Elizabeth M. Pierce

Assessing data quality with control matrices

The control matrix, long used by IS auditors to evaluate information integrity, can be modified to assess the reliability of information products.

The genetic code--more than just a table.

The standard codon table is a primary tool for basic understanding of molecular biology. In the minds of many, the table’s orderly arrangement of bases and amino acids is synonymous with the true genetic code, i.e., the biological coding principle itself. However, developments in the field reveal a much more complex and interesting picture. In this article, we review the traditional codon table and its limitations in light of the true complexity of the genetic code. We suggest the codon table be brought up to date and, as a step, we present a novel superposition of the BLOSUM62 matrix and an allowed point mutation matrix. This superposition depicts an important aspect of the true genetic code—its ability to tolerate mutations and mistranslations.

A Case Study in Partial Parsing Unstructured Text

This paper presents a parsing method for the entity extraction from open source documents. A Web page of interest is first downloaded to a text file. The method then applies a set of patterns to the text file to extract interesting entity fragments. The patterns are currently particularly designed for obituary announcements. With the extracted entities, the next step is to identify these entities before they are populated into a database. An entity resolution process is presented to determine the actual identities. A case study is illustrated with the method and the results are presented also. Although the results show that the method is not technically effective and promising, the research results do help understand how well or bad a quick parsing technique extracts entities of interest from obituaries on the Web. More effective techniques should be further considered to improve the extraction results.

Epilogue: The Data Quality Profession

In this final chapter, we will discuss four significant topics concerning the data quality profession. First, we will examine how the data quality profession has evolved. Second, we will explore what it means to be a data quality professional. Third, we will review the training opportunities currently available to those interested in becoming a data quality professional, and finally, we will assess the outlook for the future of the data quality profession. Throughout this chapter we will use the terms “data” and “information” interchangeably.