[CfP] Extension: Second Workshop on Capturing Scientific Knowledge (SciKnow) at KCAP2017

The deadline for SciKnow 2017 has been extended one week!

Second International Workshop on Capturing Scientific Knowledge,
in conjunction with the 9th conference on Knowledge Capture (K-CAP 2017)

December 4-6, 2017

Austin, TX, USA

Workshop page: https://sciknow.github.io/sciknow2017



   Submission deadline: *September 24th, 2017*

   Author notification: October 1st, 2017

   Workshop: December 4, 2017


>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.


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:

      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.

      What are effective approaches that enable open sharing,
      dissemination, and reuse of scientific knowledge?

Submissions can be made in the following categories:


   Report papers: Overviews or summaries of past work on approaches to
   represent and capture scientific knowledge.

   Research papers: Novel results of research on scientific knowledge
   representation or capture.

   Position papers: Discussion on issues concerning the representation,
   capture, and dissemination of scientific knowledge, particularly to
   facilitate cross-disciplinary integrative science.

   Challenge papers: Specific scenarios that describe the benefits to
   science if the limitations identified are overcome.

Submissions should be *up to 6 pages* and in the format of the ACM SIG
Proceedings template: http://www.acm.org/sigs/public
ations/proceedings-templates. However, SciKnow 2017 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 emailed to *sciknow2017@gmail.com

Accepted papers will be made available on the workshop site https://sciknow
.github.io/sciknow2017/, and published on the conference proceedings.

Workshop Chairs:


   Daniel Garijo, University of Southern California

   Martine de Vos, Netherlands eScience center

Received on Monday, 18 September 2017 14:57:11 UTC