L. Ehrlinger, J. Schrott, and W. Wöß. Database and Expert Systems Applications - DEXA 2023 Workshops, page 3--10. Cham, Springer Nature Switzerland, (2023)
Abstract
Training machine learning models, especially in producing enterprises with numerous information systems having different data structures, requires efficient data access. Hence, standardized descriptions of data sources and their data structures are a fundamental requirement. We therefore introduce version 4.0 of the Data Source Description Vocabulary (DSD), which represents a data source in a standardized form using an ontology. We present several real-world applications where the DSD vocabulary has been applied in recent years to demonstrate its relevance. An evaluation against the FAIR principles highlights the scientific quality and potential for reuse of the DSD vocabulary.
%0 Conference Paper
%1 10.1007/978-3-031-39689-2_1
%A Ehrlinger, Lisa
%A Schrott, Johannes
%A Wöß, Wolfram
%B Database and Expert Systems Applications - DEXA 2023 Workshops
%C Cham
%D 2023
%E Kotsis, Gabriele
%E Tjoa, A. Min
%E Khalil, Ismail
%E Moser, Bernhard
%E Mashkoor, Atif
%E Sametinger, Johannes
%E Khan, Maqbool
%I Springer Nature Switzerland
%K data description dexa paper source vocabulary
%P 3--10
%T DSD: The Data Source Description Vocabulary
%U https://link.springer.com/chapter/10.1007/978-3-031-39689-2_1
%X Training machine learning models, especially in producing enterprises with numerous information systems having different data structures, requires efficient data access. Hence, standardized descriptions of data sources and their data structures are a fundamental requirement. We therefore introduce version 4.0 of the Data Source Description Vocabulary (DSD), which represents a data source in a standardized form using an ontology. We present several real-world applications where the DSD vocabulary has been applied in recent years to demonstrate its relevance. An evaluation against the FAIR principles highlights the scientific quality and potential for reuse of the DSD vocabulary.
%@ 978-3-031-39689-2
@inproceedings{10.1007/978-3-031-39689-2_1,
abstract = {Training machine learning models, especially in producing enterprises with numerous information systems having different data structures, requires efficient data access. Hence, standardized descriptions of data sources and their data structures are a fundamental requirement. We therefore introduce version 4.0 of the Data Source Description Vocabulary (DSD), which represents a data source in a standardized form using an ontology. We present several real-world applications where the DSD vocabulary has been applied in recent years to demonstrate its relevance. An evaluation against the FAIR principles highlights the scientific quality and potential for reuse of the DSD vocabulary.},
added-at = {2023-09-18T15:42:24.000+0200},
address = {Cham},
author = {Ehrlinger, Lisa and Schrott, Johannes and W{\"o}{\ss}, Wolfram},
biburl = {https://www.bibsonomy.org/bibtex/21c012ea31212db76a134ebf53faf6a11/scch},
booktitle = {Database and Expert Systems Applications - DEXA 2023 Workshops},
editor = {Kotsis, Gabriele and Tjoa, A. Min and Khalil, Ismail and Moser, Bernhard and Mashkoor, Atif and Sametinger, Johannes and Khan, Maqbool},
interhash = {0b763b808e08ed88d9dc644b88919e81},
intrahash = {1c012ea31212db76a134ebf53faf6a11},
isbn = {978-3-031-39689-2},
keywords = {data description dexa paper source vocabulary},
pages = {3--10},
publisher = {Springer Nature Switzerland},
timestamp = {2023-09-18T15:42:24.000+0200},
title = {DSD: The Data Source Description Vocabulary},
url = {https://link.springer.com/chapter/10.1007/978-3-031-39689-2_1},
year = 2023
}