RDF-based Deployment Pipelining for Efficient Dataset Release Management
C. Stadler, L. Wenige, S. Tramp, K. Junghanns, and M. Martin. Proceedings of the Posters and Demos Track of the 14th International Conference on Semantic Systems co-located with the 14th International Conference on Semantic Systems (SEMANTICS'19), Karlsruhe, Germany, (2019)
Abstract
Open Data portals often struggle to provide release features (i.e., stable versioning, up-to-date download links, rich metadata descritions) for their datasets. By this means, wide adoption of publicly available datasets is hindered, since consuming applications cannot access fresh data sources or might break due to data quality issues. While there exists a variety of tools to efficiently control release processes in software development, the management of dataset releases is not as clear. This paper proposes a deployment pipeline for efficient dataset releases that is based on automated enrichment of DCAT/DATAID metadata and is a first step towards efficient deployment pipelining for Open Data publishing.
Proceedings of the Posters and Demos Track of the 14th International Conference on Semantic Systems co-located with the 14th International Conference on Semantic Systems (SEMANTICS'19)
%0 Conference Paper
%1 stadler-n-2019--rdfdeploy
%A Stadler, Claus
%A Wenige, Lisa
%A Tramp, Sebastian
%A Junghanns, Kurt
%A Martin, Michael
%B Proceedings of the Posters and Demos Track of the 14th International Conference on Semantic Systems co-located with the 14th International Conference on Semantic Systems (SEMANTICS'19)
%C Karlsruhe, Germany
%D 2019
%K group_aksw junghanns limboproject martin stadler tramp wenige
%T RDF-based Deployment Pipelining for Efficient Dataset Release Management
%U https://svn.aksw.org/papers/2019/semantics_rdf_pipeline/public.pdf
%X Open Data portals often struggle to provide release features (i.e., stable versioning, up-to-date download links, rich metadata descritions) for their datasets. By this means, wide adoption of publicly available datasets is hindered, since consuming applications cannot access fresh data sources or might break due to data quality issues. While there exists a variety of tools to efficiently control release processes in software development, the management of dataset releases is not as clear. This paper proposes a deployment pipeline for efficient dataset releases that is based on automated enrichment of DCAT/DATAID metadata and is a first step towards efficient deployment pipelining for Open Data publishing.
@inproceedings{stadler-n-2019--rdfdeploy,
abstract = {Open Data portals often struggle to provide release features (i.e., stable versioning, up-to-date download links, rich metadata descritions) for their datasets. By this means, wide adoption of publicly available datasets is hindered, since consuming applications cannot access fresh data sources or might break due to data quality issues. While there exists a variety of tools to efficiently control release processes in software development, the management of dataset releases is not as clear. This paper proposes a deployment pipeline for efficient dataset releases that is based on automated enrichment of DCAT/DATAID metadata and is a first step towards efficient deployment pipelining for Open Data publishing.},
added-at = {2024-06-18T09:46:29.000+0200},
address = {Karlsruhe, Germany},
author = {Stadler, Claus and Wenige, Lisa and Tramp, Sebastian and Junghanns, Kurt and Martin, Michael},
biburl = {https://www.bibsonomy.org/bibtex/229ed048f600680fda6e0cbb070278f9c/aksw},
booktitle = {Proceedings of the Posters and Demos Track of the 14th International Conference on Semantic Systems co-located with the 14th International Conference on Semantic Systems (SEMANTICS'19)},
interhash = {fe402139ec1bec2fa2ef50f84ac89c1c},
intrahash = {29ed048f600680fda6e0cbb070278f9c},
keywords = {group_aksw junghanns limboproject martin stadler tramp wenige},
timestamp = {2024-06-18T09:46:29.000+0200},
title = {RDF-based Deployment Pipelining for Efficient Dataset Release Management},
url = {https://svn.aksw.org/papers/2019/semantics_rdf_pipeline/public.pdf},
year = 2019
}