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ALTHOUGH I MIGHT have been able to describe the characteristics of our most recent presidents as 'How to Pick a President' (February) did, I found the explanation of how they [...]

The article discusses efforts to incorporate culturally diverse students in computer science (CS) at U.S. universities and the prevention of database decay by database administrators (DBAs). An overview of underrepresented minority (URM) computer science students in the U.S., including the potential motivating factors that would incorporate women into CS curricula, is provided.

Twenty-five Semantic Web and Database researchers met at the 2011 STI Semantic Summit in Riga, Latvia July 6-8, 2011[1] to discuss the opportunities and challenges posed by Big Data for the Semantic Web, Semantic Technologies, and Database communities. The unanimous conclusion was that the greatest shared challenge was not only engineering Big Data, but also doing so meaningfully. The following are four expressions of that challenge from different perspectives.

Until recently, data quality was poorly understood and seldom achieved, yet it is essential to the effective use of information systems. This paper discusses the nature and importance of data quality. The role of data quality is placed in the life cycle framework. Many new concepts, tools and techniques from both programming languages and database management systems are presented and related to data quality. In particular, the concept of a database constraint is considered in detail. Some current limitations and research directions are proposed.

A letter to the editor is presented in response to an article on empiricism in Big Data published in the May 3, 2014 issue.