Preserving mapping consistency under schema changes

Velegrakis, Yannis; Miller, John A.; Popa, Lucian

doi:10.1007/s00778-004-0136-2

Cited by 53 publications

(49 citation statements)

References 29 publications

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“…Due to its great significance and practical importance, the database evolution has already gained research attention. Several works have identified this problem as a great challenge for database researchers (Roddick, 2000) and various efforts have been proposed so far (Bellahsene, 2002), (Gupta, 2001), (Nica, 1998), (Velegrakis, 2004). In our work, we extend previous results (Nica, 1998) by incorporating the addition of attributes and by appropriately treating conditions.…”

Section: Introductionmentioning

confidence: 53%

“…In our work, we extend previous results (Nica, 1998) by incorporating the addition of attributes and by appropriately treating conditions. Also, we allow the restructuring of the database, which is considered as a graph in our framework, towards either the retention of the original query semantics -a similar but quite restrictive approach has been proposed by (Velegrakis, 2004) -or their appropriate readjustment to the new semantics. In addition, we complement our approach by proposing an elegant extension to the SQL language for the management of database evolution.…”

Section: Introductionmentioning

confidence: 99%

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Language Extensions for the Automation of Database Schema Evolution

Papastefanatos¹,

Vassiliadis²,

Simitsis³

et al. 2008

Proceedings of the Tenth International Conference on Enterprise Information Systems

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Abstract:The administrators and designers of modern Information Systems face the problem of maintaining their systems in the presence of frequently occurring changes in any counterpart of it. In other words, when a change occurs in any point of the system -e.g., source, schema, view, software construct-they should propagate the change in all the involved parts of the system. Hence, it is imperative that the whole process should be done correctly, i.e., the change should be propagated to all the appropriate points of the system, with a limited overhead imposed on both the system and the humans, who design and maintain it. In this paper, we are dealing with the problem of evolution in the context of databases. First, we present a coherent, graph-based framework for capturing the effect of potential changes in the database software of an Information System. Next, we describe a generic annotation policy for database evolution and we propose a feasible and powerful extension to the SQL language specifically tailored for the management of evolution. Finally, we demonstrate the efficiency and feasibility of our approach through a case study based on a realworld situation occurred in the Greek public sector.

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Section: Introductionmentioning

confidence: 53%

Section: Introductionmentioning

confidence: 99%

Language Extensions for the Automation of Database Schema Evolution

Papastefanatos¹,

Vassiliadis²,

Simitsis³

et al. 2008

Proceedings of the Tenth International Conference on Enterprise Information Systems

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show abstract

“…Hence, we have developed techniques for incrementally modifying mappings as correspondences change [49]. To keep our example simple, we assume that correspondences v 1 , v 2 , v 3 , v 4 are correct.…”

Section: Correspondencesmentioning

confidence: 99%

“…In this paper, as in other Clio work [43,49,52], we will use a more verbose form of the mapping language to make the algorithms and ideas easier to follow. Let an expression be defined by the grammar e ::= S | x | e.l, where x is a variable, S is a schema root, l is a label, and e.l is record projection.…”

Section: Fig 5 a Target Instances For Mapping (5) In Pnfmentioning

confidence: 99%

Clio: Schema Mapping Creation and Data Exchange

Fagin¹,

Haas²,

Hernández³

et al. 2009

Conceptual Modeling: Foundations and Applications

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165

118

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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.

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“…These range from data manipulation languages, and maintenance of views under changes [2], to schema evolution [3] and mapping adaptation [4]. To cope with the history of data changes, temporal models have been proposed for the relational [5] and ER [6] models, for semi-structured data [7], XML [8] and for RDF [9].…”

Section: Introductionmentioning

confidence: 99%

Modeling Concept Evolution: A Historical Perspective

Rizzolo

Velegrakis

Mylopoulos

et al. 2009

Conceptual Modeling - ER 2009

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Abstract. The world is changing, and so must the data that describes its history. Not surprisingly, considerable research effort has been spent in Databases along this direction, covering topics such as temporal models and schema evolution. A topic that has not received much attention, however, is that of concept evolution. For example, Germany (instance-level concept) has evolved several times in the last century as it went through different governance structures, then split into two national entities that eventually joined again. Likewise, a caterpillar is transformed into a butterfly, while a mother becomes two (maternally-related) entities. As well, the concept of Whale (a class-level concept) changed over the past two centuries thanks to scientific discoveries that led to a better understanding of what the concept entails. In this work, we present a formal framework for modeling, querying and managing such evolution. In particular, we describe how to model the evolution of a concept, and how this modeling can be used to answer historical queries of the form "How has concept X evolved over period Y". Our proposal extends an RDF-like model with temporal features and evolution operators. Then we provide a query language that exploits these extensions and supports historical queries.

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Preserving mapping consistency under schema changes

Cited by 53 publications

References 29 publications

Language Extensions for the Automation of Database Schema Evolution

Language Extensions for the Automation of Database Schema Evolution

Clio: Schema Mapping Creation and Data Exchange

Modeling Concept Evolution: A Historical Perspective

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