There is currently a gap between the natural language expression of scholarly publications and their structured semantic content modeling to enable intelligent content search. With the volume of research growing exponentially every year, a search feature operating over semantically structured content is compelling. Toward this end, in this work, we propose a novel semantic data model for modeling the contribution of scientific investigations. Our model, i.e. the Research Contribution Model (RCM), includes a schema of pertinent concepts highlighting six core information units, viz. Objective, Method, Activity, Agent, Material, and Result, on which the contribution hinges. It comprises bottom-up design considerations made from three scientifi...
Knowledge graphs facilitate the discovery of information by organizing it into entities and describi...
Fully structured semantic resources representing facts in the form of triples (i.e., knowledge graph...
The document-centric workflows in science have reached (or already exceeded) the limits of adequacy....
The continuous growth of scientific literature brings innovations and, at the same time, raises new ...
Scientific knowledge graphs have been proposed as a solution to structure the content of research pu...
The transfer of knowledge has not changed fundamentally for many hundreds of years: It is usually do...
Several scholarly knowledge graphs have been proposed to model and analyze the academic landscape. H...
The document-oriented workflows in science have reached (or already exceeded) the limits of adequacy...
Knowledge graphs represent the meaning of properties of real-world entities and relationships among ...
The continuously increasing output of published research makes the work of researchers harder as it ...
The transfer of knowledge has not changed fundamentally for many hundreds of years: It is usually do...
In this paper, we present a preliminary approach that uses a set of NLP and Deep Learning methods fo...
The past decades have witnessed a huge growth in scholarly information published on the Web, mostly ...
Knowledge graphs (KG) are large network of entities and relationships, tipically expressed as RDF tr...
Knowledge graphs (KG) are large networks of entities and relationships, typically expressed as RDF t...
Knowledge graphs facilitate the discovery of information by organizing it into entities and describi...
Fully structured semantic resources representing facts in the form of triples (i.e., knowledge graph...
The document-centric workflows in science have reached (or already exceeded) the limits of adequacy....
The continuous growth of scientific literature brings innovations and, at the same time, raises new ...
Scientific knowledge graphs have been proposed as a solution to structure the content of research pu...
The transfer of knowledge has not changed fundamentally for many hundreds of years: It is usually do...
Several scholarly knowledge graphs have been proposed to model and analyze the academic landscape. H...
The document-oriented workflows in science have reached (or already exceeded) the limits of adequacy...
Knowledge graphs represent the meaning of properties of real-world entities and relationships among ...
The continuously increasing output of published research makes the work of researchers harder as it ...
The transfer of knowledge has not changed fundamentally for many hundreds of years: It is usually do...
In this paper, we present a preliminary approach that uses a set of NLP and Deep Learning methods fo...
The past decades have witnessed a huge growth in scholarly information published on the Web, mostly ...
Knowledge graphs (KG) are large network of entities and relationships, tipically expressed as RDF tr...
Knowledge graphs (KG) are large networks of entities and relationships, typically expressed as RDF t...
Knowledge graphs facilitate the discovery of information by organizing it into entities and describi...
Fully structured semantic resources representing facts in the form of triples (i.e., knowledge graph...
The document-centric workflows in science have reached (or already exceeded) the limits of adequacy....