Tag: metadata

Link dump 2016/6: planes over the Atlantic, hidden metadata, name wars and materials

Next time I cross the Atlantic, I shall stop a moment to reflect on everything that’s happening in the background to make this possible. AeroSavvy has a great post explaining how the North Atlantic Tracks system works.

This experimental visualization tool from the Internet Archive is a fun way to explore the popularity of a given concept:

Graph displaying instances over time of the word "Colonialism" in 82,000 books indexed by the Internet Archive.
Dated instances of the word “Colonialism” in 82,000 books indexed by the Internet Archive.

The Anatomy of a Tweet. Unsurprisingly, a tweet is composed of much more than 140 characters. There’s a scary amount of metadata coming along with it.

Serialization formats are not toys. Things to watch out for if you are building a web application that takes YAML, XML or JSON input. Watch it even if you don’t: being aware of how easy it is to break software is sobering.

Game of Thrones — the French Baby Boys’ Names Edition. An hilarious take on the evolution of the most popular boy’s names in France. Also from the same excellent Strange Maps blog, I can’t help but love the straightforward honesty of cartographer Jacques-Nicolas Bellin who admitted to the following on his 1753 map of Australia:

Excerpt from a 1753 map, showing the words "Ceci est Conjecturale".
Excerpt from Bellin’s Carte Réduite des Terres Australes, 1753.

I’m currently reading Mark Miodownik’s Stuff Matters and discovering little snippets information about materials I wasn’t aware of. For example, that the reason reinforced concrete works so well is because “as luck would have it, steel and concrete have almost identical coefficients of expansion” (p. 75). In passing, he also warns against the simplistic equation concrete = ugly:

But the truth is that cheap design is cheap design whatever the material. Steel can be used in good or bad design, as can wood or bricks, but it is only with concrete that the epithet of ‘ugly’ has stuck. There is nothing intrinsically poor about the aesthetics of concrete.

I agree.

Guessing the language of a book based on its title

In the midst of endless report-writing, I was faced with an interesting challenge at work this week. We are trying to aggregate e-book usage data for the members of our consortium, and we were interested in figuring out how well the French language content is faring compared to the English titles that make the bulk of the collection.

Unfortunately, one of our vendors do not include language data in either their title lists or the usage reports. Before trying to recoup the usage reports with the full e-book metadata I could get from the MARC records, I tried to run the title list through the guess_language library by way of a simple Python script:

from guess_language import guess_language
import csv
with open('2015-01_ProQuest_titles.csv', 'rb') as csvfile:
    PQreader = csv.DictReader(csvfile)
    for row in PQreader:
        title = row['Title']
        language = guess_language(title.decode('utf-8'))
        print language, title

The results were a disaster:

pt How to Dotcom : A Step by Step Guide to E-Commerce
en My Numbers, My Friends : Popular Lectures on Number Theory
en Foundations of Differential Calculus
en Language and the Internet
en Hollywood & Anti-Semitism : A Cultural History, 1880-1941
de Agape, Eros, Gender : Towards a Pauline Sexual Ethic
la International Law in Antiquity
fr Delinquent-Prone Communities
en Modernist Writing & Reactionary Politics

guess_language works by identifying trigrams, combinations of three characters that are more prevalent in one language than another. While it works reasonably well on whole sentences and short text snippets, the particular construction of a book title seems to throw the method entirely off-kilter.

As I was pondering the next steps, I came to realize that I could also filter titles based on language directly in the vendor database and then export to a CSV file… which solved my issue in seconds but wasn’t half as fun as playing around with computational linguistics. Back to writing reports, I guess.