This is the sixth of our twelve interviews with data management authors to celebrate our twelfth birthday.
This week, I chat with my good friend and erstwhile fellow Board member at IAIDQ/IQ International and DAMA International, and fellow coalition member at The Leaders’ Data Group, Laura Sebastian Coleman.
In this video, Laura discusses her 2013 book Measuring Data Quality for Ongoing Improvement. This book grew out of a data governance programme where Laura’s colleagues were struggling to communicate clearly about the problems with measuring the quality of data. The fundamental issue: everyone had different answers to what the definitions of key terms were. This resulted in the development of a framework to support the objective measurement of data quality so different stakeholders could understand the objective quality of data consistently.
Laura has written a number of other books since this one, so her key takeaway on something she would change was the need to simplify and clarify definitions associated with data quality. She would also have given more examples to illustrate the abstract concepts with concrete illustrations.
This is yet another interview where a data management professional highlights the need for data management professionals to be widely read. Laura’s selected book discusses the history of the evolution of the concept of objectivity, which has its root in the pursuit of “ideal forms” in taxonomies. She highlights the pitfalls we often fall into in data where people often think there is “one right answer” (particularly in data modelling) and projects and initiatives get bogged down (which brings to mind the old joke about the difference between a hostage taker and a data modeller: you can negotiate with a hostage taker).
Measuring Data Quality for Ongoing Improvement is the first in a number of books that Laura has written on data quality management. Laura’s new book is scheduled for publication in early 2022.
And as a small point of trivia, Laura is the second data management author featured in our series who has a PhD in English Literature (proof, if needed, that data management professionals can come from widely different backgrounds to the “technologist” path).
Watch the interview below (and then scrolls down for our competition).
Laura references Objectivity by Daston and Galison as one of her more recent influences. In common with other authors interviewed, Laura had a wide range of books to choose from as influences. But as discussed earlier, this book’s examination of the history of the development of the concept of objectivity in epistemology, science, and philosophy over the past few centuries. It’s interesting to note the authors of this book pinpoint the mid-19th century as the period when “objectivity” became a mainstream concept in science. But even at that, the interpretation and application of the concept of objectivity has continued to evolve from the pursuit of an “ideal form” to a focus on “accuracy to reality”.
This is similar to the debate that data quality projects have faced when discussing “accuracy” – is it to reality or to a surrogate (ideal form) source?
If you would like to be entered into a draw to win some of the books referenced by Laura in this video and in the rest of the videos we’re running this month, please provide your email address and an answer to the simple question in the form below. The terms and conditions for the competition can be found here:
Books Referenced in this Video
- Measuring Data Quality for Ongoing Improvement (Laura Sebastian-Coleman)
- Objectivity (Lorraine Daston, Pierre Galison)
Related Castlebridge Content
- Definitions, Words, and the Alchemy of Information
- The Princess Bride Effect, Boil Water Notices, and Brexit
- John Ladley – Author Interview Week 1
- Katherine O’Keefe – Author Interview Week 2
- Dr Tom Redman – Author Interview Week 3
- Danette McGilvray – Author Interview Week 4
- Barry Devlin – Author Interview Week 5