Fwd: IBM Journal of R&D - Special Issue on "Data Science for Social Good"
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Patrick Meier
Jul 18, 2016, 7:08:26 PM7/18/16
to Cliff Pickover, DS4-Soc...@googlegroups.com
Many thanks, Cliff, really appreciate it. Am sharing this with the Data Science for Social Good email-list (~150 members).
Thanks again,
---------- Forwarded message ----------
From: Cliff Pickover <cli...@us.ibm.com>
Date: Mon, Jul 18, 2016 at 11:23 AM
Subject: IBM Journal of R&D - Special Issue on "Data Science for Social Good"
To: pat...@irevolution.net
From: Cliff Pickover <cli...@us.ibm.com>
Date: Mon, Jul 18, 2016 at 11:23 AM
Subject: IBM Journal of R&D - Special Issue on "Data Science for Social Good"
To: pat...@irevolution.net
Patrick, I thought you may be interested
in this. Feel free to spread the word....
(Also, if you have ideas for people you'd like me to personally invite from any organization, I'd be happy to do so....)
Date: September 7, 2016: Preliminary Abstracts Due
Overview
Unprecedented growth of digital information provides special opportunities to change the world for the better using analytics, including projects ranging from reducing or eliminating inequalities, and improving access to health care and education, to reducing pollution and our carbon footprint.
Certain industries and sectors have taken advantage of the big data era and reaped the benefits through descriptive, predictive, and prescriptive analytics. However, some organizations and agencies in the social and public sectors, despite facing challenges that are very important for humanity, are not yet utilizing advanced analytics as much as they could, even though they are leaders in open data initiatives and have a heritage of quantitative and qualitative analysis. The movement involving data science for social good is attempting to improve this situation.
This special issue of the IBM Journal of Research and Development will emphasize new solutions, models, capabilities, and technologies that focus on addressing humanitarian challenges. We solicit Abstracts (paper proposals) on research that, among other approaches, makes use of machine learning, data mining, and data science for the purpose of social good. Broadly construed, this may include analytics-driven applications for social good or new methods or theories of particular interest for social good applications.
Potential Focus Areas for Papers
· Innovative applications of data science to humanitarian problems such as hunger, poverty, injustice, emerging diseases, inequalities in society, access to health care, access to clean energy, lack of civic engagement, and sustainability of the environment
· Case studies highlighting interdisciplinary collaborations between data scientists and NGOs, social enterprises, or public-sector agencies
· Algorithmic advances, new platforms and architectures that arise from the unique nature of problems in the social sector
IBM Journal Manuscript Preparation Guidelines
The Journal is peer reviewed -- all papers will be sent to several experts to be reviewed before a final publication decision is made. All papers must place the described research and results in perspective by carefully citing relevant related scientific work. Contact Cliff Pickover (cli...@us.ibm.com), or visit the journal web site, for the manuscript preparation template:
http://www.research.ibm.com/journal/rdauth.html
Contact Information
Guest editors for the issue are Aleksandra Mojsilović and Kush Varshney. Authors should indicate their interest in submitting a paper by sending a preliminary abstract to Aleksandra Mojsilović (alek...@us.ibm.com) and journal Editor-in-Chief Cliff Pickover (cli...@us.ibm.com) -- by September 7, 2016. You must submit an abstract to be consideredfor this issue, and we will notify you when your abstract is accepted.
Important Deadlines and Schedule
· September 7, 2016: Preliminary Abstracts Due(tentative article title, author names/affiliations, 1 paragraph description)
· January 7, 2017: Final Paper Draft Due (if your abstract is accepted)
· November, 2017: Special Issue Published (every paper will be on-line by this date)
Regards, Cliff
------------------
Cliff Pickover, Ph.D., IBM Master Inventor & Council for Innovation Leadership
Editor-in-Chief, IBM Journal of R&D, Watson Research Center
IBM Journal: http://www.research.ibm.com/journal/
Personal: http://www.pickover.com Twitter: @pickover
(Also, if you have ideas for people you'd like me to personally invite from any organization, I'd be happy to do so....)
Date: September 7, 2016: Preliminary Abstracts Due
Call for
Papers
IBM Journal of Research and Development
Special Issue on "Data Science for Social Good"
IBM Journal of Research and Development
Special Issue on "Data Science for Social Good"
Overview
Unprecedented growth of digital information provides special opportunities to change the world for the better using analytics, including projects ranging from reducing or eliminating inequalities, and improving access to health care and education, to reducing pollution and our carbon footprint.
Certain industries and sectors have taken advantage of the big data era and reaped the benefits through descriptive, predictive, and prescriptive analytics. However, some organizations and agencies in the social and public sectors, despite facing challenges that are very important for humanity, are not yet utilizing advanced analytics as much as they could, even though they are leaders in open data initiatives and have a heritage of quantitative and qualitative analysis. The movement involving data science for social good is attempting to improve this situation.
This special issue of the IBM Journal of Research and Development will emphasize new solutions, models, capabilities, and technologies that focus on addressing humanitarian challenges. We solicit Abstracts (paper proposals) on research that, among other approaches, makes use of machine learning, data mining, and data science for the purpose of social good. Broadly construed, this may include analytics-driven applications for social good or new methods or theories of particular interest for social good applications.
Potential Focus Areas for Papers
· Innovative applications of data science to humanitarian problems such as hunger, poverty, injustice, emerging diseases, inequalities in society, access to health care, access to clean energy, lack of civic engagement, and sustainability of the environment
· Case studies highlighting interdisciplinary collaborations between data scientists and NGOs, social enterprises, or public-sector agencies
· Algorithmic advances, new platforms and architectures that arise from the unique nature of problems in the social sector
IBM Journal Manuscript Preparation Guidelines
The Journal is peer reviewed -- all papers will be sent to several experts to be reviewed before a final publication decision is made. All papers must place the described research and results in perspective by carefully citing relevant related scientific work. Contact Cliff Pickover (cli...@us.ibm.com), or visit the journal web site, for the manuscript preparation template:
http://www.research.ibm.com/journal/rdauth.html
Contact Information
Guest editors for the issue are Aleksandra Mojsilović and Kush Varshney. Authors should indicate their interest in submitting a paper by sending a preliminary abstract to Aleksandra Mojsilović (alek...@us.ibm.com) and journal Editor-in-Chief Cliff Pickover (cli...@us.ibm.com) -- by September 7, 2016. You must submit an abstract to be consideredfor this issue, and we will notify you when your abstract is accepted.
Important Deadlines and Schedule
· September 7, 2016: Preliminary Abstracts Due(tentative article title, author names/affiliations, 1 paragraph description)
· January 7, 2017: Final Paper Draft Due (if your abstract is accepted)
· November, 2017: Special Issue Published (every paper will be on-line by this date)
Regards, Cliff
------------------
Cliff Pickover, Ph.D., IBM Master Inventor & Council for Innovation Leadership
Editor-in-Chief, IBM Journal of R&D, Watson Research Center
IBM Journal: http://www.research.ibm.com/journal/
Personal: http://www.pickover.com Twitter: @pickover
johnbri...@gmail.com
May 24, 2018, 4:37:38 AM5/24/18
to Data Science for Social Good
Data science is the study of where information comes from, what it represents and how it can be turned into a valuable resource in the creation of business and IT strategies. Mining large amounts of structured and unstructured data to identify patterns can help an organization rein in costs, increase efficiencies, recognize new market opportunities and increase the organization's competitive advantage.
The main advantage of enlisting data science in an organization is the empowerment and facilitation of decision-making. Organizations with data scientists can factor in quantifiable, data-based evidence into their business decisions.
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