Categories |
DIGITAL LIBRARIES
KNOWLEDGE GRAPHS
SEMANTIC WEB
|
About |
In the last decade, we experienced an urgent need for a flexible, context-sensitive, fine-grained, and machine-actionable representation of scholarly knowledge and corresponding infrastructures for knowledge curation, publishing and processing. Such technical infrastructures are becoming increasingly popular in representing scholarly knowledge as structured, interlinked, and semantically rich Scientific Knowledge Graphs (SKG). Knowledge graphs are large networks of entities and relationships, usually expressed in W3C standards such as OWL and RDF. SKGs focus on the scholarly domain and describe the actors (e.g., authors, organizations), the documents (e.g., publications, patents), and the research knowledge (e.g., research topics, tasks, technologies) in this space as well as their reciprocal relationships. These resources provide substantial benefits to researchers, companies, and policymakers by powering several data-driven services for navigating, analysing, and making sense of research dynamics. Some examples include Microsoft Academic Graph (MAG), Open Academic Graph (combining MAG and AMiner), ScholarlyData, PID Graph, Open Research Knowledge Graph, OpenCitations, and OpenAIRE research graph. Current challenges in this area include: i) the design of ontologies able to conceptualise scholarly knowledge, ii) (semi-)automatic extraction of entities and concepts, integration of information from heterogeneous sources, identification of duplicates, finding connections between entities, and iii) the development of new services using this data, that allow to explore this information, measure research impact and accelerate science. This workshop aims at bringing together researchers and practitioners from different fields (including, but not limited to, Digital Libraries, Information Extraction, Machine Learning, Semantic Web, Knowledge Engineering, Natural Language Processing, Scholarly Communication, and Bibliometrics) in order to explore innovative solutions and ideas for the production and consumption of Scientific Knowledge Graphs (SKGs). |
Call for Papers |
We encourage papers that directly contribute to the advancement of the Scientific Knowledge Graphs. Topics include, but are not limited to:
SUBMISSION DETAILSSubmissions are welcome in the following categories:
Papers must comply with the LNCS style and should be submitted in PDF format via the workshop’s EasyChair (skg2020) submission pages. IMPORTANT DATES
|
Summary |
SKG 2020 : Workshop at TPDL 2020 on SCIENTIFIC KNOWLEDGE GRAPHS will take place in Lyon, France. It’s a 4 days event starting on Aug 25, 2020 (Tuesday) and will be winded up on Aug 28, 2020 (Friday). SKG 2020 falls under the following areas: DIGITAL LIBRARIES, KNOWLEDGE GRAPHS, SEMANTIC WEB, etc. Submissions for this Workshop can be made by Apr 04, 2020. Authors can expect the result of submission by May 05, 2020. Upon acceptance, authors should submit the final version of the manuscript on or before Jun 05, 2020 to the official website of the Workshop. Please check the official event website for possible changes before you make any travelling arrangements. Generally, events are strict with their deadlines. It is advisable to check the official website for all the deadlines. Other Details of the SKG 2020
|
Credits and Sources |
[1] SKG 2020 : Workshop at TPDL 2020 on SCIENTIFIC KNOWLEDGE GRAPHS |