[CfP] Third International Workshop on Capturing Scientific Knowledge (co-located with K-CAP 2019)

Join us at the Third International Workshop on Capturing Scientific 
Knowledge,
in conjunction with the 10th conference on Knowledge Capture (K-CAP 2019)
*November 19-21, 2019*
Marina del Rey, Los Angeles, USA

Workshop page: https://sciknow.github.io/sciknow2019

IMPORTANT DATES

     Submission deadline: *September 27, 2019.*
     Author notification: October 8, 2019.
     Workshop: November 19, 2019.

CALL FOR PAPERS

 From the early days of Artificial Intelligence, researchers have been 
interested in capturing scientific knowledge to develop intelligent 
systems. There are a variety of formalisms used today in different areas 
of science. Ontologies are widely used for organizing knowledge, 
particularly in biology and medicine. Process representations are used 
to do qualitative reasoning in areas such as physics and chemistry. 
Probabilistic graphical models are used by machine learning researchers, 
e.g., in climate modeling.

In addition to enabling more advanced capabilities for intelligent 
systems in science, capturing scientific knowledge enables knowledge 
dissemination and open science practices. This is increasingly more 
important to enable the reuse of scientific knowledge across scientific 
disciplines, businesses and the public.

Although great advances have been made, scientific knowledge is complex 
and poses great challenges for knowledge capture. This workshop will 
provide a forum to discuss existing forms of scientific knowledge 
representation and existing systems that use them, and to envision major 
areas to augment and expand this important field of research.

The increasing emphasis in open science has had a major focus on data 
sharing but it needs to encompass knowledge as well. There are many 
research challenges in open sharing and reuse of scientific knowledge 
that need to be addressed in future research.

SUBMISSIONS
Major topics of interest for this workshop include:

  * Capture of scientific knowledge:
      o Successful knowledge capture and representation formalisms are
        used in a variety of scientific domains, what are their key
        features and merits?
      o Scientific knowledge is inherently complex and requires
        significant effort to capture.  What are effective approaches to
        model and to acquire scientific knowledge?
  * Representation of scientific knowledge:
      o Given the variety of representation formalisms for scientific
        knowledge, how can   they be combined to enable more advanced
        capabilities?
      o What approaches can support the uncertainty and evolution
        inherent in scientific models?
  * (Re)use of scientific knowledge:
      o   Imagine what scientific breakthroughs might be enabled with
        improved representational schema of existing scientific
        knowledge, and of course the subsequent capture of additional
        scientific knowledge.
      o What are effective approaches that enable open sharing,
        dissemination, and reuse of scientific knowledge?

Submissions can be made in the following categories:

  * Report papers (up to 6 pages): Overviews or summaries of past work
    on approaches to represent and capture scientific knowledge.
  * Research papers (up to 6 pages): Novel results of research on
    scientific knowledge representation or capture.
  * Position papers (up to 4 pages): Discussion on issues concerning the
    representation, capture, and dissemination of scientific knowledge,
    particularly to facilitate cross-disciplinary integrative science.
  * Challenge papers (up to 4 pages): Specific scenarios that describe
    the benefits to science if the limitations identified are overcome.

Submissions should follow the Standard ACM SIG Conference Proceedings 
template: https://www.acm.org/publications/proceedings-template. 
However, SciKnow 2019 *explicitly welcomes alternative and enhanced 
submission formats, such as HTML submissions*. Authors who are preparing 
such a submission should contact the workshop organizers in advance to 
make sure we can accommodate for them in the submission and review process.

Submissions should be managed through Easychair 
(https://easychair.org/conferences/?conf=sciknow2019). At least one 
author of each accepted paper is expected to attend the workshop.

Accepted papers will be published with the CEUR Workshop Proceedings 
(CEUR-WS.org), listed by DBLP.

Workshop Chairs:

  Daniel Garijo, Information Sciences Institute, University of Southern 
California
  Milan Markovic, University of Aberdeen
  Paul Groth, University of Amsterdam
  Idafen Santana, Instituto Canario de Estadistica
  Khalid Belhajjame, University Paris-Dauphine