[Rdap] Fwd: [section-editors] Data Science Journal Call for Papers: Advances in Data Modeling and Knowledge Representation for Research Data

Tue Dec 8 05:10:41 EST 2015

Dear colleagues,
find attached the last Call for Papers from CODATA Data Science Journal

Kind regards from Spain

Fernanda Peset
http://www.datasea.es

---------- Forwarded message ----------
From: Simon CODATA <simon at codata.org>
Date: 2015-12-08 9:14 GMT+01:00
Subject: [section-editors] Data Science Journal Call for Papers: Advances
in Data Modeling and Knowledge Representation for Research Data

The Data Science Journal is a peer-reviewed, open access, electronic
journal dedicated to the advancement of data science and its application in
policies, practices and management of Open Data.

*The Data Science Journal is seeking papers for a special issue devoted
to “Advances in Data Modeling and Knowledge Representation for Research
Data”.*

   - *Deadline for submissions: 31 March 2016*
   - *Detailed call for
   submissions:
http://www.codata.org/news/94/62/Data-Science-Journal-Call-for-Papers-Advances-in-Data-Modeling-and-Knowledge-Representation-for-Research-Data
   <http://www.codata.org/news/94/62/Data-Science-Journal-Call-for-Papers-Advances-in-Data-Modeling-and-Knowledge-Representation-for-Research-Data>*
   - *Data Science Journal: http://datascience.codata.org/
   <http://datascience.codata.org/>*

*Call for Papers: Advances in Data Modeling and Knowledge Representation
for Research Data*
Research data systems have matured greatly over the last decade - partly in
response to the growing complexity, amount, and heterogeneity of research
data. Innovations such as data harmonization, interoperability frameworks,
and feature extraction tools are greatly improving the capabilities of
research communities to access and manipulate data in computing systems.
Underpinning these new systems-level features and functionalities are a
number of robust conceptual, logical, and physical data models. These
include data- and curation-oriented models such as the Open Provenance
Model and the Research Object Model, as well as ontologies of observable
phenomena and objects such as the the Semantic Web for Earth and
Environmental Terminology (SWEET) ontologies and the Gene Ontology.

Unfortunately, the formal literature of data science often glosses over or
excludes the design work that goes into developing and implementing these
models. As a result it is often unclear how or why design decisions were
made, or what advances and new techniques have been developed for data
modeling and knowledge representation as they are applied to research data.
This special issue seeks contributions from the Data Science community on
the development, implementation, and evolution of data models and
ontologies - including the use of knowledge representation languages like
RDF and OWL in advancing the capabilities of research data systems. We
welcome submissions that report on empirical research that is completed or
in progress, as well as pieces that can clearly articulate grand
challenges and opportunities for advancing our current understanding of
data models, research data curation systems, and knowledge
representation, more generally.

*Submissions may cover topics including (but are not limited to):*

   - *Design choices: *A designer of a data model often faces choices
   between expressiveness, ease of use, and computational complexity - How are
   these tradeoffs accounted for in doing requirements engineering at the
   beginning stages of developing a curation system?
   - *Harmonization: *What are complications in, or best practices for
   harmoniz- ing conceptual models ? (e.g. FRBR + CIDOC CRM = FRBRoo)
   - *Interoperability: *How have data models been developed to facilitate
   cross or interdisciplinary data interoperability?
   - Requirements Engineering: Research data systems are often developed by
   working closely with data producers and potential systems users. How are
   requirements for a data model generated from these types of interactions?
   - *Ontology Development: *Ontologies capture a conceptualization of a
   domain. How are the essential aspects of research domain or a research data
   system to be analyzed for representation? How can an existing ontologies be
   evaluated for potential implementation or refinement?
   - *Sustainability: *Knowledge organization and representation activities
   con- tribute greatly to the sustainability and long-term success of
   a research data curation systems - How do these activities co-evolve with
   the discipline or domain that they serve? How have data models and metadata
   schemas been edited and revised to accommodate changes in scale,
   complexity, or heterogeneity of research data?
   - *Education: *What are the competencies necessary for doing knowledge
   representation work and research data systems development? How are these
   skills taught in classrooms, workshops, and continuing education programs

*Submissions can be of two types:*
*Research Papers *describe the outcomes and application of unpublished
original research. These should make a substantial contribution
to knowledge and understanding in the subject matter and should be
supported by relevant figures and where appropriate data. Research
Papers should be no more than 8,000 words in length.

*Practice Papers* report upon or critique a specific topic such as a
particularly difficult aspect of doing data modeling, education
in Knowledge Representation, or other topics related to the special issue’s
focus. Practice Papers can either describe the finished outputs of
a project, or the procedures, protocols, and models in use by an
established research data system. Practice Papers should be no longer
than 3,000 words in length.

*Article Processing Charges (APCs): *Potential authors should note that
Data Science Journal levies an APC of £350 for each article (Research Paper
or Practice Paper) published. Please contact the Guest Editors or
Editor-in-Chief, Sarah Callaghan (sarah.callaghan at stfc.ac.uk), if you have
any questions or think you will have difficulty meeting this cost.

*The deadlines associated with this special issue are as follows: - Full
papers due: March 31, 2016 - Special issue publication (anticipated):
December, 2016 Special-issue Guest Editors*

• Nic Weber (University of Washington) nmweber at uw.edu
• Karen Wickett (University of Texas)
• Pascal Hitzler (Wright State University)

___________________________

NEW! APPLICATIONS OPEN FOR CODATA-RDA RESEARCH DATA SCIENCE SUMMER SCHOOL:
http://indico.ictp.it/event/7658/

NEW! CALL FOR PAPERS, DATA SCIENCE JOURNAL: http://datascience.codata.org/

RECENT CODATA REPORTS:
http://codata.org/blog/2015/11/17/codata-collection-in-zenodo-recent-reports/
___________________________
Dr Simon Hodson | Executive Director CODATA | http://www.codata.org

E-Mail: simon at codata.org | Twitter: @simonhodson99 | Skype: simonhodson99
Blog: http://www.codata.org/blog
Diary: http://bit.ly/simonhodson99-calendar
Tel (Office): +33 1 45 25 04 96 | Tel (Cell): +33 6 86 30 42 59

CODATA (ICSU Committee on Data for Science and Technology), 5 rue Auguste
Vacquerie, 75016 Paris, FRANCE

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