[Esip-discovery] FW: [EXTERNAL] [SIG-IRList] [Call for papers] - 1st​ Workshop on Scientific Knowledge Graphs (SKG2020)

[Mcgibbney, Lewis J (172B)]

FYI

Dr. Lewis John McGibbney Ph.D., B.Sc.(Hons)
Enterprise Search Technologist

Web and Mobile Application Development Group (172B)
Application, Consulting, Development and Engineering Section (1722)
Info & Engineering Technology Planning and Development Division (1720)

Jet Propulsion Laboratory

California Institute of Technology 

4800 Oak Grove Drive

Pasadena, California 91109-8099

Mail Stop : 600-172A

Tel:  (+1) (818)-393-7402

Cell: (+1) (626)-487-3476

Fax:  (+1) (818)-393-1190

Email: lewis.j.mcgibbney at jpl.nasa.gov
ORCID: orcid.org/0000-0003-2185-928X

 

           

 

 Dare Mighty Things

On 2/25/20, 1:56 AM, "ACM SIGIR Mailing List on behalf of Angelo Salatino" <SIGIR at LISTSERV.ACM.ORG on behalf of aas88ie at GMAIL.COM> wrote:

    Dear all,
    
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    SKG2020
    1st Workshop on Scientific Knowledge Graphs
    Held in conjunction with TPDL2020 (Lyon, France), 25th-28th August 2020
    Twitter: @skgworkshop
    Website: https://skg.kmi.open.ac.uk
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    Apologies for cross-posting.
    
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    IMPORTANT DATES
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    - Paper deadline: April 4, 2020
    - Notification: May 5, 2020
    - Camera-ready due: June 5, 2020
    - Workshop day: TBA (25th-28th August)
    
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    SCOPE
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    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.
    
    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).
    
    
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    TOPICS
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    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
    
    
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    SUBMISSION DETAILS
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    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:
    https://easychair.org/conferences/?conf=skg2020
    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.
    
    
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    CHAIRS
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    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 https://skg.kmi.open.ac.uk
    Contact: skg2020 at easychair.org
    
    --
    Angelo Salatino
    Research Associate
    Knowledge Media Institute,
    The Open University
    Twttr: @angelosalatino <https://twitter.com/angelosalatino>
    Web: https://salatino.org <https://salatino.org/>