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Semantic Publishing Challenge: Bootstrapping a Value Chain for Scientific Data

: Vahdati, Sahar; Dimou, Anastasia; Lange, Christoph; Iorio, Angelo di

Volltext urn:nbn:de:0011-n-4813611 (5.0 MByte PDF)
MD5 Fingerprint: 348facda24e4605938b0536cc900da6b
Erstellt am: 5.9.2018

González-Beltrán, A.:
Semantics, analytics, visualization. Enhancing scholarly data : Second International Workshop, SAVE-SD 2016, Montreal, QC, Canada, April 11, 2016 : revised selected papers
Cham: Springer International Publishing, 2016 (Lecture Notes in Computer Science 9792)
ISBN: 978-3-319-53636-1
ISBN: 978-3-319-53637-8
International Workshop Semantics, Analytics, Visualization - Enhancing Scholarly Data (SAVE-SD) <2, 2016, Montreal>
European Commission EC
H2020; 643410; OpenAIRE2020
Open Access Infrastructure for Research in Europe 2020
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IAIS ()
name entity recognition; link open data; evaluation dataset; legacy solution; ontology alignment evaluation initiative

The objective of the Semantic Publishing (SemPub) challenge series is to bootstrap a value chain for scientific data to enable services, such as assessing the quality of scientific output with respect to novel metrics. The key idea was to involve participants in extracting data from heterogeneous resources and producing datasets on scholarly publications, which can be exploited by the community itself. Differently from other challenges in the semantic publishing domain, whose focus is on exploiting semantically enriched data, SemPub focuses on producing Linked Open Datasets. The goal of this paper is to review both (i) the overall organization of the Challenge, and (ii) the results that the participants have produced in the first two challenges of 2014 and 2015 – in terms of data, ontological models and tools – in order to better shape future editions of the challenge, and to better serve the needs of the semantic publishing community.