Tand he term ���data quality��� can best be defined as ���fitness for use,��� which implies the concept of data quality is rel- ative. Thus data with quality considered appropriate for one use may not possess sufficient quality for another use. The trend toward multiple uses of data, exemplified by the popularity of data warehouses, has highlighted the need to address data quality concerns. Furthermore, fitness for use implies that one needs to look beyond traditional concerns with the accuracy of the data. Data found in accounting-type systems may be accurate but unfit for use if that data is not sufficiently timely. Also, personnel databases situated in different divisions of a company may be correct but unfit for use if the desire is to combine the two and they have incompatible formats. A related problem with multiple users of data is that of semantics. The data gatherer and initial user may be fully aware of the nuances regarding the meaning of the various data items, but that will not be true for all of the other users. Thus, although the value may be correct, it can easily be misinterpreted. Also, the capability of judging the reasonableness of the data is lost when users have no responsibility for the data���s integrity and when they are removed from the gatherers. Such problems are becoming increas- ingly critical as organizations implement data ware- houses. Another trend that explains the heightened aware- 54 February 1998/Vol. 41, No. 2 COMMUNICATIONS OF THE ACM Ensuring the quality of the data resource has been a continuing concern to those in the information systems profession. Over time techniques and procedures have evolved designed to make sure the data required by traditional transaction processing systems possesses an appropriate level of quality. However, the use of legacy data in, for example, decision and executive support systems has refocused attention on data quality and has exposed problems such as the need for ���soft��� data not encountered in traditional systems. Furthermore, data is now viewed as a key organizational resource should be managed accordingly. Giri Kumar Tayi and Donald P. Ballou, Guest Editors QualityDataExamining PAUL WATSON

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