On Metadata Support for Integrating Evolving Heterogeneous Data Sources

Darja Solodovnikova; Laila Niedrite; Aivars Niedritis

doi:10.1007/978-3-030-30278-8_38

On Metadata Support for Integrating Evolving Heterogeneous Data Sources

Darja Solodovnikova^*
, Laila Niedrite
, Aivars Niedritis

^*Corresponding author for this work

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › Research › peer-review

4 Citations (Scopus)

Abstract

With the emergence of big data technologies, the problem of structure evolution of integrated heterogeneous data sources has become extremely topical due to dynamic and diverse nature of big data. To solve the big data evolution problem, we propose an architecture that allows to store and process structured and unstructured data at different levels of detail, analyze them using OLAP capabilities and semi-automatically manage changes in requirements and data expansion. In this paper, we concentrate on the metadata essential for the operation of the proposed architecture. We propose a metadata model to describe schemata and supplementary properties of data sets extracted from sources and transformed to obtain integrated data for the analysis in a flexible way. Furthermore, the unique feature of the proposed model is that it allows to keep track of all changes that occur in the system.

Original language	English
Title of host publication	New Trends in Databases and Information Systems - ADBIS 2019 Short Papers, Workshops BBIGAP, QAUCA, SemBDM, SIMPDA, M2P, MADEISD, and Doctoral Consortium 2019, Proceedings
Editors	Tatjana Welzer, Vili Podgorelec, Aida Kamišalic Latific, Johann Eder, Robert Wrembel, Mikolaj Morzy, Mirjana Ivanovic, Johann Gamper, Theodoros Tzouramanis, Jérôme Darmont
Publisher	Springer Verlag
Pages	378-390
Number of pages	13
ISBN (Print)	9783030302771
DOIs	https://doi.org/10.1007/978-3-030-30278-8_38
Publication status	Published - 2019
Event	Workshops and doctoral consortium papers of the 23rd European Conference on Advances in Databases and Information Systems, ADBIS 2019 - Bled, Slovenia Duration: 8 Sept 2019 → 11 Sept 2019

Publication series

Name	Communications in Computer and Information Science
Volume	1064
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	Workshops and doctoral consortium papers of the 23rd European Conference on Advances in Databases and Information Systems, ADBIS 2019
Country/Territory	Slovenia
City	Bled
Period	8/09/19 → 11/09/19

Keywords

Big data
Data warehouse
Evolution
Metadata

Access to Document

10.1007/978-3-030-30278-8_38

Cite this

Solodovnikova, D., Niedrite, L., & Niedritis, A. (2019). On Metadata Support for Integrating Evolving Heterogeneous Data Sources. In T. Welzer, V. Podgorelec, A. Kamišalic Latific, J. Eder, R. Wrembel, M. Morzy, M. Ivanovic, J. Gamper, T. Tzouramanis, & J. Darmont (Eds.), New Trends in Databases and Information Systems - ADBIS 2019 Short Papers, Workshops BBIGAP, QAUCA, SemBDM, SIMPDA, M2P, MADEISD, and Doctoral Consortium 2019, Proceedings (pp. 378-390). (Communications in Computer and Information Science; Vol. 1064). Springer Verlag. https://doi.org/10.1007/978-3-030-30278-8_38

Solodovnikova, Darja ; Niedrite, Laila ; Niedritis, Aivars. / On Metadata Support for Integrating Evolving Heterogeneous Data Sources. New Trends in Databases and Information Systems - ADBIS 2019 Short Papers, Workshops BBIGAP, QAUCA, SemBDM, SIMPDA, M2P, MADEISD, and Doctoral Consortium 2019, Proceedings. editor / Tatjana Welzer ; Vili Podgorelec ; Aida Kamišalic Latific ; Johann Eder ; Robert Wrembel ; Mikolaj Morzy ; Mirjana Ivanovic ; Johann Gamper ; Theodoros Tzouramanis ; Jérôme Darmont. Springer Verlag, 2019. pp. 378-390 (Communications in Computer and Information Science).

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title = "On Metadata Support for Integrating Evolving Heterogeneous Data Sources",

abstract = "With the emergence of big data technologies, the problem of structure evolution of integrated heterogeneous data sources has become extremely topical due to dynamic and diverse nature of big data. To solve the big data evolution problem, we propose an architecture that allows to store and process structured and unstructured data at different levels of detail, analyze them using OLAP capabilities and semi-automatically manage changes in requirements and data expansion. In this paper, we concentrate on the metadata essential for the operation of the proposed architecture. We propose a metadata model to describe schemata and supplementary properties of data sets extracted from sources and transformed to obtain integrated data for the analysis in a flexible way. Furthermore, the unique feature of the proposed model is that it allows to keep track of all changes that occur in the system.",

keywords = "Big data, Data warehouse, Evolution, Metadata",

author = "Darja Solodovnikova and Laila Niedrite and Aivars Niedritis",

note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2019.; Workshops and doctoral consortium papers of the 23rd European Conference on Advances in Databases and Information Systems, ADBIS 2019 ; Conference date: 08-09-2019 Through 11-09-2019",

year = "2019",

doi = "10.1007/978-3-030-30278-8\_38",

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booktitle = "New Trends in Databases and Information Systems - ADBIS 2019 Short Papers, Workshops BBIGAP, QAUCA, SemBDM, SIMPDA, M2P, MADEISD, and Doctoral Consortium 2019, Proceedings",

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Solodovnikova, D , Niedrite, L & Niedritis, A 2019, On Metadata Support for Integrating Evolving Heterogeneous Data Sources. in T Welzer, V Podgorelec, A Kamišalic Latific, J Eder, R Wrembel, M Morzy, M Ivanovic, J Gamper, T Tzouramanis & J Darmont (eds), New Trends in Databases and Information Systems - ADBIS 2019 Short Papers, Workshops BBIGAP, QAUCA, SemBDM, SIMPDA, M2P, MADEISD, and Doctoral Consortium 2019, Proceedings. Communications in Computer and Information Science, vol. 1064, Springer Verlag, pp. 378-390, Workshops and doctoral consortium papers of the 23rd European Conference on Advances in Databases and Information Systems, ADBIS 2019, Bled, Slovenia, 8/09/19. https://doi.org/10.1007/978-3-030-30278-8_38

On Metadata Support for Integrating Evolving Heterogeneous Data Sources. / Solodovnikova, Darja ; Niedrite, Laila ; Niedritis, Aivars.
New Trends in Databases and Information Systems - ADBIS 2019 Short Papers, Workshops BBIGAP, QAUCA, SemBDM, SIMPDA, M2P, MADEISD, and Doctoral Consortium 2019, Proceedings. ed. / Tatjana Welzer; Vili Podgorelec; Aida Kamišalic Latific; Johann Eder; Robert Wrembel; Mikolaj Morzy; Mirjana Ivanovic; Johann Gamper; Theodoros Tzouramanis; Jérôme Darmont. Springer Verlag, 2019. p. 378-390 (Communications in Computer and Information Science; Vol. 1064).

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › Research › peer-review

TY - GEN

T1 - On Metadata Support for Integrating Evolving Heterogeneous Data Sources

AU - Solodovnikova, Darja

AU - Niedrite, Laila

AU - Niedritis, Aivars

N1 - Publisher Copyright: © Springer Nature Switzerland AG 2019.

PY - 2019

Y1 - 2019

N2 - With the emergence of big data technologies, the problem of structure evolution of integrated heterogeneous data sources has become extremely topical due to dynamic and diverse nature of big data. To solve the big data evolution problem, we propose an architecture that allows to store and process structured and unstructured data at different levels of detail, analyze them using OLAP capabilities and semi-automatically manage changes in requirements and data expansion. In this paper, we concentrate on the metadata essential for the operation of the proposed architecture. We propose a metadata model to describe schemata and supplementary properties of data sets extracted from sources and transformed to obtain integrated data for the analysis in a flexible way. Furthermore, the unique feature of the proposed model is that it allows to keep track of all changes that occur in the system.

AB - With the emergence of big data technologies, the problem of structure evolution of integrated heterogeneous data sources has become extremely topical due to dynamic and diverse nature of big data. To solve the big data evolution problem, we propose an architecture that allows to store and process structured and unstructured data at different levels of detail, analyze them using OLAP capabilities and semi-automatically manage changes in requirements and data expansion. In this paper, we concentrate on the metadata essential for the operation of the proposed architecture. We propose a metadata model to describe schemata and supplementary properties of data sets extracted from sources and transformed to obtain integrated data for the analysis in a flexible way. Furthermore, the unique feature of the proposed model is that it allows to keep track of all changes that occur in the system.

KW - Big data

KW - Data warehouse

KW - Evolution

KW - Metadata

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DO - 10.1007/978-3-030-30278-8_38

M3 - Conference paper

AN - SCOPUS:85072976299

SN - 9783030302771

T3 - Communications in Computer and Information Science

SP - 378

EP - 390

BT - New Trends in Databases and Information Systems - ADBIS 2019 Short Papers, Workshops BBIGAP, QAUCA, SemBDM, SIMPDA, M2P, MADEISD, and Doctoral Consortium 2019, Proceedings

A2 - Welzer, Tatjana

A2 - Podgorelec, Vili

A2 - Kamišalic Latific, Aida

A2 - Eder, Johann

A2 - Wrembel, Robert

A2 - Morzy, Mikolaj

A2 - Ivanovic, Mirjana

A2 - Gamper, Johann

A2 - Tzouramanis, Theodoros

A2 - Darmont, Jérôme

PB - Springer Verlag

T2 - Workshops and doctoral consortium papers of the 23rd European Conference on Advances in Databases and Information Systems, ADBIS 2019

Y2 - 8 September 2019 through 11 September 2019

ER -

Solodovnikova D , Niedrite L , Niedritis A. On Metadata Support for Integrating Evolving Heterogeneous Data Sources. In Welzer T, Podgorelec V, Kamišalic Latific A, Eder J, Wrembel R, Morzy M, Ivanovic M, Gamper J, Tzouramanis T, Darmont J, editors, New Trends in Databases and Information Systems - ADBIS 2019 Short Papers, Workshops BBIGAP, QAUCA, SemBDM, SIMPDA, M2P, MADEISD, and Doctoral Consortium 2019, Proceedings. Springer Verlag. 2019. p. 378-390. (Communications in Computer and Information Science). doi: 10.1007/978-3-030-30278-8_38

On Metadata Support for Integrating Evolving Heterogeneous Data Sources

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Keywords

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