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<div class="PlainText">fyi<br>
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On 2/25/20, 1:56 AM, "ACM SIGIR Mailing List on behalf of Angelo Salatino" <SIGIR@LISTSERV.ACM.ORG on behalf of aas88ie@GMAIL.COM> wrote:<br>
<br>
Dear all,<br>
<br>
=============================================================================<br>
SKG2020<br>
1st Workshop on Scientific Knowledge Graphs<br>
Held in conjunction with TPDL2020 (Lyon, France), 25th-28th August 2020<br>
Twitter: @skgworkshop<br>
Website: <a href="https://urldefense.proofpoint.com/v2/url?u=https-3A__skg.kmi.open.ac.uk&d=DwIGaQ&c=ApwzowJNAKKw3xye91w7BE1XMRKi2LN9kiMk5Csz9Zk&r=img-rO8ZBhblrx41WBkIFetQkzEsdhT-s4UDDrJe0Xk&m=lgr5YtAvGixX0qkvNkdyZtMKGZbpYq86_-oWXJ2rpq0&s=uoFEP24nueUqy0ej_XFp0PrJZn2rq0zfHut9wF1lXTE&e=">
https://urldefense.proofpoint.com/v2/url?u=https-3A__skg.kmi.open.ac.uk&d=DwIGaQ&c=ApwzowJNAKKw3xye91w7BE1XMRKi2LN9kiMk5Csz9Zk&r=img-rO8ZBhblrx41WBkIFetQkzEsdhT-s4UDDrJe0Xk&m=lgr5YtAvGixX0qkvNkdyZtMKGZbpYq86_-oWXJ2rpq0&s=uoFEP24nueUqy0ej_XFp0PrJZn2rq0zfHut9wF1lXTE&e=</a><br>
=============================================================================<br>
<br>
<br>
Apologies for cross-posting.<br>
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IMPORTANT DATES<br>
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<br>
- Paper deadline: April 4, 2020<br>
- Notification: May 5, 2020<br>
- Camera-ready due: June 5, 2020<br>
- Workshop day: TBA (25th-28th August)<br>
<br>
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SCOPE<br>
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<br>
In the last decade, we experienced an urgent need for a flexible, context-<br>
sensitive, fine-grained, and machine-actionable representation of scholarly<br>
knowledge and corresponding infrastructures for knowledge curation,<br>
publishing and processing. Such technical infrastructures are becoming<br>
increasingly popular in representing scholarly knowledge as structured,<br>
interlinked, and semantically rich Scientific Knowledge Graphs (SKG).<br>
Knowledge graphs are large networks of entities and relationships, usually<br>
expressed in W3C standards such as OWL and RDF. SKGs focus on the scholarly<br>
domain and describe the actors (e.g., authors, organizations), the documents<br>
(e.g., publications, patents), and the research knowledge (e.g., research<br>
topics, tasks, technologies) in this space as well as their reciprocal<br>
relationships.<br>
<br>
Current challenges in this area include: i) the design of ontologies able to<br>
conceptualise scholarly knowledge, ii) (semi-)automatic extraction of<br>
entities and concepts, integration of information from heterogeneous sources,<br>
identification of duplicates, finding connections between entities, and iii)<br>
the development of new services using this data, that allow to explore this<br>
information, measure research impact and accelerate science.<br>
<br>
This workshop aims at bringing together researchers and practitioners from<br>
different fields (including, but not limited to, Digital Libraries,<br>
Information Extraction, Machine Learning, Semantic Web, Knowledge<br>
Engineering, Natural Language Processing, Scholarly Communication, and<br>
Bibliometrics) in order to explore innovative solutions and ideas for the<br>
production and consumption of Scientific Knowledge Graphs (SKGs).<br>
<br>
<br>
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TOPICS<br>
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<br>
We encourage the submission of papers covering, but not limited to, one or<br>
more of the following topics:<br>
- Methods for extracting entities (methods, research topics, technologies,<br>
tasks, materials, metrics, research contributions) and relationships from<br>
research publications<br>
- Methods for extracting metadata about authors, documents, datasets, grants,<br>
affiliations and others.<br>
- Data models (e.g., ontologies, vocabularies, schemas) for the description<br>
of scholarly data and the linking between scholarly data/software and<br>
academic papers that report or cite them<br>
- Description of citations for scholarly articles, data and software and<br>
their interrelationships<br>
- Applications for the (semi-)automatic annotation of scholarly papers<br>
- Theoretical models describing the rhetorical and argumentative structure<br>
of scholarly papers and their application in practice<br>
- Methods for quality assessment of scientific knowledge graphs<br>
- Description and use of provenance information of scholarly data<br>
- Methods for the exploration, retrieval and visualization of scientific<br>
knowledge graphs<br>
- Pattern discovery of scholarly data<br>
- Scientific claims identification from textual contents<br>
- Automatic or semi-automatic approaches to making sense of research dynamics<br>
- Content- and data-based analysis on scholarly papers<br>
- Automatic semantic enhancement of existing scholarly libraries and papers<br>
- Reconstruction, forecasting and monitoring of scholarly data<br>
- Novel user interfaces for interaction with paper, metadata, content,<br>
software and data<br>
- Visualisation of related papers or data according to multiple dimensions<br>
(semantic similarity of abstracts, keywords, etc.)<br>
- Applications for making sense of scholarly data<br>
<br>
<br>
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SUBMISSION DETAILS<br>
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<br>
Submissions are welcome in the following categories:<br>
- Full papers presenting original work (12 pages incl. refer., LNCS format)<br>
- Short papers presenting original work (6 pages incl. refer., LNCS format)<br>
<br>
Papers can be submitted via EasyChair:<br>
<a href="https://urldefense.proofpoint.com/v2/url?u=https-3A__easychair.org_conferences_-3Fconf-3Dskg2020&d=DwIGaQ&c=ApwzowJNAKKw3xye91w7BE1XMRKi2LN9kiMk5Csz9Zk&r=img-rO8ZBhblrx41WBkIFetQkzEsdhT-s4UDDrJe0Xk&m=lgr5YtAvGixX0qkvNkdyZtMKGZbpYq86_-oWXJ2rpq0&s=c1WwWbxBGVQ6i90xXc0rIoknTkxO000agxck5psuH3E&e=">
https://urldefense.proofpoint.com/v2/url?u=https-3A__easychair.org_conferences_-3Fconf-3Dskg2020&d=DwIGaQ&c=ApwzowJNAKKw3xye91w7BE1XMRKi2LN9kiMk5Csz9Zk&r=img-rO8ZBhblrx41WBkIFetQkzEsdhT-s4UDDrJe0Xk&m=lgr5YtAvGixX0qkvNkdyZtMKGZbpYq86_-oWXJ2rpq0&s=c1WwWbxBGVQ6i90xXc0rIoknTkxO000agxck5psuH3E&e=</a><br>
Submissions will be evaluated based on originality, significance, technical<br>
soundness and clarity.<br>
<br>
Accepted papers (after blind review of at least 3 experts) will be published<br>
in the Springer CCIS series. The best paper (according to the reviewers’<br>
rate) will be invited to a special issue of the journal Computer Science and<br>
Information Systems.<br>
<br>
At least one of the authors of the accepted papers must register for the<br>
workshop to be included in the workshop proceedings.<br>
<br>
All paper submissions have to be in English and submitted as a PDF file.<br>
Authors should consult Springer’s authors’ guidelines and use their<br>
proceedings templates, either for LaTeX or Word, for the preparation of their<br>
papers. Springer encourages authors to include their ORCIDs in their papers.<br>
<br>
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CHAIRS<br>
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<br>
Andrea Mannocci, Italian Research Council (CNR), Pisa (IT)<br>
Francesco Osborne, The Open University, Milton Keynes (UK)<br>
Angelo Salatino, The Open University, Milton Keynes (UK)<br>
<br>
More information about SKG2020 is available at <a href="https://urldefense.proofpoint.com/v2/url?u=https-3A__skg.kmi.open.ac.uk&d=DwIGaQ&c=ApwzowJNAKKw3xye91w7BE1XMRKi2LN9kiMk5Csz9Zk&r=img-rO8ZBhblrx41WBkIFetQkzEsdhT-s4UDDrJe0Xk&m=lgr5YtAvGixX0qkvNkdyZtMKGZbpYq86_-oWXJ2rpq0&s=uoFEP24nueUqy0ej_XFp0PrJZn2rq0zfHut9wF1lXTE&e=">
https://urldefense.proofpoint.com/v2/url?u=https-3A__skg.kmi.open.ac.uk&d=DwIGaQ&c=ApwzowJNAKKw3xye91w7BE1XMRKi2LN9kiMk5Csz9Zk&r=img-rO8ZBhblrx41WBkIFetQkzEsdhT-s4UDDrJe0Xk&m=lgr5YtAvGixX0qkvNkdyZtMKGZbpYq86_-oWXJ2rpq0&s=uoFEP24nueUqy0ej_XFp0PrJZn2rq0zfHut9wF1lXTE&e=</a><br>
Contact: skg2020@easychair.org<br>
<br>
--<br>
Angelo Salatino<br>
Research Associate<br>
Knowledge Media Institute,<br>
The Open University<br>
Twttr: @angelosalatino <https://urldefense.proofpoint.com/v2/url?u=https-3A__twitter.com_angelosalatino&d=DwIGaQ&c=ApwzowJNAKKw3xye91w7BE1XMRKi2LN9kiMk5Csz9Zk&r=img-rO8ZBhblrx41WBkIFetQkzEsdhT-s4UDDrJe0Xk&m=lgr5YtAvGixX0qkvNkdyZtMKGZbpYq86_-oWXJ2rpq0&s=SocUsSBdTSvwIwn6uSwGXouOJlibOuO6YTWLvdJuogY&e=
><br>
Web: <a href="https://urldefense.proofpoint.com/v2/url?u=https-3A__salatino.org&d=DwIGaQ&c=ApwzowJNAKKw3xye91w7BE1XMRKi2LN9kiMk5Csz9Zk&r=img-rO8ZBhblrx41WBkIFetQkzEsdhT-s4UDDrJe0Xk&m=lgr5YtAvGixX0qkvNkdyZtMKGZbpYq86_-oWXJ2rpq0&s=TPi1dQ3nMqiO1DGwW2OsQcrpOXw8PZ4ItB-YwonEpG8&e=">
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><br>
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