Evolution and change in data management — issues and directions

Roddick, John F.; Al-Jadir, Lina; Bertossi, Leopoldo; Dumas, Marlon; Estrella, Florida; Gregersen, Heidi; Hornsby, Kathleen; Lufter, Jens; Mandreoli, Federica; Männistö, Tomi; Mayol, Enric; Wedemeijer, Lex

doi:10.1145/344788.344789

Cited by 26 publications

(9 citation statements)

References 16 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: 52%

“…A number of research works are related to the problems of database schema evolution. Roddick surveys schema versioning and evolution (Roddick, 1995) and presents a categorization of the overall issues regarding evolution and change in data management (Roddick, 2000). The problem of view adaptation after redefinition is mainly investigated in (Bellahsene, 2002;Gupta, 2001), where changes in views definition are invoked by the user and rewriting is used to keep the view consistent with the database schema.…”

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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: 52%

mentioning

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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“…Inevitably, XML documents need to be managed efficiently and effectively (Roddick et al, 2000). For example, there may be errors in the documents that need correction.…”

Section: Some Open Issuesmentioning

confidence: 99%

A survey in indexing and searching XML documents

Luk

Leong

Dillon

et al. 2002

J. Am. Soc. Inf. Sci.

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XML holds the promise to yield (1) a more precise search by providing additional information in the elements, (2) a better integrated search of documents from heterogeneous sources, (3) a powerful search paradigm using structural as well as content specifications, and (4) data and information exchange to share resources and to support cooperative search. We survey several indexing techniques for XML documents, grouping them into flatfile, semistructured, and structured indexing paradigms. Searching techniques and supporting techniques for searching are reviewed, including full text search and multistage search. Because searching XML documents can be very flexible, various search result presentations are discussed, as well as database and information retrieval system integration and XML query languages. We also survey various retrieval models, examining how they would be used or extended for retrieving XML documents. To conclude the article, we discuss various open issues that XML poses with respect to information retrieval and database research. IntroductionAn Internet search engine (e.g., Altavista or Infoseek) returns thousands of so-called matched documents from a single query, some of which are relevant and others irrelevant to the query. End users typically have problems with organizing and digesting such vast quantities of information, in which much (i.e., 75% as pointed out by Selberg and Etzioni, 1997) of the information retrieved is likely to be irrelevant. XML holds the promise that searching can be done more precisely because structural, self-describing information and meta-data (e.g., RDF) is available, to allow for context-based and/or category-based search. XML also holds the promise to model heterogeneous data, generated from databases (DBs) or from word processors, thereby enabling search engines to locate and process heterogeneous documents or records.An XML document consists of a set of elements, which are hierarchically structured, as defined by the user. Each element has a name (e.g., p for paragraph), which is defined by the user. Data of an element (say, p) can be stored inside the element delimited by its start tag (i.e., ͗p͘) and its end tag (i.e., ͗/p͘), or it can be stored as values in its attribute (e.g., ͗p idϭ "1"͘). Certain attribute value types are reserved for referencing (e.g., IDREF). An XML element is accessed typically using the XPath language. Child elements and their parent element are separated by a slash. For example, the XPath /header/author/first accesses the first element from the root element header, and then the author element.It is possible to use other mark-up languages (e.g., HTML) or proprietary formats but XML appears to be suitable for a wide variety of information retrieval (IR) tasks, specific enough to reduce modeling complexity and open enough for easy and rapid adoption. A major advantage of XML over HTML is that users can define their own tags. Tag names are typically chosen to incorporate some relationship to the semantics of the contents or the type of co...

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“…Such combinations of dimensions are very interesting, because it may often happen that there may be very little evolution in terms of either the entire set of dimensions or individual dimensions; yet some particular combinations of dimensions may show huge levels of evolution because of changes in the correlation structure of the data. A closely related problem is that of mining spatiotemporal or mobile data [21], [22], for which it is useful to have the ability to diagnose aggregate changes in spatial characteristics over time. The results of this paper are equally valuable for providing such understanding.…”

Section: Introductionmentioning

confidence: 99%

On change diagnosis in evolving data streams

Aggarwal

2005

IEEE Trans. Knowl. Data Eng.

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In recent years, the progress in hardware technology has made it possible for organizations to store and record large streams of transactional data. This results in databases which grow without limit at a rapid rate. This data can often show important changes in trends over time. In such cases, it is useful to understand, visualize, and diagnose the evolution of these trends. In this paper, we introduce the concept of velocity density estimation, a technique used to understand, visualize, and determine trends in the evolution of fast data streams. We show how to use velocity density estimation in order to create both temporal velocity profiles and spatial velocity profiles at periodic instants in time. These profiles are then used in order to predict three kinds of data evolution: dissolution, coagulation, and shift. Methods are proposed to visualize the changing data trends in a single online scan of the data stream and a computational requirement which is linear in the number of data points. The visualization techniques can also be used to provide online animations which show the changes in the data characteristics while they occur. In addition, batch processing techniques are proposed in order to quantify the level of change across different combinations of dimensions. This quantification is then used in order to determine dimensional combinations with significant evolution. The techniques discussed in this paper can be easily extended to spatiotemporal data, changes in data snapshots at fixed instances in time, or any other data which has a temporal component during its evolution.

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Evolution and change in data management — issues and directions

Cited by 26 publications

References 16 publications

Language Extensions for the Automation of Database Schema Evolution

Language Extensions for the Automation of Database Schema Evolution

A survey in indexing and searching XML documents

On change diagnosis in evolving data streams

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