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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
Available online: IRI: https://w3id.org/dsd; DOI: https://doi.org/10.5281/zenodo.7773861.
- 2.
- 3.
- 4.
- 5.
- 6.
- 7.
- 8.
- 9.
- 10.
See the “connectors” Java package in https://github.com/lisehr/dq-meerkat.
- 11.
- 12.
The FAIR principles and the corresponding descriptions in the leftmost column of Table 1 are directly taken from the GO-FAIR website (https://www.go-fair.org/fair-principles/).
- 13.
References
Atzeni, P., Gianforme, G., Cappellari, P.: A universal metamodel and its dictionary. In: Hameurlain, A., Küng, J., Wagner, R. (eds.) Transactions on Large-Scale Data- and Knowledge-Centered Systems I. LNCS, vol. 5740, pp. 38–62. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-03722-1_2
Candel, C.J.F., Sevilla Ruiz, D., García-Molina, J.J.: A Unified Metamodel for NoSQL and Relational Databases. Information Syst. 104, 101898 (2022). https://doi.org/10.1016/j.is.2021.101898
Ehrlinger, L., Gindlhumer, A., Huber, L., Wöß, W.: DQ-MeeRKat: automating Data Quality Monitoring with a Reference-Data-Profile-Annotated Knowledge Graph. In: Proceedings of the 10th International Conference on Data Science, Technology and Applications - DATA, pp. 215–222. SciTePress (2021)
Ehrlinger, L., Werth, B., Wöß, W.: Automated continuous data quality measurement with QuaIIe. Int. J. Adv. Softw. 11(3 & 4), 400–417 (2018)
Ehrlinger, L., Wöß, W.: Semi-automatically generated hybrid ontologies for information integration. In: Joint Proceedings of the Posters and Demos Track of 11th International Conference on Semantic Systems - SEMANTiCS2015 and 1st Workshop on Data Science: Methods, Technology and Applications (DSci15), vol. 1481, pp. 100–104. CEUR Workshop Proceedings (2015). https://ceur-ws.org/Vol-1481/paper30.pdf
Ehrlinger, L., Wöß, W.: Automated schema quality measurement in large-scale information systems. In: Hacid, H., Sheng, Q.Z., Yoshida, T., Sarkheyli, A., Zhou, R. (eds.) QUAT 2018. LNCS, vol. 11235, pp. 16–31. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-19143-6_2
Garijo, D., Corcho, O., Poveda-Villalón, M.: FOOPS!: an ontology pitfall scanner for the FAIR principles. In: International Semantic Web Conference (ISWC) 2021. CEUR Workshop Proceedings, vol. 2980 (2021). http://ceur-ws.org/Vol-2980/paper321.pdf
Gebru, T.: Datasheets for datasets. Commun. ACM 64(12), 86–92 (2021). https://doi.org/10.1145/3458723
Klarlund, N., Møller, A., Schwartzbach, M.I.: The DSD schema language. Autom. Softw. Eng. 9, 285–319 (2002). https://doi.org/10.1023/A:1016376608070
Rashid, S.M., et al.: The semantic data dictionary - an approach for describing and annotating data. Data Intell. 2(4), 443–486 (2020). https://doi.org/10.1162/dint_a_00058
Schrott, J., Weidinger, S., Tiefengrabner, M., Lettner, C., Wöß, W., Ehrlinger, L.: GOLDCASE: a generic ontology layer for data catalog semantics. In: Garoufallou, E., Vlachidis, A. (eds.) MTSR 2022. CCIS, vol. 1789, pp. 26–38. Springer, Cham (2023). https://doi.org/10.1007/978-3-031-39141-5_3
Wilkinson, M.D., et al.: The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data 3(1), 160018 (2016). https://doi.org/10.1038/sdata.2016.18
World Wide Web Consortium: All Standards and Drafts - W3C. https://www.w3.org/TR/. Accessed 21 Feb 2023
Acknowledgements
This research has been partially funded by BMK, BMAW, and the State of Upper Austria in the frame of the SCCH competence center INTEGRATE (FFG grant no. 892418) part of the FFG COMET Competence Centers for Excellent Technologies Programme and by the “ICT of the Future” project QuanTD (no. 898626).
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Ehrlinger, L., Schrott, J., Wöß, W. (2023). DSD: The Data Source Description Vocabulary. In: Kotsis, G., et al. Database and Expert Systems Applications - DEXA 2023 Workshops. DEXA 2023. Communications in Computer and Information Science, vol 1872. Springer, Cham. https://doi.org/10.1007/978-3-031-39689-2_1
Download citation
DOI: https://doi.org/10.1007/978-3-031-39689-2_1
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-39688-5
Online ISBN: 978-3-031-39689-2
eBook Packages: Computer ScienceComputer Science (R0)