Rexplore

Exploring Research Data

Rexplore leverages novel solutions in large-scale data mining, semantic technologies and visual analytics, to provide an innovative environment for exploring and making sense of scholarly data. In particular, Rexplore allows users:

To detect and make sense of important trends in research, such as, significant migrations of researchers from one area to another, the emergence of new topics, the evolution of communities within a particular area, and several others.

To identify a variety of interesting relations between researchers, e.g., recognizing authors who share similar research trajectories. These relations go well beyond the standard co-authorship links or relationships informed by social networks, which are commonly found in other systems.

To perform fine-grained expert search with respect to detailed multi-dimensional parameters.

To analyse research performance at different levels of abstraction, including individual researchers, organizations, countries, and research communities identified on the basis of dynamic criteria.

An important aspect of Rexplore is that it does not rely on manually-generated taxonomies of research areas, which tend to be shallow and date very rapidly, but uses instead an innovative ontology population algorithm, Klink, which automatically constructs a semantic network of fine-grained research areas, linked by semantic relations, such as sameAs and subAreaOf. The use of Klink ensures a fine-grained handling of research areas and affords Rexplore a very high level of precision and recall in associating topics to publications and researchers.

Rexplore offers an advanced graphical interface, comprising a variety of innovative and fine grained visualizations, which support users in exploring authors, topics, and research communities. To support effective exploration, all graphical elements can be clicked on, thus enabling a seamless and contextualized navigation.

Angelo Salatino

Angelo Salatino

Ilaria Tiddi

Mathieu d'Aquin

Mannocci, A., Osborne, F. and Motta, E. (2019) Geographical trends in academic conferences: An analysis of authors' affiliations Special Issue about Semantics, Analytics and Visualisation: Enhancing Scholarly Dissemination, pp. (Early Access), IOS Press

Buscaldi, D., Dessì, D., Motta, E., Osborne, F. and Recupero, D. (2019) Mining Scholarly Publications for Scientific Knowledge Graph Construction, Extended Semantic Web Conference 2019, Portoroz, Slovenia

Osborne, F. and Hollink, L. (eds.) (2019) Proceedings of the EKAW Doctoral Consortium 2018 co-located with the 21st International Conference on Knowledge Engineering and Knowledge Management (EKAW 2018), Nancy, France, November 13, 2018., eds. Laura Hollink,Francesco Osborne, 2306, CEUR

Mannocci, A., Osborne, F. and Motta, E. (2019) The Evolution of IJHCS and CHI: A Quantitative Analysis The Evolution of IJHCS and CHI: A Quantitative Analysis, pp. (In Press)

Salatino, A.A., Thanapalasingam, T., Mannocci, A., Osborne, F. and Motta, E. (2018) Classifying Research Papers with the Computer Science Ontology, Poster at International Semantic Web Conference, Posters & Demonstrations and Industry Tracks, MONTEREY, CALIFORNIA, USA ISWC 2018