In this work, we tackle the problem of generating comprehensive overviews of research findings in a structured and comparable way. To bring structure to such information and thus to enable researchers to, e.g., explore domain overviews, we present an approach for automatic unveiling of realm overviews for research artifacts (Aurora), an approach to generate overviews of research domains and their relevant artifacts. Aurora is a semi-automatic crowd-sourcing workflow that captures such information into the OpenResearch.org semantic wiki. Our evaluation confirms that Aurora, when compared to the current manual approach, reduces the effort for researchers to compile and read survey papers.
CITATION STYLE
Vahdati, S., Fathalla, S., Auer, S., Lange, C., & Vidal, M. E. (2019). Semantic Representation of Scientific Publications. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11799 LNCS, pp. 375–379). Springer Verlag. https://doi.org/10.1007/978-3-030-30760-8_37
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