About

In the last decades, there has been a surge in the volume of published scientific articles and related research objects (e.g., data sets, software, models), a trend that is expected to continue. The Sci-K workshop aims to provide a forum for researchers and practitioners from different disciplines to present, educate from, and guide research related to scientific knowledge. Specifically, we foresee three main challenging themes.

Representation. There is an urge for Scientific Knowledge Graphs (SKGs), that offer flexible, context-sensitive, fine-grained, and machine-actionable representations of scholarly knowledge that, at the same time, are structured, interlinked, and semantically rich. The key challenge in this area is the development of ontologies that can capture the conceptualisation, representation, and interoperability of scholarly knowledge across different SKGs.

Discovery. It is crucial that scholarly information is easily findable, discoverable, and visible so that it can be mined and organised within SKGs. Current challenges are related to discovering and extracting entities and concepts, integrating information from heterogeneous sources, identifying duplicates, finding connections between entities, and identifying conceptual inconsistencies.

Assessment. Due to the continuous growth in the volume of research outputs, we need reliable and comprehensive indicators of scientific impact and merit for the diverse scientific outputs and actors.

The Sci-K series spawned from the collaboration of two workshops, namely, the Scientific Knowledge Graphs Workshop (SKG 2020), and the Workshop on Assessing Impact and Merit in Science (AIMinScience 2020), held in conjunction with the 2020 edition of the International Conference on Theory and Practice of Digital Libraries (TPDL).

Sci-k prides itself for having attracted submissions from 27 different countries, including 8 from the Global South, and with at least 40 attendees per edition.