25th Aug 2020
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).
TIB Leibniz Information Centre for Science and Technology, DE
Abstract coming soon. Stay tuned!!
SESSION 1 | |
- | Welcome |
- | Keynote by Sören Auer - Describing scholarly contributions semantically with the Open Research Knowledge Graph |
- | Short Paper - Integrating Knowledge Graphs for Analysing Academia and Industry Dynamics. Simone Angioni, Angelo Antonio Salatino, Francesco Osborne, Diego Reforgiato Recupero and Enrico Motta. |
- | Break |
SESSION 2 | |
- | Long Paper - Open Science Graphs Must Interoperate! Amir Aryani, Martin Fenner, Paolo Manghi, Andrea Mannocci and Markus Stocker. |
- | Long Paper - WikiCSSH: Extracting Computer Science Subject Headings from Wikipedia. Kanyao Han, Pingjing Yang, Shubhanshu Mishra and Jana Diesner. |
- | Long Paper - DINGO an ontology for projects and grants linked data. Diego Chialva and Alexis Michel Mugabushaka. |
- | Break |
SESSION 3 | |
- | Short Paper - A Philological Perspective on Meta-Scientific Knowledge Graphs. Tobias Weber. |
- | Demo - Read and manipulate the OpenAIRE Research Graph Dump with R. Najko Jahn, Maximilian Held and Birgit Schmidt |
- | Demo - WikiCSSH: Extracting CS Subject Headings from Wikipedia for scholarly data. Kanyao Han, Pingjing Yang, Shubhanshu Mishra and Jana Diesner |
- | Demo - AIDA Dashboard. Simone Angioni, Angelo Antonio Salatino, Francesco Osborne, Diego Reforgiato Recupero and Enrico Motta |
- | Closing |
Due to COVID-19, the whole event (including both conference and workshop) will be held online. Registration fees for speakers have been simplified and decreased accordingly (check here for more info).
Participants/attendees benefit from a free registration, but must nonetheless register with the following online form: https://adbis-tpdl-eda-2020.insight-outside.fr/.
Italian Research Council (CNR), Pisa (IT)
The Open University, Milton Keynes (UK)
The Open University, Milton Keynes (UK)