Efficiently Labeling and Retrieving Temporal Anomalies in Relational Databases.
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| Title: | Efficiently Labeling and Retrieving Temporal Anomalies in Relational Databases. |
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| Authors: | Khnaisser, Christina1 (AUTHOR) Christina.Khnaisser@usherbrooke.ca, Hamrouni, Hind2 (AUTHOR) hindhamrouni@gmail.com, Blumenthal, David B.3 (AUTHOR) david.b.blumenthal@fau.de, Dignös, Anton2 (AUTHOR) anton.dignoes@unibz.it, Gamper, Johann2 (AUTHOR) johann.gamper@unibz.it |
| Source: | Information Systems Frontiers. Apr2026, Vol. 28 Issue 2, p561-585. 25p. |
| Subjects: | Relational databases, Data quality, Constraint satisfaction, Outlier detection, Data extraction, Medical databases |
| Abstract: | Time and temporal constraints are implicit in most databases. To facilitate data analysis and quality assessment, a database should provide explicit operations to identify the violation of temporal constraints. Against this background, the purpose of this paper is threefold: (1) we identify and provide a formal definition of five common anomalies in temporal databases, (2) we propose two new relational operations that allow, respectively, to label anomalous tuples in and to retrieve the anomalous tuples from a dataset, and (3) we provide three different SQL implementations of these operations for current relational database management systems. The healthcare domain is used to illustrate the usage and utility of the temporal anomalies. Finally, an experimental evaluation on real-world and synthetic data analyses the performance of the different implementations of the anomaly operators. [ABSTRACT FROM AUTHOR] |
| Copyright of Information Systems Frontiers is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 194005060 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Efficiently Labeling and Retrieving Temporal Anomalies in Relational Databases. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Khnaisser%2C+Christina%22">Khnaisser, Christina</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> Christina.Khnaisser@usherbrooke.ca</i><br /><searchLink fieldCode="AR" term="%22Hamrouni%2C+Hind%22">Hamrouni, Hind</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> hindhamrouni@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Blumenthal%2C+David+B%2E%22">Blumenthal, David B.</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> david.b.blumenthal@fau.de</i><br /><searchLink fieldCode="AR" term="%22Dignös%2C+Anton%22">Dignös, Anton</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> anton.dignoes@unibz.it</i><br /><searchLink fieldCode="AR" term="%22Gamper%2C+Johann%22">Gamper, Johann</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> johann.gamper@unibz.it</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Information+Systems+Frontiers%22">Information Systems Frontiers</searchLink>. Apr2026, Vol. 28 Issue 2, p561-585. 25p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Relational+databases%22">Relational databases</searchLink><br /><searchLink fieldCode="DE" term="%22Data+quality%22">Data quality</searchLink><br /><searchLink fieldCode="DE" term="%22Constraint+satisfaction%22">Constraint satisfaction</searchLink><br /><searchLink fieldCode="DE" term="%22Outlier+detection%22">Outlier detection</searchLink><br /><searchLink fieldCode="DE" term="%22Data+extraction%22">Data extraction</searchLink><br /><searchLink fieldCode="DE" term="%22Medical+databases%22">Medical databases</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Time and temporal constraints are implicit in most databases. To facilitate data analysis and quality assessment, a database should provide explicit operations to identify the violation of temporal constraints. Against this background, the purpose of this paper is threefold: (1) we identify and provide a formal definition of five common anomalies in temporal databases, (2) we propose two new relational operations that allow, respectively, to label anomalous tuples in and to retrieve the anomalous tuples from a dataset, and (3) we provide three different SQL implementations of these operations for current relational database management systems. The healthcare domain is used to illustrate the usage and utility of the temporal anomalies. Finally, an experimental evaluation on real-world and synthetic data analyses the performance of the different implementations of the anomaly operators. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Information Systems Frontiers is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s10796-024-10495-w Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 25 StartPage: 561 Subjects: – SubjectFull: Relational databases Type: general – SubjectFull: Data quality Type: general – SubjectFull: Constraint satisfaction Type: general – SubjectFull: Outlier detection Type: general – SubjectFull: Data extraction Type: general – SubjectFull: Medical databases Type: general Titles: – TitleFull: Efficiently Labeling and Retrieving Temporal Anomalies in Relational Databases. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Khnaisser, Christina – PersonEntity: Name: NameFull: Hamrouni, Hind – PersonEntity: Name: NameFull: Blumenthal, David B. – PersonEntity: Name: NameFull: Dignös, Anton – PersonEntity: Name: NameFull: Gamper, Johann IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 04 Text: Apr2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 13873326 Numbering: – Type: volume Value: 28 – Type: issue Value: 2 Titles: – TitleFull: Information Systems Frontiers Type: main |
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