SoGood 2017 - 2nd Workshop on Data Science for Social Good
Topics/Call fo Papers
Held in conjunction with ECML PKDD 2017 - the European Conference
on Machine Learning, Principles and Practice of Knowledge Discovery=20
,
Skopje, Macedonia, September 18th, 2017
*https://sites.google.com/site/ecmlpkddsogood2017/*
This is the second edition of the workshop; the first was held jointly
with ECML PKDD 2016.
*Scope:*
The possibilities of Data Science for contributing to social, common,
or public good are often not sufficiently perceived by the public at
large. Data science applications are already helping in serving people
at the bottom of the economic pyramid, aiding people with special needs,
helping international cooperation, or dealing with environmental problems,
disasters, and climate change.
In regular conferences and journals, papers on these topics are often
scattered among sessions with names that hide their common nature
(such as "Social networks", "Predictive models" or even under the
catch-all term "Applications"). Additionally, such forums tend to have
a strong bias for papers that are novel in the strictly technical sense
(new algorithms, new kinds of data analysis, new technologies)
rather than novel in terms of social impact of the application.
This workshops aims to attract papers presenting applications (which may,
or may not require new methods) of Data Science to Social Good, or else
that take into account social aspects of Data Science methods and=20
techniques.
Application domains should be as varied as possible. A non-exclusive list
includes:
* Public safety and disaster relief
* Access to food, water, and utilities
* Efficiency and sustainability
* Government transparency
* Data journalism
* Economic, social, and personal development
* Transportation
* Energy
* Smart city services
* Education
* Social services, unemployment and homelessness
* Healthcare
* Cybersafety (including cyberbullying, propaganda and radicalization, etc.=
)
* Ethical issues, fairness, and accountability
* In general, the UN development goals at
http://www.un.org/sustainabledevelopment/sustainab...
The novelty of the application and its social impact will be major
selection criteria. Additionally, "social good" projects are often
associated to the idea of non-profit; we are particularly interested
in applications that have built a viable business model, that is, while
not defined as "non-profit", still have social good as their main focus.
*Workshop format:*
This is a half-day workshop, comprising:
* Oral presentation of the accepted papers. Depending on the number,
they may range from 10 to 20 minutes each.
* A panel: The future of Data Science as a contributor to Social Good.
-Obstacles, opportunities, challenges, and controversial issues
(e.g., privacy, ethics, discrimination, etc.).
- How can the scientific community organize itself to contribute?
-Are we using Data Science to solve problems that really matter and=20
how to
encourage this?
-How can sustainable business models be created?
* Possibly, a poster session with the accepted papers and late arrivals.
*Paper submission:*
Authors should submit a PDF version in Springer LNCS style using the
workshop EasyChair site, accessible from the workshop site.
Papers are expected to be between 8 and 15 pages long, but there is no=20
hard limit
on paper length, within reason. Conditionally accepted papers may be=20
required to
address requirements from the PC for change, including length changes,=20
for the
camera-ready version.
Submitting a paper to the workshop means that if the paper is accepted=20
at least
one author commits to presenting it at the workshop. Papers not=20
presented at the
workshop will not be included in the proceedings.
*Paper publication:*
Proceedings will be published in the CEUR Workshop proceedings series=20
(http://ceur-ws.org/).
* Important Dates:*
* Submission deadline: Monday, July 3, 2017
* Acceptance notification : Monday, July 24, 2017
* Camera-ready deadline: Monday, August 8th, 2017
* Workshop: September 18th, 2017
*PC members:*
* Albert Bifet, Telecom ParisTech
* Carlos Castillo, Eurecat
* Michelangelo Ceci, U. degli Studi di Bari
* Nitesh Chawla, U. of Notre Dame
* Itziar de Lecuona, U. Barcelona
* Jeremiah Deng, U. of Otago
* Finale Doshi-Velez, Harvard U.
* Cesar Ferri, UPV Valencia
* Geoffrey Holmes, U. of Waikato
* Josep-Lluis Larriba, UPC BarcelonaTech
* Yann-Ael Le Borgne, U. Libre Bruxelles
* Alexandra Olteanu, IBM Research
* Carlos Soares, U. of Porto
* Alicia Troncoso, Pablo de Olavide U.
* Evgueni Smirnov, U. Maastricht
* Tong Wang, U. Iowa
*Organizers and contact:*
* Ricard Gavalda (UPC BarcelonaTech), gavalda-AT-cs.upc.edu
* Irena Koprinska (U. of Sydney), irena.koprinska-AT-sydney.edu.au
* Stefan Kramer (JGU Mainz), kramer-AT-informatik.uni-mainz.de
*Workshop site:*
https://sites.google.com/site/ecmlpkddsogood2017/
on Machine Learning, Principles and Practice of Knowledge Discovery=20
,
Skopje, Macedonia, September 18th, 2017
*https://sites.google.com/site/ecmlpkddsogood2017/*
This is the second edition of the workshop; the first was held jointly
with ECML PKDD 2016.
*Scope:*
The possibilities of Data Science for contributing to social, common,
or public good are often not sufficiently perceived by the public at
large. Data science applications are already helping in serving people
at the bottom of the economic pyramid, aiding people with special needs,
helping international cooperation, or dealing with environmental problems,
disasters, and climate change.
In regular conferences and journals, papers on these topics are often
scattered among sessions with names that hide their common nature
(such as "Social networks", "Predictive models" or even under the
catch-all term "Applications"). Additionally, such forums tend to have
a strong bias for papers that are novel in the strictly technical sense
(new algorithms, new kinds of data analysis, new technologies)
rather than novel in terms of social impact of the application.
This workshops aims to attract papers presenting applications (which may,
or may not require new methods) of Data Science to Social Good, or else
that take into account social aspects of Data Science methods and=20
techniques.
Application domains should be as varied as possible. A non-exclusive list
includes:
* Public safety and disaster relief
* Access to food, water, and utilities
* Efficiency and sustainability
* Government transparency
* Data journalism
* Economic, social, and personal development
* Transportation
* Energy
* Smart city services
* Education
* Social services, unemployment and homelessness
* Healthcare
* Cybersafety (including cyberbullying, propaganda and radicalization, etc.=
)
* Ethical issues, fairness, and accountability
* In general, the UN development goals at
http://www.un.org/sustainabledevelopment/sustainab...
The novelty of the application and its social impact will be major
selection criteria. Additionally, "social good" projects are often
associated to the idea of non-profit; we are particularly interested
in applications that have built a viable business model, that is, while
not defined as "non-profit", still have social good as their main focus.
*Workshop format:*
This is a half-day workshop, comprising:
* Oral presentation of the accepted papers. Depending on the number,
they may range from 10 to 20 minutes each.
* A panel: The future of Data Science as a contributor to Social Good.
-Obstacles, opportunities, challenges, and controversial issues
(e.g., privacy, ethics, discrimination, etc.).
- How can the scientific community organize itself to contribute?
-Are we using Data Science to solve problems that really matter and=20
how to
encourage this?
-How can sustainable business models be created?
* Possibly, a poster session with the accepted papers and late arrivals.
*Paper submission:*
Authors should submit a PDF version in Springer LNCS style using the
workshop EasyChair site, accessible from the workshop site.
Papers are expected to be between 8 and 15 pages long, but there is no=20
hard limit
on paper length, within reason. Conditionally accepted papers may be=20
required to
address requirements from the PC for change, including length changes,=20
for the
camera-ready version.
Submitting a paper to the workshop means that if the paper is accepted=20
at least
one author commits to presenting it at the workshop. Papers not=20
presented at the
workshop will not be included in the proceedings.
*Paper publication:*
Proceedings will be published in the CEUR Workshop proceedings series=20
(http://ceur-ws.org/).
* Important Dates:*
* Submission deadline: Monday, July 3, 2017
* Acceptance notification : Monday, July 24, 2017
* Camera-ready deadline: Monday, August 8th, 2017
* Workshop: September 18th, 2017
*PC members:*
* Albert Bifet, Telecom ParisTech
* Carlos Castillo, Eurecat
* Michelangelo Ceci, U. degli Studi di Bari
* Nitesh Chawla, U. of Notre Dame
* Itziar de Lecuona, U. Barcelona
* Jeremiah Deng, U. of Otago
* Finale Doshi-Velez, Harvard U.
* Cesar Ferri, UPV Valencia
* Geoffrey Holmes, U. of Waikato
* Josep-Lluis Larriba, UPC BarcelonaTech
* Yann-Ael Le Borgne, U. Libre Bruxelles
* Alexandra Olteanu, IBM Research
* Carlos Soares, U. of Porto
* Alicia Troncoso, Pablo de Olavide U.
* Evgueni Smirnov, U. Maastricht
* Tong Wang, U. Iowa
*Organizers and contact:*
* Ricard Gavalda (UPC BarcelonaTech), gavalda-AT-cs.upc.edu
* Irena Koprinska (U. of Sydney), irena.koprinska-AT-sydney.edu.au
* Stefan Kramer (JGU Mainz), kramer-AT-informatik.uni-mainz.de
*Workshop site:*
https://sites.google.com/site/ecmlpkddsogood2017/
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Last modified: 2017-06-06 23:20:43