[Dbworld] Second Call for Papers DSMM 2017 with SIGMOD 2017

			SECOND CALL FOR PAPERS	
			
           Workshop on Data Science for Macro-Modeling DSMM2017 
		    	    dsmmworkshop.org 
		Held in conjunction with ACM SIGMOD 2017

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The SIGMOD Executive Committee decided to move SIGMOD / PODS 2017 to a
different location.  http://wp.sigmod.org/?p=2079 for more details.
DSMM 2017 will continue to be held with SIGMOD 2017 (new date and 
location to be announced soon).  

*** NEW DEADLINES ***
Submission deadline:            Friday March 3, 2017 (old February 24, 2017)
Notification to authors:        Sunday March 26, 2017
Camera-ready due:               Friday April 14, 2017
 
DSMM 2017 will explore the challenges of macro-modeling with financial and/or 
economic datasets. The workshop will also showcase the Financial Entity 
Identification and Information Integration (FEIII) Challenge.
ir.nist.gov/dsfin

Two trends are providing data-rich opportunities for macro-modeling of financial 
and economic ecosystems. First, public financial data is becoming increasingly 
available from a variety of sources, including WRDS's CRSP, SEC EDGAR, and 
the Federal Reserve's FRED. Economists have used longitudinal datasets (US Census 
Bureau, Department of Labor, World Bank, etc.).  The advent of Big Data infrastructures 
and analytical tools can support the required integration across these data sources, 
as well as macro-modeling with diverse datasets, and can potentially lead to the 
exploration of complex financial and economic ecosystems.  Although integrating datasets 
may pose technical and policy/privacy challenges, the potential benefits are immense. 
For example, social media data often contains features that could enhance macroeconomic 
statistics derived from traditional survey-driven datasets. The resulting enriched 
datasets could explore hypotheses with a different focus or level of granularity. 

The financial world is a closely interlinked Web of financial entities and 
networks where multiple financial entities may be counterparties to a complex 
financial contract.  Financial analysts, regulators and academic researchers 
recognize that they must address the unprecedented and unfamiliar challenges of 
monitoring, integrating, and analyzing data at scale. The benefits of addressing 
these challenges are immense and may result in improved tools for regulators to 
monitor financial systems or to set economic or fiscal policy. Additional benefits 
may include fundamentally new designs of market mechanisms, new ways to reach 
consumers, and new ways to exploit the wisdom of the crowds.

The FEIII Challenge is sponsored by the Office of Financial Research and the 
National Institutes of Standards and Technology and is modeled after the successful 
TREC series. The Year One challenge in 2016 was a record linkage challenge. 
The Year Two challenge will be a ranking of triples, i.e., sentences extracted
from SEC filings that describe the "role" played by a "mentioned" financial entity.
Challenge participants will be invited to share their insights in a special session.
ir.nist.gov/dsfin
  
We expect attendees with an interest in information integration, data mining, 
knowledge representation, network and visual analytics, stream data processing, etc. 
The DSMM 2014 workshop, in conjunction with SIGMOD 2016, attracted a diverse group 
of researchers from databases, data modeling, finance, math/stat and economics. 
Proceedings of ACM DSMM 2016 are available here:  
http://dl.acm.org/citation.cfm?id=2951894

SUBMISSION FORMAT
We will accept the following types of papers in the SIGMOD format:
* Regular papers that are a maximum of 6 pages will have a presentation slot.
* Extended abstracts of up to 2 pages will have a poster presentation and a
  short presentation slot if time permits.

PROGRAM CHAIRS
Doug Burdick		IBM Research		   drburdic-r/[email protected]
Rajasekar Krishnamurthy IBM Research               rajase-r/[email protected]
Louiqa Raschid          University of Maryland     [email protected]

STEERING COMMITTEE 
Laura Haas		IBM Research 		   lmhaas-r/[email protected]
H.V. Jagadish	 	University of Michigan	   [email protected]
Shiv Vaithyanathan	IBM Research		   vaithyan-r/[email protected]

PROGRAM COMMITTEE

Elena Baralis		Politecnico di Torino	   	[email protected]
Don Berndt		University of South Florida	[email protected]
Jefferson Braswell	Tahoe Blue			[email protected]
Sanjiv Das 	   	Santa Clara University     	[email protected]
Amol Deshpande	        University of Maryland     	[email protected]
Mark Flood		Office Financial Research  	[email protected]
Mark Dredze		John Hopkins University		mdredze-vD/[email protected]
Gerard Hoberg		USC 			   	[email protected]
Juliana Freire		New York University		juliana.freire-RWB/[email protected]
Vasant Honavar		Pennsylvania State University  	[email protected]
Joe Langsam		University of Maryland	   	[email protected]
Shawn Mankad            University of Maryland     	[email protected]          
Felix Naumann		University of Potsdam		[email protected]
Frank Olken						[email protected]
Kevin Sheppard		Office Financial Research  	[email protected]
Ian Soboroff		NIST			   	ian.soboroff-R3+/[email protected]
Roger Stein		CSRA and MIT		   	[email protected]
Jian Wu			Pennsylvania State University	[email protected]
Kunpeng Zhang		University of Maryland	   	[email protected]


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