System-guided view integration for object-oriented databases

Gotthard, Willi; Lockemann, Peter C.; Neufeld, Andrea

doi:10.1109/69.124894

Cited by 60 publications

(22 citation statements)

References 19 publications

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“…Schema-level matching methods may use constraint information, such as data type constraints, optionality constraints, or uniqueness constraints of attributes [3,[14][15][16][17][18][19][20]. The use of constraint information assumes that this information is meaningful for judging the similarity of database elements.…”

Section: Schema-level Techniquesmentioning

confidence: 99%

“…the relationships between database elements such as relationship-types between entity-types or foreign-key dependencies between tables [4,5,14,15,18,19,23,24,28]. The use of structural information for identifying matching database elements may be limited to local structures, where relationships only between directly connected database elements are considered, or it may encompass global structures, where the overall structure of the database is considered [14].…”

Section: Schema-level Techniquesmentioning

confidence: 99%

“…Linguistic information may be used by measuring character string similarity [3,5,14,15,18] or by using externally supplied dictionaries, thesauri or lexical databases [4,11,16,19,[21][22][23][24][25] such as WordNet [26] or CyC [27]. Such linguistic databases provide lists of homonyms, synonyms, and other standard semantic relationships between words.…”

Section: Schema-level Techniquesmentioning

confidence: 99%

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Theories of meaning in schema matching: An exploratory study

Evermann

2009

Information Systems

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Section: Schema-level Techniquesmentioning

confidence: 99%

Section: Schema-level Techniquesmentioning

confidence: 99%

Section: Schema-level Techniquesmentioning

confidence: 99%

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Theories of meaning in schema matching: An exploratory study

Evermann

2009

Information Systems

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“…1 S1.SELECTION ["is a conference author"]Author ∩ S2.authors WCI name 2 S1.SELECTION ["is a conference paper"]Paper ∩ S2.Paper WCI title WCA keywords 3 S1.Conference ∩ S2.proceedings WCI ISN WCA year, N°4 S1.Conference.name ∩ S2.Conference WCI name 5 S1.Author-Write-Paper ≡ S2.authors-Paper 6 S1.Conference-Publication-Contain-Paper ≡ S2.proceedings-papers:Paper 7 S1.Conference.name-Conference ≡ S2.Conference-proceedings With real, large schemas to be integrated, the task of identifying all relevant ICAs is far from trivial. A significant amount of research has been and is being invested into tools for automated identification of plausible correspondences [3]. These tools measure the similarity between two schemas elements by looking for identical or similar characteristics: names, identifiers, components, properties, attributes (name, domain, constraints), methods.…”

Section: / How Representations Are Relatedmentioning

confidence: 99%

“…Based on the completeness goal, a standard solution for such conflicts is to build in the IS the appropriate generalization hierarchy [3,5], as shown is table 1a. If needed, a common subtype (supertype) is added to achieve connectivity of the generalization hierarchy.…”

Section: Conflicts: Taxonomy and Solutionsmentioning

confidence: 99%

Issues and approaches of database integration

1998

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In many large companies the widespread usage of computers has led a number of different application-specific databases to be installed. As company structures evolve, boundaries between departments move, creating new business units. Their new applications will use existing data from various data stores, rather than new data entering the organization. Henceforth, the ability to make data stores interoperable becomes a crucial factor for the development of new information systems.Data interoperability may come in various degrees. At the lowest level, commercial gateways connect specific pairs of database management systems (DBMSs). Software providing facilities for defining persistent views over different databases [6] simplifies access to distant data but does not support automatic enforcement of consistency constraints among different databases. Full interoperability is achieved by distributed or federated database systems, which support integration of existing data into virtual databases (i.e. databases which are logically defined but not physically materialized). The latter allow existing databases to remain under control of their respective owners, thus supporting a harmonious coexistence of scalable data integration and site autonomy requirements [9]. Federated systems are very popular today. However, before they become marketable, many issues remain to be solved. Design issues focus on either human-centered aspects (cooperative work, including autonomy issues and negotiation procedures) or database-centered aspects (data integration, schema/database evolution). Operational issues investigate system interoperability mainly in terms of support of new transaction types, new query processing algorithms, security concerns, etc. General overviews may be found elsewhere [4,9]. This paper is devoted to database integration, possibly the most critical issue. Simply stated, database integration is the process which takes as input a set of databases, and produces as output a single unified description of the input schemas (the integrated schema) and the associated mapping information supporting integrated access to existing data through the integrated schema. As such, database integration is also used in the process of re-engineering an existing legacy system.Database integration has attracted many diverse and diverging contributions. The purpose, and the main intended contribution of this article is to provide a clear picture of what are the approaches and the current solutions and what remains to be achieved. We focus on fundamental concepts and alternatives. We first give an example to provide a context for the rest of the paper. We then present the steps involved in developing an integrated schema (see Figure 1):• Pre-integration, where input schemas are transformed to make them more homogenous (both syntactically and semantically); homogenous (both syntactically and semantically);• Correspondence identification, devoted to the identification and description of interschema relationships; and • Integration, the fina...

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