[DL] [CfP] Sci-K @ The Web Conference 2021 – 1st International Workshop on Scientific Knowledge Representation, Discovery, and Assessment
Angelo Salatino
aas88ie at gmail.com
Wed Dec 2 14:53:43 CET 2020
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CALL FOR PAPERS
Sci-K – 1st International Workshop on Scientific Knowledge Representation,
Discovery, and Assessment in conjunction with The Web Conference (WWW) 2021
April 19-23, 2021, Ljubljana, Slovenia
web: https://sci-k.github.io, twitter: @scik_workshop
Submissions deadline: January 25, 2021
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Aim and Scope:
In the last decades, we have experienced a substantial increase in the
volume of published scientific articles and related research objects (e.g.,
data sets, software packages); a trend that is expected to continue. This
opens up fundamental challenges including generating large-scale
machine-readable representations of scientific knowledge, making scholarly
data discoverable and accessible, and designing reliable and comprehensive
metrics to assess scientific impact. The main objective of Sci-K is to
provide a forum for researchers and practitioners from different
disciplines to present, educate from, and guide research related to
scientific knowledge. Specifically, we foresee three main themes that cover
the most important challenges in the field: representation,
discoverability, and assessment.
Representation. There is an urge for flexible, context-sensitive,
fine-grained, and machine-actionable representations of scholarly knowledge
that at the same time are structured, interlinked, and semantically rich:
Scientific Knowledge Graphs (SKGs). These resources can power several
data-driven services for navigating, analysing, and making sense of
research dynamics. Current challenges are related to the design of
ontologies able to conceptualise scholarly knowledge, model its
representation, and enable its exchange across different SKGs.
Discoverability. It is important that scholarly information is easily
findable, discoverable, and visible, so that it can be mined and organised
within SKGs. Hence, we need discovery tools able to crawl the Web and
identify scholarly data, whether on a publisher’s website or elsewhere –
institutional repositories, preprint servers, open-access repositories, and
others. This is a particularly challenging endeavour as it requires a deep
understanding of both the scholarly communication landscape and the needs
of a variety of stakeholders: researchers, publishers, funders, and the
general public. Other challenges are related to the discovery and
extraction of entities and concepts, integration of information from
heterogeneous sources, identification of duplicates, finding connections
between entities, and identifying conceptual inconsistencies.
Assessment. Due to the continuous growth in the volume of research output,
rigorous approaches for the assessment of research impact are now more
valuable than ever. In this context, we urge reliable and comprehensive
metrics and indicators of the scientific impact and merit of publications,
datasets, research institutions, individual researchers, and other relevant
entities.
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Topics of Interest:
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Representation
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Data models for the description of scholarly data and their
relationships.
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Description and use of provenance information of scientific data.
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Integration and interoperability models of different data sources.
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Discoverability
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Methods for extracting metadata, entities and relationships from
scientific data.
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Methods for the (semi-)automatic annotation and enhancement of
scientific data.
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Methods and interfaces for the exploration, retrieval, and
visualisation of scholarly data.
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Assessment
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Novel methods, indicators, and metrics for quality and impact
assessment of scientific publications, datasets, software, and other
relevant entities based on scholarly data.
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Uses of scientific knowledge graphs and citation networks for the
facilitation of research assessment.
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Studies regarding the characteristics or the evolution of scientific
impact or merit.
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Submission Guidelines:
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Full Research papers (10 pages max)
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Short Research papers (4 pages max)
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Vision/Position papers (4 pages max)
The workshop calls for full research papers (up to 10 pages), describing
original work on the listed topics, and short papers (up to 4 pages), on
early research results, new results on previously published works, demos,
and projects. In accordance with Open Science principles, research papers
may also be in the form of data papers and software papers (short or long
papers). The former present the motivation and methodology behind the
creation of data sets that are of value to the community; e.g., annotated
corpora, benchmark collections, training sets. The latter present software
functionality, its value for the community, and its application to a
non-specialist reader. To enable reproducibility and peer-review, authors
will be requested to share the DOIs of the data sets and the software
products described in the articles and thoroughly describe their
construction and reuse.
The workshop will also call for vision/position papers (up to 4 pages)
providing insights towards new or emerging areas, innovative or risky
approaches, or emerging applications that will require extensions to the
state of the art. These do not have to include results already, but should
carefully elaborate about the motivation and the ongoing challenges of the
described area.
Submissions for review must be in PDF format and must adhere to the ACM
template and format. Submissions that do not follow these guidelines, or do
not view or print properly, may be rejected without review.
The proceedings of the workshops will be published jointly with The Web
Conference 2021 proceedings.
Submit your contributions following the link:
https://sci-k.github.io/#submission
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Important Dates:
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Workshop paper submissions due: January 25, 2021
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Workshop paper notifications due: February 15, 2021
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Camera-ready versions due: March 1, 2021
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Workshop Day: April 19-23, 2021
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Organizing Committee (alphabetical order):
Paolo Manghi, ISTI-CNR, Italy
Andrea Mannocci, ISTI-CNR, Italy
Francesco Osborne, The Open University, UK
Dimitris Sacharidis, TU Wien, Austria
Angelo Salatino, The Open University, UK
Thanasis Vergoulis, “Athena” RC, Greece
*Angelo Antonio Salatino [salatino.org <http://salatino.org/>]
[**about.me/angelosalatino
<http://about.me/angelosalatino>]*
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