Towards a Semantic Toolbox for Reproducible Knowledge Graph Generation in the Biodiversity Domain - How to Make the Most out of Biodiversity Data
Zusammenfassung
Knowledge Graphs are widely regarded as one of the most promising ways to manage and link information in the age of Big Data. Their broad uptake is still hindered by the large effort required to create and maintain them, though. In this paper, we propose the creation of a semantic toolbox that will support data owners in transforming their databases into reproducible, dynamically extendable knowledge graphs that can be integrated and jointly used. We showcase the need, potential benefits and first steps towards the solution in our example domain, biodiversity research.
- Vollständige Referenz
- BibTeX
Babalou, S., Schellenberger Costa, D., Kattge, J., Römermann, C. & König-Ries, B.,
(2021).
Towards a Semantic Toolbox for Reproducible Knowledge Graph Generation in the Biodiversity Domain - How to Make the Most out of Biodiversity Data.
In:
, .
(Hrsg.),
INFORMATIK 2021.
Gesellschaft für Informatik, Bonn.
(S. 581-590).
DOI: 10.18420/informatik2021-044
@inproceedings{mci/Babalou2021,
author = {Babalou, Samira AND Schellenberger Costa, David AND Kattge, Jens AND Römermann, Christine AND König-Ries, Birgitta},
title = {Towards a Semantic Toolbox for Reproducible Knowledge Graph Generation in the Biodiversity Domain - How to Make the Most out of Biodiversity Data},
booktitle = {INFORMATIK 2021},
year = {2021},
editor = {} ,
pages = { 581-590 } ,
doi = { 10.18420/informatik2021-044 },
publisher = {Gesellschaft für Informatik, Bonn},
address = {}
}
author = {Babalou, Samira AND Schellenberger Costa, David AND Kattge, Jens AND Römermann, Christine AND König-Ries, Birgitta},
title = {Towards a Semantic Toolbox for Reproducible Knowledge Graph Generation in the Biodiversity Domain - How to Make the Most out of Biodiversity Data},
booktitle = {INFORMATIK 2021},
year = {2021},
editor = {} ,
pages = { 581-590 } ,
doi = { 10.18420/informatik2021-044 },
publisher = {Gesellschaft für Informatik, Bonn},
address = {}
}
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Mehr Information
ISBN: 978-3-88579-708-1
ISSN: 1617-5468
Datum: 2021
Sprache:
(en)
(en)
