The previous chapters of this book have described new advances in the constant effort to improve the quality of spatial data, and to make it possible for users of spatial data to understand the effects of data quality on their work. These results add to the already substantial literature on the topic, and it is clear that after two decades of work we now have a much better understanding of spat...

A variety of dependency formalisms have been studied for improving data quality. To treat these dependencies in a uniform framework, we propose a simple language, Quality Improving Dependencies (QIDs). We show that previous dependencies considered for data quality can be naturally expressed as QIDs, and that different enforcement mechanisms of QIDs yield various data repairing strategies.

Data warehousing has been touted to be the "solveall" for the decision making managers. This is an exaggeration, as the problem of lack of data quality in data is one of the fundamental obstacles in the current data warehousing environment. The erroneous data can significantly affect an organisation, not to mention the frustration of the users of the data warehouse. In this paper, the researche...

This paper deals with perceptual test methodologies to assess speech quality of telecommunication systems. Faced with the tremendous evolution in the telecommunications industry and with drawbacks of typical methodologies recommended by ITU-T, a new way to assess speech quality is investigated. It consists in measuring performance (i.e. reaction times and error rates) when subjects are performi...

The large amount of patient data amassed in the Electronic Patient Record systems are of great value for medical research. Aggregating research-grade data from these systems is a laborious, often manual process. We present a semantic framework that incorporates a data semantic model and validation rules to accelerate the cleansing process for data in Electronic Patient Record systems. We demons...

The Bureau of Labor Statistics (BLS) has begun a new survey to collect and publish job openings and labor turnover data. This new survey, the Job Openings and Labor Turnover Survey, or JOLTS, began collecting data in March 2000 and will soon publish estimates for the first time. Published estimates will include rates and levels for job openings, hires, and separations. These data will add to th...

Big data analytics associated with database searching, mining, and analysis can be seen as an innovative IT capability that can improve firm performance. Even though some leading companies are actively adopting big data analytics to strengthen market competition and to open up new business opportunities, many firms are still in the early stage of the adoption curve due to lack of understanding ...