A formal model for temporal schema versioning in object-oriented databases

Grandi, Fábio; Mandreoli, Federica

doi:10.1016/s0169-023x(02)00207-0

Cited by 28 publications

(14 citation statements)

References 39 publications

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“…), and defines a set of evolution operators. The work presented here extends our previous evolution model and language presented in [3] and is inspired from the object-oriented evolution model in [8].…”

Section: Related Workmentioning

confidence: 98%

A Model and Language for Bitemporal Schema Versioning in Data Warehouses

Rechy-Ramirez¹,

Benítez–Guerrero²

2006

2006 15th International Conference on Computing

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A Data Warehouse (DW) is a vast collection of historical data built to support multidimensional data analysis applications. In this context, an important problem is that of evolving the implementation (multidimensional, relational) schema of a DW to incorporate new requirements. This paper introduces a conceptual evolution model based on bitemporal versioning of multidimensional schemas, which allows one to modify the DW schema (a) in an implementation-independent manner, and (b) without affecting the operation of existing applications.It also presents a SQL-like language associated to this model, which offers expressions to create and change versions of multidimensional schemas.

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Section: Related Workmentioning

confidence: 98%

A Model and Language for Bitemporal Schema Versioning in Data Warehouses

Rechy-Ramirez¹,

Benítez–Guerrero²

2006

2006 15th International Conference on Computing

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“…The BCDM has been used widely, including in data warehouses, temporal OODBS, schema versioning, and XML support [12], [21], [22], [23], [24], [25].…”

Section: The Bcdm Temporal Data Modelmentioning

confidence: 99%

Schema Vacuuming in Temporal Databases

Roddick

2009

IEEE Trans. Knowl. Data Eng.

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Abstract-Temporal databases facilitate the support of historical information by providing functions for indicating the intervals during which a tuple was applicable (along one or more temporal dimensions). Because data are never deleted, only superceded, temporal databases are inherently append-only, resulting, over time, in a large historical sequence of database states. Data vacuuming in temporal databases allows for this sequence to be shortened by strategically, and irrevocably, deleting obsolete data. Schema versioning allows users to maintain a history of database schemata without compromising the semantics of the data or the ability to view data through historical schemata. While the techniques required for data vacuuming in temporal databases have been relatively well covered, the associated area of vacuuming schemata has received less attention. This paper discusses this issue and proposes a mechanism that fits well with existing methods for data vacuuming and schema versioning.

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“…A schema, which describes the structure of the data that are stored, can evolve. An evolving schema is a collection of schema versions supporting one or two temporal dimension, on-time schema versioning with no reference to time (only current schema can be modified with access to older versions), and/or a temporal validity assigned to different versions that can be accessed and modified [27]. In the object versioning strategies used in this work, only the current version is modified according to events, which are time-stamped as both absolute time and relative time, and all the versions can be accessed.…”

Section: Schema Versioningmentioning

confidence: 99%