-------- Original Message -------- Subject: [AISWorld] CALL FOR BOOK CHAPTER PROPOSALS: Information Quality and Governance for Business Intelligence Date: Mon, 22 Oct 2012 09:02:19 +0000 From: William Yeoh william.yeoh@deakin.edu.au To: aisworld@lists.aisnet.org aisworld@lists.aisnet.org
*CALL FOR BOOK CHAPTER PROPOSALS*
*Proposal Submission Deadline: October 31, 2012*
*/Information Quality and Governance for Business Intelligence/*
A book edited by
Dr. John Talburt (University of Arkansas at Little Rock, USA)
Dr. William Yeoh (Deakin University, Australia)
Dr. Yinle Zhou (IBM Corporation, USA)
To be published by IGI Global: http://www.igi-global.com/publish/call-for-papers/call-details/832
*Introduction*
Although Business Intelligence (BI) applications have been dominating the technology priority list of many organizations, these efforts often fail to accomplish their objectives. In many cases the reason for the failure is directly attributable to the poor quality of the underlying information. Achieving and sustaining high-levels of information and data quality draws on knowledge and skills across a number of disciplines such as quality management, information technology, project management, and change management. At the same time a typical business intelligence initiative has to address a growing number of data and information quality conundrums including cross-functional information integration of data from disparate sources, the emergence of "big data" with its increasing volume, velocity, and variety, and the lack of effective information quality and governance strategies and policies.
Information quality (IQ) is a body of knowledge and practice around realizing the maximum value from an organization's information assets by assuring that the information products produced from that information will meet the expectations of ("are fit for use by") the people and the system using them. Of these information products, perhaps none are more critical than Business intelligence (BI) applications. BI applications must deliver the right information, in the right format, to the right people at the right time for more informed decision making. The quality of BI output is directly related to the quality of the input data. Successful information quality and governance programs are fundamental to the success of any business intelligence initiative, especially those at the enterprise level. Unfortunately the information quality and governance capabilities in many organizations are not up to the levels needed to support their BI applications. Therefore, the goal of this book is to provide a collection of research papers and case studies that provide a road map to the best practices for information quality and governance to support business intelligence applications.
*Objective of the Book*
The mission of this book is to advance research and practice in the field of business intelligence and information quality. The book is a peer-reviewed publication dedicated to the exchange of the latest academic research on all aspects of practicing and managing information quality and governance for business intelligence in organizations. The book will publish original research and case studies by academic, business, and government contributors on strategies, practices, techniques, and technologies that advance the understanding and practice of information quality in support of business intelligence. This book takes a multidisciplinary approach to the examination of information quality for business intelligence.
*Target Audience*
The prospective audience of the book can be:
·Researchers interested in business intelligence and data/information quality;
·Business intelligence and information quality practitioners; and
·University students specialising in business intelligence, information quality or information systems.
*Recommended topics*
This book will focus on the interplay of data quality/information quality (DQ/IQ) and business intelligence (BI). Within the context of business intelligence, suggested topics include, but are not limited to:
. Alignment of DQ/IQ with BI strategies
. Applications of data quality/cleansing tools
. Business process modeling in BI context
. Case studies of DQ/IQ practices
. Cost/Benefit analysis of DQ/IQ improvement
. Critical assessments of data quality/cleansing solutions
. Data governance and stewardship
. Data integrity and sustainability
. Data profiling and enrichment
. Data scrubbing and cleaning
. Design, implementation, and assessment of innovative DQ/IQ systems
. Development of DQ/IQ-oriented architectures for BI
. DQ frameworks and governance for BI
. DQ/ IQ training and education
. DQ/IQ assessment, policies, and standards
. DQ/IQ concepts, metrics, measures, and models
. DQ/IQ for unstructured data
. DQ/IQ metrics and their effectiveness
. Drivers and barriers to achieving DQ/IQ
. Effective measurement of DQ/IQ for BI
. Impacts of DQ/IQ to BI
. Information product theory and practice
. Managing people and change processes associated with DQ/IQ
. Metadata and Master data management
. Organisational culture and its impact on DQ/IQ
. Privacy and security issues in data cleansing
. Record linkage and entity resolution
. Slowly-changed dimensions
. Taxonomy of DQ/IQ problems and solutions
. Technical and business metadata of BI
. The relationship between DQ/IQ and BI
//
Submission Procedure
Researchers and practitioners are invited to submit /on or before *October 31, 2012*/, a 1 - 2 page chapter proposal clearly explaining the mission and concerns of his or her proposed chapter. Authors of accepted proposals will be notified by */December 30, 2012/* about the status of their proposals and sent chapter guidelines. Full chapters are expected to be submitted by */February 28, 2013/*. All submitted chapters will be reviewed on a double-blind review basis, and/*contributors must be willing to serve as reviewers for submissions by other authors participating in this project*/.
*Publisher*
This book is scheduled to be published by IGI Global (formerly Idea Group Inc.), publisher of the "Information Science Reference" (formerly Idea Group Reference), "Medical Information Science Reference," "Business Science Reference," and "Engineering Science Reference" imprints. For additional information regarding the publisher, please visit www.igi-global.com http://www.igi-global.com/. This publication is anticipated to be released in 2013.
*Important Dates*
*October 31, 2012: *Proposal Submission Deadline**
*December 30, 2012: *Notification of Acceptance**
*February 28, 2013: *Full Chapter Submission**
*April 30, 2013 : *Review Results Returned**
*May 30, 2013: *Final Chapter Submission**
*June 15, 2013: *Final Acceptance Notification
**
*Editorial Advisory Board Members:*
Dr. Barbara Dinter, University of St. Gallen
Dr. Greg Richards, University of Ottawa
Dr. Latif Al-Hakim, University of Southern Queensland
Dr. Markus Helfert, Dublin City University
Dr. Neal Gibson, Arkansas Research Center
Dr. Neil Foshay, St. Francis Xavier University
Dr. Peter Aiken, Virginia Commonwealth University
Dr. Roger Blake, University of Massachusetts Boston
Dr. Shazia Sadiq, The University of Queensland
Dr. Te-Wei Wang, University of Illinois at Springfield
Dr. Thomas Redman, Navesink Consulting Group
Dr. Ying Su, Institute of Scientific and Technical Information of China
//
/Inquiries and submissions can be forwarded electronically (Word document) to:/
Dr. William Yeoh
Deakin University, Australia
E-mail: william.yeoh@deakin.edu.au mailto:william.yeoh@deakin.edu.au
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