My rating: 4 of 5 stars
Disclosure: the publisher of this book provided me with a free copy in exchange for a review. The opinions expressed in the review are my own.
While OpenRefine is an extremely useful “power tool for messy data”, its power can be difficult to master without a great deal of trial and error on the part of the user. Part of this stems from the evolving nature of the tool. It began life as Freebase Gridworks, with the purpose of cleaning up data in order to run it against linked data in Freebase. When the Freebase parent organization was acquired by Google, they rebranded the tool as Google Refine, but as Google’s priorities shifted, they stopped working on the tool and it became the open source OpenRefine. This legacy means that the tool has many pieces created by different people for different purposes. While there is quite a lot of good documentation out there on the OpenRefine site and elsewhere, this book puts it together in a easy to follow format. Like a lot of OpenRefine documentation, it is a series of “recipes” that explain how to do one specific task, but is written with the cover to cover reader in mind as well. The Google produced tutorial videos have similar coverage, but the book is more in depth, and has the advantage for readers coming from the cultural institution side of using a museum data set for examples. Another advantage is that the authors of the book have a particular interest in named entity recognition (part of the book covers the tool that one of them produced), which is particularly helpful for more abstract data sets with cultural data.
Using OpenRefine is useful for beginner or intermediate users of OpenRefine. As someone who has used OpenRefine for awhile and written about its use in libraries, this was more helpful than I expected initially, since there were pieces of functionality I’d not yet encountered in experimentation or documentation so far. My one criticism is that much of the book promises a complete explanation in the appendix of regular expressions and the Google Refine Expression Language that powers the software, but I found that the GREL documentation was less useful than I hoped, though I still learned from it. I would have preferred if that section had been earlier in the book. That aside, I would recommend this book to anyone who has been using OpenRefine or thinking about using it, and additionally for library and museum professional development collections.