[Air-L] The Data Economy workshop: how online data change economy and business, Thessaloniki Greece 22/11/2017

michail vafopoulos vafopoulos at gmail.com
Fri Jul 21 05:14:15 PDT 2017


Dear AoIR list members,

the organisers of the Data Economy workshop (to be held at the Internet
Science Conference 2017) kindly invite you to submit research full
papers (10-20 pages) presenting new results and short papers (6-9 pages)
with disruptive ideas and work-in-progress, shedding light on how online
data change economy and business. Accepted papers will appear in a
post-conference proceedings volume to be published by LNCS Springer.
Submitted papers should follow the INSCI Paper Submission Guidelines.

Important Dates
Deadline of paper submission: 20/8/2017, 15:00 CET
Notification of Acceptance: 20/9/2017
Workshop: 22/11/2017

Description
Big data, data analytics, personal data, open data, linked data,
metadata, data journalism, data science, data infrastructures….and still
you can add a new “data” phrase!
Data has become a buzzword used in a number of disciplines, by technical
and business communities. At the same time, the growing interaction
among corporate, governmental and personal information spaces introduces
a novel set of opportunities and challenges for the economy.
The DATA ECONOMY workshop will try to engage scholars and professionals
from multiple disciplines including economics, management, open
governance, data science, computer science and software engineering in
discussions related to how digital data, scattered in decentralised
information systems and applications and being accessible via the Web,
change the economy and the ways we are doing business.
Possible topics for discussion (but not limited to):

●	Economic theory and practice related to online data and the Web
●	Data infrastructures (and open standards) for the economy (e.g. open
banking standard)
●	Data and information strategies and policies
●	Open data as a tool in economic policy
●	Open data for business and economic development
●	Financial data transparency (e.g. open ownership, open budgets)
●	Business practices and the economic impact of GAFA
●	Business intelligence and data analytics
●	Business models and value creation in data-oriented environments
●	Data and content based e-commerce
●	The role of data in the Digital Single Market in Europe
●	Open Scientific Data and the European Open Science Cloud
●	Computational economy and big data in finance
●	Big data in operational research, business intelligence and economic
analysis
●	Personal data and Personal Information Management systems (PIMS):
markets, business models and consumer behaviour
●	Economic implications of data transparency and algorithmic (or AI)
accountability
●	Social media analytics: business models and economic impact
●	Measuring the data economy (e.g. open data indices, societal impact etc.)
●	Legal issues in the data economy
●	Security issues for data economy stakeholders (e.g. in security for
data centres, cloud infrastructure, user authentication etc.)
●	Privacy as a commodity and privacy-related aspects of monetising user data


Keynote speakers

Daniele Rizzi, EC DG Connect
Nikos Loutas, PwC

Organisers
Michalis Vafopoulos, Software & Knowledge Engineering Laboratory (SKEL)
of the National Center for Scientific Research «Demokritos»

Vangelis Karkaletsis, Software & Knowledge Engineering Laboratory (SKEL)
of the National Center for Scientific Research «Demokritos».

Vassilios Peristeras, Assοc. Professor, International Hellenic University.

Ioannis Anagnostopoulos, Assistant Professor, Department of Computer
Science and Biomedical Informatics, University of Thessaly.

Benjamin Heitmann, PhD, RWTH Aachen University, Germany.

Stefan Decker, Professor, Director of Fraunhofer Institute for Applied
Information Technology FIT, Germany.


-- 
Best regards,

============================
Michalis Vafopoulos
vafopoulos.org - +30 6945897894
Researcher, Software and Knowledge Engineering Laboratory,
National Center for Scientific Research “Demokritos”

Founder, Open Data Institute – Athens Node



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