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Rural Life

Post author By Margaret
Post date January 11, 2017

I live in a dense urban environment surrounded by apartments, taxis, etc., but I happen to live in a house with a wonderful backyard where we grow vegetables, fruit, and flowers in addition to a lawn I mow with a manual push mower. It’s winter now, but we still manage to find some joy in the garden with my “visual interest” plantings that may more signal lack of weeding. (I have a 5 month old, it’s hard to keep up).

I’ve been reading a lot about rural life and farming lately. Various things converged to make this happen. Anyway, there’s a lot of writing about the contentment that comes in connection to land and place, even if it appears to outsiders to constrict choice. I’ve never really read Wendell Berry before, but I’m going to start, because I think he has a lot of value to say about life in rural areas that comes from a more useful point of view than the bloviating in political discourse.

I don’t think technology entrepreneurs need to farmsplain rural life to people who live there, who aren’t all the same and don’t think all the same.

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Review of Using OpenRefine by Ruben Verborgh and Max De Wilde

Post author By Margaret
Post date November 19, 2013

Using Openrefine by Ruben Verborgh

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.

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