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journal Data Science: Special Issue on FAIR Data, Systems and Analysis

From: Michel Dumontier <michel.dumontier@gmail.com>
Date: Tue, 19 Mar 2019 09:38:31 +0100
Message-ID: <CALcEXf5ZTGhkjYoUC+4O7KbP88Mi-w2JnmAr-CY1ORLJzJhDYw@mail.gmail.com>
To: w3c semweb hcls <public-semweb-lifesci@w3.org>
The journal Data Science (https://datasciencehub.net) invites submissions
for a special issue on FAIR Data, Systems and Analysis, to be edited by
Michel Dumontier and Paul Groth. Submissions are due by June 1st, 2019.

*Topic of the Special Issue*
The FAIR principles (https://www.go-fair.org/fair-principles/) outline key
attributes to make digital resources more Findable, Accessible,
Interoperable, and Reusable. Globally endorsed and widely adopted, there is
now a pressing need to enable the establishment of an Internet of FAIR Data
and Services, to demonstrate how these can be used to generate new
insights, and to assess the overall value proposition for FAIR across
different sectors (health, finance, law, etc). Realizing the value of the
FAIR principles will require a combination of scientific, technical,
social, legal, and ethical advances for the production, sharing, discovery,
assessment, and reuse of data.

The aim of this special issue is to highlight unique contributions towards
the development and assessment of FAIR data, systems, and analysis. Topics
of submissions include, but are not limited to:
 - systems to automatically create FAIR data and services
 - methods to automatically capture detailed provenance and other metadata
 - development and maintenance of FAIR knowledge graphs
 - FAIR support tools, repositories and resources
 - methods, tools and systems for computing and using FAIR assessments
 - computable licenses and terms of use
 - novel analytics for FAIR data
 - distributed systems to share and mine sensitive data in a privacy
preserving manner
 - legal and ethical contributions related to FAIR data and systems
 - contributions to assess the economic value and benefits of FAIR

Special Issue Editors
Dr. Michel Dumontier is the Distinguished Professor of Data Science at
Maastricht University, the Founder and Director of the interfaculty
Institute of Data Science, and the co-Founder of the FAIR (Findable,
Accessible, Interoperable and Reusable) principles. His research aims to
create tools and infrastructure that facilitate the automated discovery and
reuse of digital content in a scalable and responsible manner. He is
editor-in-chief for the journal Data Science.

Dr. Paul Groth is Professor of Algorithmic Data Science at the University
of Amsterdam’s Informatics Institute where he leads the Intelligent Data
Engineering Lab (INDElab). His research focuses on intelligent systems for
dealing with large amounts of diverse contextualized knowledge with a
particular focus on web and science applications. This includes research in
data provenance, data integration and knowledge sharing. Paul was co-chair
of the W3C Provenance Working Group that created a standard for provenance
interchange. He has also contributed to the emergence of community
initiatives to build a better scholarly ecosystem including altmetrics and
the FAIR data principles.

*Important Dates*
Submission deadline: June 1st, 2019
Author notification: July 15th, 2019
Final version: September 1st, 2019
Publication: October 15th, 2019

*Submitting a Paper*
Submissions should comply with the guidelines for authors as outlined at
https://datasciencehub.net/content/guidelines-authors

For submitting please go to
https://datasciencehub.net/content/submit-manuscript


*Information About the Data Science Journal*
Please note that all submitted papers to the special issue will be made
openly available on the journal website as pre-prints before the reviewing
starts, so reviewers and everybody else will be free to not only read but
also share submitted papers. Pre-prints will remain available after
reviewing, independent of whether the paper will be accepted or rejected
for publication. Reviews to the papers are non-anonymous by default (but
reviewers can request to stay anonymous). All reviews are made openly
available under CC-BY licenses after a decision has been made on the
submission (independent of whether the decision was accept or reject). In
addition to solicited reviews, everybody is welcome to submit additional
reviews and comments for papers that are under review. Editors and
non-anonymous reviewers will be mentioned in the published articles. All
accepted articles will be published in the official publisher version of
the journal with Open Access. The Article Publication Fees (APC's) for this
special issue are waived so there is no payment required to publish a paper
in this special issue. Please consult https://datasciencehub.net for more
detailed information about the journal.


-- 
Michel Dumontier
Distinguished Professor of Data Science
Maastricht University
http://dumontierlab.com

-- 
Michel Dumontier
Distinguished Professor of Data Science
Maastricht University
http://dumontierlab.com
Received on Tuesday, 19 March 2019 08:39:06 UTC

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