ACM Journal of Data
and Information Quality NEW
Saturday November 11th, 11:00 am ET
The new web site for the journal is at: http://www.acm.org/pubs/periodicals/jdiq/
The ACM JDIQ welcomes research contributions on the following areas, but not limited to:
· Information Quality in the Enterprise Context, including
o The impact and role of information quality on business, work process and strategy
o The impact and role on a firm's overall operational or economic performance, cost and benefits, IT management, human resource management
o Impact on knowledge management, customer management, supply-chain management, extended-enterprise management, and global management.
o Impact and role of information quality on groups, organizations, and society.
· Database related technical solutions for information quality, including
o New types of database systems that manage data, uncertainty (approximate, probabilistic, inexact, incomplete, imprecise, fuzzy, inaccurate, data)
o Data lineage and provenance
o Data cleaning
o Entity management, entity resolution, and record linking
o Data Integration Processes
· Information Quality in the Context of Computer Science and Information Technology
o New ways of understanding, modeling, improving and incorporating information quality
o Technical solutions of information systems
o Technical layers of networks and communications
o Data Privacy and Protection mechanisms
· Information Curation, including
o Standards and policies for ensuring information integrity for future generations
JDIQ plans to accept research conducted using various types of methods ranging from positivists to interpretive methods, systems building descriptions, and database theory, including statistical analysis, mathematical modeling, quasi experimental method, hermeneutics, action research, and case study. JDIQ will accept diverse research methods that are customary in different research backgrounds and traditions, both quantitative and qualitative.
Research papers need to demonstrate the use of a rigorous method or methods. Research papers also need to provide valuable and relevant implications for applying their findings and solutions in practice.
JDIQ plans to publish high quality articles that make a significant novel contribution to the field of data and information quality. JDIQ will be a peer reviewed journal employing double blind review mechanism. JDIQ will be a print publication and will aim for the same online capabilities as that of other ACM journals. Full papers in JDIQ will be research papers, in addition there are plans to include one or two short concise papers in each issue. It is expected that the journal will be published quarterly.
Authors for JDIQ submissions are invited from the entire data and information quality community, which spans multiple industries as well as the Computer Science, Information Systems, Operations Research, Bioinformatics, Healthcare, Management, and other disciplines. ACM members are certainly one pool from which authors will come. However, the information quality community is bigger than ACM. The number of conferences, websites, and books either devoted to information quality or with close ties to data quality issues is growing, attesting to the vitality, size, and interest in this area.
Sample articles published in other journals during the past ten years can be found at http://web.mit.edu/smadnick/www/JDIQ/Sample%20Articles.htm
· Advertising and Call for Papers – Spring 2007
· First Issue Appears – 2008
The pricing structure for subscription will be consistent with other ACM journals. We expect an annual subscription fee of around US$50 for ACM Members.
Editor-in-Chief-MIS: Yang Lee, Northeastern University
Editor-in-Chief-CS: Stuart Madnick, Massachusetts Institute of Technology
Managing Director: Elizabeth
Queen's University (
Michael Franklin, U.C. Berkeley (
Maurizio Lenzerini, U. Roma "La Sapienza" (Italy)
Felix Naumann, Hasso-Plattner-Institut (Germany)
Barbara Pernici, Politecnico di Milano (Italy)
Leo Pipino, U Mass,
Mary Ann Robbert,
Arie Segev, U.C. Berkeley (USA)
Giri Kumar Tayi, SUNY,
Northeastern University (
Richard Wang, Massachusetts Institute of Technology (