It is possible to design cooperative work tools based only on "common sense " and good intuitions. But the history of technology is replete with examples of good theories greatly aiding the development of useful technology. Where, then, might we look for theories to help us design computer-supported cooperative work tools? In this paper, we will describe one possible perspective-the interdisciplinary study of coordination-that focuses, in part, on how people work together now and how they might do so differently with new information technologies. In one sense, there is little that is new about the study of coordination. Many different disciplines--including computer science, sociology, political science, management science, systems theory, economics, linguistics, and psychology--have all dealt, in one way or another, with fundamental questions about coordination. Furthermore, several previous writers have suggested that theories about coordination are likely to be important for designing cooperative work tools (e.g., Holt8], (Wino86]). We hope to suggest here, however, that the potential for fruitful interdisciplinary connections concerning coordination is much greater than has as yet been widely

Abstiuct-Organizational databases are pervaded with data of poor quality. However, there has not been an analysis of the data quality literature that provides an overall understanding of the state-of-art research in this area. Using an analogy between product manufacturing and data manufacturing, this paper de-velops a framework for analyzing data quality research, and uses it as the basis for organizing the data quality literature. This framework consists of seven elements: management responsibili-ties, operation and assurance costs, research and development, production, distribution, personnel management, and legal func-tion. The analysis reveals that most research efforts focus on op-eration and assurance costs, research and development, and pro-duction of data products. Unexplored research topics and unre-solved issues are identified and directions for future research provided. Index Terms-Data quality, data manufacturing, data product,

Travel time forecasting models have been studied intensively as a subject of Intelligent Transportation Systems (ITS), particularly in the topics of advanced traffic management systems (ATMS) and advanced traveler information systems (ATIS). Now, the interests for the travel time forecasting models have been revived, particularly since the market for location-based services (LBS) are foreseen to be rapidly increasing. While the concept of travel time forecasting is relatively simple, it involves a notably complicated task to implement even a simple model. Thus, existing forecasting models are diverse in their original formulations, including mathematical optimizations, computer simulations, statistics, and artificial intelligence. A comprehensive literature review, therefore, would assist in formulating a more reliable travel time forecasting model. On the other hand, geographic information systems (GIS) technologies primarily provide the capability of spatial and network database management, as well as technology management. Thus, GIS could support travel time forecasting in various ways by providing useful functions to both the managers in transportation management and information centers (TMICs) and private sector