Simplifying license attribution for OER with emacs-reveal
Author:
Abstract
Open Educational Resources (OER) come with different license terms that require different forms of attribution. Properly attributing OER with licensing information has previously been identified as one of the most time-consuming factors of OER projects. As shown in this paper, the semantic annotation standard CC REL lacks features that are necessary for correct attribution with popular Creative Commons licenses. The software emacs-reveal addresses this gap in the context of OER slideshows, which may contain figures under different licensing terms: For each figure, a simple text file stores metadata building upon the vocabulary of CC REL (with pragmatic extensions) and can be shared along with the figure. From that metadata, the software generates attribution statements, both in machine-readable form (based on RDFa) and in human-readable form. The novel resulting process avoids manual copying of relevant license information, which is time-consuming and error-prone.
- Citation
- BibTeX
Lechtenbörger, J.,
(2019).
Simplifying license attribution for OER with emacs-reveal.
In:
Pinkwart, N. & Konert, J.
(Hrsg.),
DELFI 2019.
Bonn:
Gesellschaft für Informatik e.V..
(S. 205-216).
DOI: 10.18420/delfi2019_280
@inproceedings{mci/Lechtenbörger2019,
author = {Lechtenbörger, Jens},
title = {Simplifying license attribution for OER with emacs-reveal},
booktitle = {DELFI 2019},
year = {2019},
editor = {Pinkwart, Niels AND Konert, Johannes} ,
pages = { 205-216 } ,
doi = { 10.18420/delfi2019_280 },
publisher = {Gesellschaft für Informatik e.V.},
address = {Bonn}
}
author = {Lechtenbörger, Jens},
title = {Simplifying license attribution for OER with emacs-reveal},
booktitle = {DELFI 2019},
year = {2019},
editor = {Pinkwart, Niels AND Konert, Johannes} ,
pages = { 205-216 } ,
doi = { 10.18420/delfi2019_280 },
publisher = {Gesellschaft für Informatik e.V.},
address = {Bonn}
}
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More Info
ISBN: 978-3-88579-691-6
ISSN: 1617-5468
xmlui.MetaDataDisplay.field.date: 2019
Language:
(en)

Content Type: Text/Conference Paper