Among the manifold takes on world literature, it is our goal to contribute to the discussion from a digital point of view by analyzing the representation of world literature in Wikipedia with its millions of articles in hundreds of languages. As a preliminary, we introduce and compare three different approaches to identify writers on Wikipedia using data from DBpedia, a community project with the goal of extracting and providing structured information from Wikipedia. Equipped with our basic set of writers, we analyze how they are represented throughout the 15 biggest Wikipedia language versions. We combine intrinsic measures (mostly examining the connectedness of articles) with extrinsic ones (analyzing how often articles are frequented by readers) and develop methods to evaluate our results. The better part of our findings seems to convey a rather conservative, old-fashioned version of world literature, but a version derived from reproducible facts revealing an implicit literary canon based on the editing and reading behavior of millions of people. While still having to solve some known issues, the introduced methods will help us build an observatory of world literature to further investigate its representativeness and biases.