Data Catalogs: A Systematic Literature Review and Guidelines to Implementation

Lisa Ehrlinger; Johannes Schrott; Martin Melichar; Nicolas Kirchmayr; Wolfram Wöß

doi:10.1007/978-3-030-87101-7_15

Data Catalogs: A Systematic Literature Review and Guidelines to Implementation

Lisa Ehrlinger
, Johannes Schrott
, Martin Melichar
, Nicolas Kirchmayr
, Wolfram Wöß

Institute for Application-oriented Knowledge Processing

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

Abstract

In enterprises, data is usually distributed across multiple data sources and stored in heterogeneous formats. The harmonization and integration of data is a prerequisite to leverage it for AI initiatives. Recently, data catalogs pose a promising solution to semantically classify and organize data sources across different environments and to enrich raw data with metadata. Data catalogs therefore allow to create a single, clear, and easy-accessible interface for training and testing computational models. Despite a lively discussion among practitioners, there is little research on data catalogs. In this paper, we systematically review existing literature and answer the following questions: (1) What are the conceptual components of a data catalog? and (2) Which guidelines can be recommended to implement a data catalog? The results benefit practitioners in implementing a data catalog to accelerate any AI initiative and researchers with a compilation of future research directions.

Original language	English
Title of host publication	Database and Expert Systems Applications - DEXA 2021 Workshops
Editors	Gabriele Kotsis, A Min Tjoa, Ismail Khalil, Bernhard Moser, Atif Mashkoor, Johannes Sametinger, Anna Fensel, Jorge Martinez-Gil, Lukas Fischer, Gerald Czech, Florian Sobieczky, Sohail Khan
Place of Publication	Cham
Publisher	Springer International Publishing
Pages	148-158
Number of pages	11
Volume	1479
ISBN (Electronic)	978-3-030-87101-7
ISBN (Print)	9783030871000
DOIs	https://doi.org/10.1007/978-3-030-87101-7_15
Publication status	Published - Sept 2021

Publication series

Name	Communications in Computer and Information Science
Volume	1479 CCIS
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Fields of science

102001 Artificial intelligence
102010 Database systems
102014 Information design
102015 Information systems
102019 Machine learning
102025 Distributed systems
102028 Knowledge engineering
102033 Data mining
102035 Data science
502007 E-commerce
506002 E-government
509018 Knowledge management

JKU Focus areas

Digital Transformation

Access to Document

10.1007/978-3-030-87101-7_15

Cite this

Ehrlinger, L., Schrott, J., Melichar, M., Kirchmayr, N., & Wöß, W. (2021). Data Catalogs: A Systematic Literature Review and Guidelines to Implementation. In G. Kotsis, A. M. Tjoa, I. Khalil, B. Moser, A. Mashkoor, J. Sametinger, A. Fensel, J. Martinez-Gil, L. Fischer, G. Czech, F. Sobieczky, & S. Khan (Eds.), Database and Expert Systems Applications - DEXA 2021 Workshops (Vol. 1479, pp. 148-158). (Communications in Computer and Information Science; Vol. 1479 CCIS). Springer International Publishing. https://doi.org/10.1007/978-3-030-87101-7_15

Ehrlinger, Lisa ; Schrott, Johannes ; Melichar, Martin et al. / Data Catalogs: A Systematic Literature Review and Guidelines to Implementation. Database and Expert Systems Applications - DEXA 2021 Workshops. editor / Gabriele Kotsis ; A Min Tjoa ; Ismail Khalil ; Bernhard Moser ; Atif Mashkoor ; Johannes Sametinger ; Anna Fensel ; Jorge Martinez-Gil ; Lukas Fischer ; Gerald Czech ; Florian Sobieczky ; Sohail Khan. Vol. 1479 Cham : Springer International Publishing, 2021. pp. 148-158 (Communications in Computer and Information Science).

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abstract = "In enterprises, data is usually distributed across multiple data sources and stored in heterogeneous formats. The harmonization and integration of data is a prerequisite to leverage it for AI initiatives. Recently, data catalogs pose a promising solution to semantically classify and organize data sources across different environments and to enrich raw data with metadata. Data catalogs therefore allow to create a single, clear, and easy-accessible interface for training and testing computational models. Despite a lively discussion among practitioners, there is little research on data catalogs. In this paper, we systematically review existing literature and answer the following questions: (1) What are the conceptual components of a data catalog? and (2) Which guidelines can be recommended to implement a data catalog? The results benefit practitioners in implementing a data catalog to accelerate any AI initiative and researchers with a compilation of future research directions.",

author = "Lisa Ehrlinger and Johannes Schrott and Martin Melichar and Nicolas Kirchmayr and Wolfram W{\"o}{\ss}",

year = "2021",

month = sep,

doi = "10.1007/978-3-030-87101-7\_15",

language = "English",

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editor = "Gabriele Kotsis and Tjoa, \{A Min\} and Ismail Khalil and Bernhard Moser and Atif Mashkoor and Johannes Sametinger and Anna Fensel and Jorge Martinez-Gil and Lukas Fischer and Gerald Czech and Florian Sobieczky and Sohail Khan",

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Ehrlinger, L, Schrott, J, Melichar, M, Kirchmayr, N & Wöß, W 2021, Data Catalogs: A Systematic Literature Review and Guidelines to Implementation. in G Kotsis, AM Tjoa, I Khalil, B Moser, A Mashkoor, J Sametinger, A Fensel, J Martinez-Gil, L Fischer, G Czech, F Sobieczky & S Khan (eds), Database and Expert Systems Applications - DEXA 2021 Workshops. vol. 1479, Communications in Computer and Information Science, vol. 1479 CCIS, Springer International Publishing, Cham, pp. 148-158. https://doi.org/10.1007/978-3-030-87101-7_15

Data Catalogs: A Systematic Literature Review and Guidelines to Implementation. / Ehrlinger, Lisa; Schrott, Johannes; Melichar, Martin et al.
Database and Expert Systems Applications - DEXA 2021 Workshops. ed. / Gabriele Kotsis; A Min Tjoa; Ismail Khalil; Bernhard Moser; Atif Mashkoor; Johannes Sametinger; Anna Fensel; Jorge Martinez-Gil; Lukas Fischer; Gerald Czech; Florian Sobieczky; Sohail Khan. Vol. 1479 Cham: Springer International Publishing, 2021. p. 148-158 (Communications in Computer and Information Science; Vol. 1479 CCIS).

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

TY - GEN

T1 - Data Catalogs: A Systematic Literature Review and Guidelines to Implementation

AU - Ehrlinger, Lisa

AU - Schrott, Johannes

AU - Melichar, Martin

AU - Kirchmayr, Nicolas

AU - Wöß, Wolfram

PY - 2021/9

Y1 - 2021/9

N2 - In enterprises, data is usually distributed across multiple data sources and stored in heterogeneous formats. The harmonization and integration of data is a prerequisite to leverage it for AI initiatives. Recently, data catalogs pose a promising solution to semantically classify and organize data sources across different environments and to enrich raw data with metadata. Data catalogs therefore allow to create a single, clear, and easy-accessible interface for training and testing computational models. Despite a lively discussion among practitioners, there is little research on data catalogs. In this paper, we systematically review existing literature and answer the following questions: (1) What are the conceptual components of a data catalog? and (2) Which guidelines can be recommended to implement a data catalog? The results benefit practitioners in implementing a data catalog to accelerate any AI initiative and researchers with a compilation of future research directions.

AB - In enterprises, data is usually distributed across multiple data sources and stored in heterogeneous formats. The harmonization and integration of data is a prerequisite to leverage it for AI initiatives. Recently, data catalogs pose a promising solution to semantically classify and organize data sources across different environments and to enrich raw data with metadata. Data catalogs therefore allow to create a single, clear, and easy-accessible interface for training and testing computational models. Despite a lively discussion among practitioners, there is little research on data catalogs. In this paper, we systematically review existing literature and answer the following questions: (1) What are the conceptual components of a data catalog? and (2) Which guidelines can be recommended to implement a data catalog? The results benefit practitioners in implementing a data catalog to accelerate any AI initiative and researchers with a compilation of future research directions.

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EP - 158

BT - Database and Expert Systems Applications - DEXA 2021 Workshops

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A2 - Tjoa, A Min

A2 - Khalil, Ismail

A2 - Moser, Bernhard

A2 - Mashkoor, Atif

A2 - Sametinger, Johannes

A2 - Fensel, Anna

A2 - Martinez-Gil, Jorge

A2 - Fischer, Lukas

A2 - Czech, Gerald

A2 - Sobieczky, Florian

A2 - Khan, Sohail

PB - Springer International Publishing

CY - Cham

ER -

Ehrlinger L, Schrott J, Melichar M, Kirchmayr N, Wöß W. Data Catalogs: A Systematic Literature Review and Guidelines to Implementation. In Kotsis G, Tjoa AM, Khalil I, Moser B, Mashkoor A, Sametinger J, Fensel A, Martinez-Gil J, Fischer L, Czech G, Sobieczky F, Khan S, editors, Database and Expert Systems Applications - DEXA 2021 Workshops. Vol. 1479. Cham: Springer International Publishing. 2021. p. 148-158. (Communications in Computer and Information Science). doi: 10.1007/978-3-030-87101-7_15

Data Catalogs: A Systematic Literature Review and Guidelines to Implementation

Abstract

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Fields of science

JKU Focus areas

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SEBISTA

Cite this

Data Catalogs: A Systematic Literature Review and Guidelines to Implementation

Abstract

Publication series

Fields of science

JKU Focus areas

Access to Document

Other files and links

Projects

SEBISTA

Cite this