procedural Prolog-SQL interfaces, interleaved knowledge-based reasoning with data access, KBDA keeps these layers separate, using declarative mappings to bridge between the two.…”

Section: Introductionmentioning

confidence: 99%

“…KBDA builds on earlier work in knowledge-based information/data/schema integration (e.g., [3][4][5]). It integrates data complying to local (heterogeneous) schemas into data complying to a global (homogeneous) schema, usually employing Global-As-View (GAV) mappings.…”

Section: Introductionmentioning

confidence: 99%

A Datalog+ RuleML 1.01 Architecture for Rule-Based Data Access in Ecosystem Research

Boley

Grütter

Zou

et al. 2014

Rules on the Web. From Theory to Applications

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Abstract. Rule-Based Data Access (RBDA) enables automated reasoning over a knowledge base (KB) as a generalized global schema for the data in local (e.g., relational or graph) databases reachable through mappings. RBDA can semantically validate, enrich, and integrate heterogeneous data sources. This paper proposes an RBDA architecture layered on Datalog + RuleML, and uses it for the ∆Forest case study on the susceptibility of forests to climate change. Deliberation RuleML [⊥] through MYNG, the RuleML Modular sYNtax confiGurator generating (Relax NG and XSD) schemas from language-feature selections. The ∆Forest case study on climate change employs data derived from three main forest monitoring networks in Switzerland. The KB includes background knowledge about the study sites and design, e.g., abundant tree species groups, pure tree stands, and statistical independence among forest plots. The KB is used to rewrite queries about, e.g., the eligible plots for studying a particular species group. The mapping rules unfold our newly designed global schema to the three given local schemas, e.g. for the grade of forest management. The RBDA/∆Forest case study has shown the usefulness of our approach to Ecosystem Research for global schema design and demonstrated how automated reasoning can become key to knowledge modeling and consolidation for complex statistical data analysis.

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On the logical foundations of schema integration and evolution in heterogeneous database systems

Cited by 57 publications

References 17 publications

Schema Evolution in Data Warehousing Environments – A Schema Transformation-Based Approach

Schema Evolution in Data Warehousing Environments – A Schema Transformation-Based Approach

Relational languages for metadata integration

A Datalog+ RuleML 1.01 Architecture for Rule-Based Data Access in Ecosystem Research

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