[DL] [CfP] Sci-K @ The Web Conference 2023 – 3rd International Workshop on Scientific Knowledge Representation, Discovery, and Assessment

[Angelo Salatino]

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CALL FOR PAPERS

Sci-K – 3rd International Workshop on Scientific Knowledge Representation,
Discovery, and Assessment in conjunction with The Web Conference (WWW) 2023



April 30-May 4, 2024, Austin, Texas, USA

web: https://sci-k.github.io, twitter: @scik_workshop

Submissions deadline: February 6th, 2023

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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, and guide research related to scientific
knowledge. Specifically, we foresee three main themes that cover the most
important challenges in this 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, comprehensive, and
equitable 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:



   -

   Representation
   -

      Data models for the description of scholarly data and their
      relationships.
      -

      Description and use of provenance information of scientific data.
      -

      Integration and interoperability models of different data sources.
      -

   Discoverability
   -

      Methods for extracting metadata, entities and relationships from
      scientific data.
      -

      Methods for the (semi-)automatic annotation and enhancement of
      scientific data.
      -

      Methods and interfaces for the exploration, retrieval, and
      visualisation of scholarly data.
      -

   Assessment
   -

      Novel methods, indicators, and metrics for quality and impact
      assessment of scientific publications, datasets, software, and other
      relevant entities based on scholarly data.
      -

      Uses of scientific knowledge graphs and citation networks for the
      facilitation of research assessment.
      -

      Studies regarding the characteristics or the evolution of scientific
      impact or merit.



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Submission Guidelines:

   -

   Full research papers (up to 8 pages for main content)
   -

   Short research papers (up to 4 pages for main content)
   -

   Vision/Position papers (up to 4 pages for main content)



The workshop calls for full research papers (up to 8 pages + 2 pages of
appendices + 2 pages of references), describing original work on the listed
topics, and short papers (up to 4 pages + 2 pages of appendices + 2 pages
of references), 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 presents 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 + 2
pages of appendices + 2 pages of references) 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 2023 proceedings.



Submit your contributions following the link:
https://sci-k.github.io/2023/#submission



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Important Dates:

   -

   Paper submission: February 6th, 2023 (23:59, AoE timezone)
   -

   Notification of acceptance: March 6th, 2023
   -

   Camera-ready due: March 20th, 2023 (23:59, AoE timezone)
   -

   Workshop day: April 30th or May 1st, 2023 (TBA)





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Organizing Committee (alphabetical order):

Yi Bu, Peking University, China

Ying Ding, University of Texas, Austin, US

Ágnes Horvát, Northwestern University, US

Yong Huang, Wuhan University, China

Meijun Liu, Fudan University, China

Paolo Manghi, ISTI-CNR, Italy

Andrea Mannocci, ISTI-CNR, Italy

Francesco Osborne, The Open University, UK

Daniel Romero, University of Michigan, US

Dimitris Sacharidis, Université Libre De Bruxelles, Belgium

Angelo Salatino, The Open University, UK

Misha Teplitskiy, University of Michigan, US

Thanasis Vergoulis, “Athena” RC, Greece

Feng Xia, RMIT University, Australia

Yujia Zhai, Tianjin Normal University, China
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