[AISWorld] 1st Call for Papers: ECIS 2013 Track "Data Governance and Data Quality Management"

[Boris Otto]

1st CALL FOR PAPERS

21st European Conference on Information Systems (ECIS 2013)
June 5-8, 2013, at Utrecht University

Track: Data Governance and Data Quality Management

Deadline for paper submissions is December 7, 2012.

DESCRIPTION

At present a number of economic, technological, and societal developments 
can be observed which, among other things, lead to a “renaissance of 
data”. One example is the rise of business data service providers such as 
Factual and InfoChimps who build novel business models upon community and 
crowd sourcing approaches to make data available to enterprises. A second 
example is the increasing volumes of structured and unstructured data 
enterprises have to make sense of. The BBC has reported on the current 
global data storage capacity, which exceeded 295 Exabyte in 2007, and a 58 
percent combined annual growth rate of computing capacity over the last 
two decades. In early 2010, Apple sold the ten-billionth song over its 
iTunes platform. Third, the capability to manage data and data quality 
efficiently and effectively becomes business-critical as the number of 
legal and regulatory provisions keeps increasing. The European directive 
REACH requires manufacturers of chemical products to be able to report 
accurate, complete, consistent, and up-to-date data on ingredients and 
implications of their products and refuses access to the market if these 
requirements are not met (“no data, no market”). Enterprises need guidance 
and support to take the opportunities and mitigate the risks related to 
this contemporary phenomenon which analyst company Gartner refers to as 
the “data economy”.

Data Governance and Data Quality Management are considered key 
presuppositions for enterprises in this endeavor. Data Quality Management 
is an enterprise function aiming at optimizing data quality by using 
methods and approaches for defining, measuring, analyzing, improving, and 
controlling data quality. Data Governance is a framework of 
decision-making rights and responsibilities regarding the management and 
use of data, aiming at optimizing the value of data.

Recently, scholars identified a number of important research directions 
for Data Governance and Data Quality Management. Some researchers 
stipulate researching data quality aspects in new ways to deliver and 
provide data to the end-user (e.g. linked data or distributed 
architectures) and to take a broader perspective at societal or group 
level (e.g. elderly people), for example. And others suggest Data 
Governance research to take a business networking view.

TOPICS OF INTEREST

·       Business models built on the concept of data quality
·       Case studies on Data Governance and Data Quality Management
·       Comprehensive societal, technological, and economic perspectives 
on data quality
·       Data Governance and Data Quality Management as organizational 
capabilities
·       Data quality in “big data” environments
·       Data quality in specific data domains (e.g. social media, 
multimedia, geographical information)
·       Data quality in supply chains, in healthcare, e-government etc.
·       Data quality in the Cloud
·       Data quality metrics and their role for Data Governance
·       Data ownership and data stewardship
·       Design and evolution of Data Governance arrangements
·       Design-oriented approaches to Data Governance and Data Quality 
Management
·       Economic value of data quality
·       Enterprise and master data management
·       Maturity of Data Governance arrangements and Data Quality 
Management capabilities in enterprises
·       Metadata management and its role for Data Governance
·       Operational and analytical viewpoints on Data Governance and Data 
Quality Management
·       Theoretical foundations for establishing Data Governance and Data 
Quality Management in enterprises

TRACK CHAIRS

Boris Otto, University of St. Gallen, Switzerland, Boris.Otto at unisg.ch
Andy Koronios, University of South Australia, Australia, 
andy.koronios at unisa.edu.au
Bernd Heinrich, University of Regensburg, Germany, 
Bernd.Heinrich at wiwi.uni-regensburg.de
Mathias Klier, University of Regensburg, Germany, 
Mathias.Klier at wiwi.uni-regensburg.de

ASSOCIATE EDITORS

Roger Blake, University of Massachusetts Boston, USA
Ismael Caballero, Universidad de Castilla-La Mancha, Spain
Cinzia Cappiello, Politecnico di Milano, Italy
Barbara Dinter, University of St. Gallen, Switzerland
Adir Even, Ben-Gurion University of the Negev, Israel
Martin Gaedcke, Chemnitz University of Technology, Germany
Barbara Klein, University of Michigan at Dearborn, USA
Yang W. Lee, Northeastern University, USA
Susanne Leist, University of Regensburg, Germany
Zoltan Miklos, École Polytechnique Fédérale de Lausanne, Switzerland
Leo L. Pipino, University of Massachusetts, USA
Shazia Sadiq, The University of Queensland, Australia
Guido Schryen, University of Regensburg, Germany
Ganesan Shankaranarayanan, Babson College, USA
Rolf T. Wigand, University of Arkansas at Little Rock, USA
Harry Zhu, Old Dominion University, USA

Yours

Boris Otto



Boris Otto
PD Dr.-Ing.; Assistant Professor
Institute of Information Management | University of St. Gallen
Müller-Friedberg-Strasse 8 | 9000 St. Gallen
Phone: +41-71-224-3220
Mail: Boris.Otto at unisg.ch | IWI-HSG
About me: http://www.alexandria.unisg.ch/Personen/Boris_Otto
CC Corporate Data Quality





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