The project SCAR is a collaboration between the DASPLab and Elsevier.
The goal of the Project is to build a prototype that enriches bibliographies by adding explicit metadata about individual bibliographic entries and characterizes them according to multiple criteria. The prototype will be based on the Semantic Publishing technologies, models and tools that are the current focus of the activities and scientific research of the DASPLab.
There are multiple aspects of bibliographic references that scholars consider when accessing bibliographies. The choice of these traits, as well as the way bibliographic entries are scanned and filtered, depends on the chore the scholar is handling. While reviewing a paper, for instance, a scholar might be interested in rapidly checking if references are up-to-date or if there is any reference to papers published in the same venue; when evaluating research, on the other hand, it might be critical to rapidly identify self-citations or to easily examine information about the authors of each cited paper (e.g., their affiliation). Particularly interesting and challenging is also the possibility of knowing the reason why a paper was cited or even just to provide the context of the citation, i.e., the sentence or the paragraph or a few lines around the text containing the citation.
The basic idea of this project is to enrich bibliographies by making rich information available for each bibliographic reference so as to increase users’ engagement. Each reference is treated as an individual, first-class entity, which can be accessed, filtered and grouped with other references according to a number of different criteria.
The name of the Project – Semantic Coloring of Academic References – reflects the fact that a bibliography should not considered as a plain list, but as a list of explicitly qualified references that need to be identified and shown appropriately, e.g. by means of different colors. Multiple ‘coloring schemes’ can be applied to the same bibliography according to different criteria (e.g., as mentioned: by publication data of the references, by authorship and/or affiliation data, by justification for citing, by sentiment, and so on).
New visualization and browsing tools need to be implemented, for instance, by grouping citations, by coloring them, or by showing rich information in popups (for instance, about the citation contexts).