An online bibliography on schema evolution

Rahm, Erhard; Bernstein, Philip A.

doi:10.1145/1228268.1228273

Cited by 61 publications

(24 citation statements)

References 11 publications

(10 reference statements)

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“…There is a broad array of related work including form-driven database generation [11], DIY web services for form creation [1] schema mapping [20], view integration [7], schema evolution [26], and automatic understanding of Deep Web search interfaces [17]. However, the problem that we address here is a new and has not been addressed before in totality.…”

Section: Related Workmentioning

confidence: 99%

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Automatically Mapping and Integrating Multiple Data Entry Forms into a Database

An¹,

Khare²,

Song³

et al. 2011

Conceptual Modeling – ER 2011

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Abstract. Forms are a standard way of gathering data into a database. Many applications need to support multiple users with evolving data gathering requirements. It is desirable to automatically link dynamic forms to the back-end database. We have developed the FormMapper system, a fully automatic solution that accepts user-created data entry forms, and maps and integrates them into an existing database in the same domain. The solution comprises of two components: tree extraction and form integration. The tree extraction component leverages a probabilistic process, Hidden Markov Model (HMM), for automatically extracting a semantic tree structure of a form. In the form integration component, we develop a merging procedure that maps and integrates a tree into an existing database and extends the database with desired properties. We conducted experiments evaluating the performance of the system on several large databases designed from a number of complex forms. Our experimental results show that the FormMapper system is promising: It generated databases that are highly similar (87% overlapped) to those generated by the human experts, given the same set of forms.

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Section: Related Workmentioning

confidence: 99%

“…Our problem is a continuous and dynamic process which does not ask the user to examine the results. Schema evolution focuses on maintaining the consistency of a database when its schema is modified [26]. Our problem focuses on how to extend a database when new data needs to be collected.…”

Section: Related Workmentioning

confidence: 99%

Automatically Mapping and Integrating Multiple Data Entry Forms into a Database

An¹,

Khare²,

Song³

et al. 2011

Conceptual Modeling – ER 2011

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“…However, strategies that we describe below can reduce the impact. Surveys [Roddick 1995;Ram and Shankaranarayanan 2003], an annotated bibliography [Roddick 1992;, and an online bibliography [Rahm and Bernstein 2006] summarize much of the work on logical redefinition.…”

Section: Strategies For Online Logical Redefinitionmentioning

confidence: 99%

“…Many strategies have been developed for logical redefinition in object-oriented DBMSs. Surveys [Roddick 1995;Ram and Shankaranarayanan 2003], an annotated bibliography [Roddick 1992;, and an online bibliography [Rahm and Bernstein 2006] cover many of the strategies. Other strategies and related discussions (not in the surveys and bibliographies) include those of , Zdonik [1986], Versant Object Technology [1991.89], Morsi et al [1991;, , Bratsberg [1993], Itasca Systems [1993, Odberg [1994], Ferrandina et al [1994], Fontana and Dennebouy [1995], Peters andÖzsu [1995], Malhotra and Munroe [1997], Goralwalla et al [1998], and probably others.…”

Section: Interpretation and Incremental Reorganization During Users' mentioning

confidence: 99%

Online reorganization of databases

Sockut

Iyer

2009

ACM Comput. Surv.

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In practice, any database management system sometimes needs reorganization, that is, a change in some aspect of the logical and/or physical arrangement of a database. In traditional practice, many types of reorganization have required denying access to a database (taking the database offline) during reorganization. Taking a database offline can be unacceptable for a highly available (24-hour) database, for example, a database serving electronic commerce or armed forces, or for a very large database. A solution is to reorganize online (concurrently with usage of the database, incrementally during users' activities, or interpretively). This article is a tutorial and survey on requirements, issues, and strategies for online reorganization. It analyzes the issues and then presents the strategies, which use the issues. The issues, most of which involve design trade-offs, include use of partitions, the locus of control for the process that reorganizes (a background process or users' activities), reorganization by copying to newly allocated storage (as opposed to reorganizing in place), use of differential files, references to data that has moved, performance, and activation of reorganization. The article surveys online strategies in three categories of reorganization. The first category, maintenance, involves restoring the physical arrangement of data instances without changing the database definition. This category includes restoration of clustering, reorganization of an index, rebalancing of parallel or distributed data, garbage collection for persistent storage, and cleaning (reclamation of space) in a logstructured file system. The second category involves changing the physical database definition; topics include construction of indexes, conversion between B + -trees and linear hash files, and redefinition (e.g., splitting) of partitions. The third category involves changing the logical database definition. Some examples are changing a column's data type, changing the inheritance hierarchy of object classes, and changing a relationship from one-to-many to many-to-many. The survey encompasses both research and commercial implementations, and this article points out several open research topics. As highly available or very large databases continue to become more common and more important in the world economy, the importance of online reorganization is likely to continue growing.

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“…Other related work is schema evolution [25]. In object-oriented databases (OODB), the problem of schema evolution is to maintain the consistency of an OODB when its schema is modified.…”

Section: Related Workmentioning

confidence: 99%

Round-Trip Engineering for Maintaining Conceptual-Relational Mappings

Song

2008

Notes on Numerical Fluid Mechanics and Multidisciplinary Design

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Abstract. Conceptual-relational mappings between conceptual models and relational schemas have been used increasingly to achieve interoperability or overcome impedance mismatch in modern data-centric applications. However, both schemas and conceptual models evolve over time to accommodate new information needs. When the conceptual model (CM) or the schema associated with a mapping evolved, the mapping needs to be updated to reflect the new semantics in the CM/schema. In this paper, we propose a round-trip engineering solution which essentially synchronizes models by keeping them consistent for maintaining conceptualrelational mappings. First, we define the consistency of a conceptualrelational mapping through "semantically compatible" instances. Next, we carefully analyze the knowledge encoded in the standard database design process and develop round-trip algorithms for maintaining the consistency of conceptual-relational mappings under evolution. Finally, we conduct a comprehensive set of experiments. The results show that our solution is efficient and provides significant benefits in comparison to the mapping reconstructing approach.

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An online bibliography on schema evolution

Abstract: We briefly motivate and present a new online bibliography on schema evolution, an area which has recently gained much interest in both research and practice.

Cited by 61 publications

References 11 publications

Automatically Mapping and Integrating Multiple Data Entry Forms into a Database

Automatically Mapping and Integrating Multiple Data Entry Forms into a Database

Online reorganization of databases

Round-Trip Engineering for Maintaining Conceptual-Relational Mappings

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