SKG 2020 : 1st​ Workshop on Scientific Knowledge Graphs

  in Conferences   Posted on February 28, 2020

Conference Information

Submission Deadline Saturday 04 Apr 2020 Proceedings indexed by :
Conference Dates Aug 25, 2020 - Aug 28, 2020
Conference Address Lyon, France
Conference & Submission Link
Conference Organizers : ( Deadline extended ? Click here to edit )

Conference Call for Papers



1st​ Workshop on Scientific Knowledge Graphs

Held in conjunction with TPDL2020 (Lyon, France), 25th-28th August 2020

Twitter: @skgworkshop



Apologies for cross-posting.




– Paper deadline: April 4, 2020

– Notification: May 5, 2020

– Camera-ready due: June 5, 2020

– Workshop day: TBA (25th-28th August)




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


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).




We encourage the submission of papers covering, but not limited to, one or

more of the following topics:

– Methods for extracting entities (methods, research topics, technologies,

tasks, materials, metrics, research contributions) and relationships from

research publications

– Methods for extracting metadata about authors, documents, datasets, grants,

affiliations and others.

– Data models (e.g., ontologies, vocabularies, schemas) for the description

of scholarly data and the linking between scholarly data/software and

academic papers that report or cite them

– Description of citations for scholarly articles, data and software and

their interrelationships

– Applications for the (semi-)automatic annotation of scholarly papers

– Theoretical models describing the rhetorical and argumentative structure

of scholarly papers and their application in practice

– Methods for quality assessment of scientific knowledge graphs

– Description and use of provenance information of scholarly data

– Methods for the exploration, retrieval and visualization of scientific

knowledge graphs

– Pattern discovery of scholarly data

– Scientific claims identification from textual contents

– Automatic or semi-automatic approaches to making sense of research dynamics

– Content- and data-based analysis on scholarly papers

– Automatic semantic enhancement of existing scholarly libraries and papers

– Reconstruction, forecasting and monitoring of scholarly data

– Novel user interfaces for interaction with paper, metadata, content,

software and data

– Visualisation of related papers or data according to multiple dimensions

(semantic similarity of abstracts, keywords, etc.)

– Applications for making sense of scholarly data




Submissions are welcome in the following categories:

– Full papers presenting original work (12 pages incl. refer., LNCS format)

– Short papers presenting original work (6 pages incl. refer., LNCS format)

Papers can be submitted via EasyChair:

Submissions will be evaluated based on originality, significance, technical

soundness and clarity.

Accepted papers (after blind review of at least 3 experts) will be published

in the Springer CCIS series. The best paper (according to the reviewers’

rate) will be invited to a special issue of the journal Computer Science and

Information Systems.

At least one of the authors of the accepted papers must register for the

workshop to be included in the workshop proceedings.

All paper submissions have to be in English and submitted as a PDF file.

Authors should consult Springer’s authors’ guidelines and use their

proceedings templates, either for LaTeX or Word, for the preparation of their

papers. Springer encourages authors to include their ORCIDs in their papers.




Andrea Mannocci, Italian Research Council (CNR), Pisa (IT)

Francesco Osborne, The Open University, Milton Keynes (UK)

Angelo Salatino, The Open University, Milton Keynes (UK)

More information about SKG2020 is available at


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