Semantic Publishing Challenge -- Assessing the Quality of Scientific Output
Abstract
Linked Open Datasets about scholarly publications enable the development and integration of sophisticated end-user services; however, richer datasets are still needed. The first goal of this Challenge was to investigate novel approaches to obtain such semantic data. In particular, we were seeking methods and tools to extract information from scholarly publications, to publish it as LOD, and to use queries over this LOD to assess quality. This year we focused on the quality of workshop proceedings, and of journal articles w.r.t. their citation network. A third, open task, asked to showcase how such semantic data could be exploited and how Semantic Web technologies could help in this emerging context.
Keywords
Cite
@article{arxiv.1408.3863,
title = {Semantic Publishing Challenge -- Assessing the Quality of Scientific Output},
author = {Christoph Lange and Angelo Di Iorio},
journal= {arXiv preprint arXiv:1408.3863},
year = {2014}
}
Comments
To appear in: Valentina Presutti and Milan Stankovic and Erik Cambria and Reforgiato Recupero, Diego and Di Iorio, Angelo and Christoph Lange and Di Noia, Tommaso and Ivan Cantador (eds.). Semantic Web Evaluation Challenges 2014. Number 457 in Communications in Computer and Information Science, Springer, 2014