Knowledge network of scientific claims derived from a semantic publication system1

The case for an inclusive scholarly communication infrastructure for social sciences and humanities

“…Moreover, large commercial databases tend to underrepresent SSH outputs ( Kulczycki et al , 2018 ); hence, scholars need to resort to web browsing and popular search engines to retrieve interesting content ( Dallas et al , 2017 ), with all the biases that come with search and personalisation algorithms. The variety of resources encompassing “electronic publications, digital libraries, repositories of full-text papers, algorithms, datasets of scientific data, terminological knowledge bases,” thus requires dedicating “greater efforts to discovering, examining, comparing, and integrating these resources” ( Marcondes, 2012 , 73). So, instead of struggling with scholarly content overflow on the web, we need to follow Marcondes suggestion and harness the potential of the digital environment for better content discovery.…”

Scientific Knowledge Engineering: a conceptual delineation and overview of the state of the art

“…It is possible to identify two main strategies used in the proposals to achieve a higher level of generality. One is marked by the group of works (Dinakarpandian et al ., 2006; Groth et al ., 2010; Clare et al ., 2011; Marcondes, 2011; de Waard & schneider, 2012; Kuhn et al ., 2013) which models scientific results as assertions described using triples of the type<antecedent><relationship><consequent> (also described as concept-relationship-concept and subject-predicate-object). The other group (Mancini & Buckingham Shum, 2006; Groza et al ., 2007; Ciccarese et al ., 2008; de Waard et al ., 2009), on the other hand, is more focussed on modelling the argumentation structures used in scientific papers, from the organization of their sections to the arrangement of arguments for and against a specific theme.…”

“…On the other hand, most discussions focus on content knowledge structures (Dinakarpandian et al ., 2006; Boyce et al ., 2007; Pike & Gahegan, 2007; Brodaric et al ., 2008; Groth et al ., 2010; Sharma et al ., 2010; Clare et al ., 2011; Croft et al ., 2011; Kraines & Guo, 2011; Marcondes, 2011; Russ et al ., 2011; Hunter & Williams, 2012; Santos & Travassos, 2013; van Valkenhoef et al ., 2013; Bölling et al, 2014; Ekaputra et al ., 2014). The difference between container and content made in this subsection will be implicitly recurrent in next subsections where their distinctions and similarities regarding technologies, reasoning capabilities and modelling process will be more apparent.…”

“…The wide use of this format is aligned with Hunter and Liu (2010) who state that ‘any domain in Science has ontological knowledge that could be usefully encoded and used in the form of a description logic’ 4 . Among the triple-based formalizations, RDF is the most common technology used for knowledge representation (Groza et al , 2007; Brodaric et al ., 2008; Ciccarese et al ., 2008; de Waard et al ., 2009; Groth et al ., 2010; Sharma et al ., 2010; Clare et al ., 2011; Kraines & Guo, 2011; Marcondes, 2011; de Waard et al ., 2012; Kuhn et al ., 2013; Bölling et al, 2014). The vocabulary developed in these works is quite diversified, including the definition of assertive relationships (e.g.…”

“…The antecedent and consequent parts of triples also vary considerably from simple terms and concepts (e.g. Groth et al ., 2010; Marcondes, 2011) to small sentences and expressions (e.g. calledAtomic, Independent, Declarative and Absolute sentences in Kuhn et al ., 2013).…”