KB Labs was established in 2016 by the IT development department at the Royal Danish Library. The goal of KB Labs is to find new ways to combine the library’s digital cultural heritage collections and research with the newest methods within machine learning. The tools are developed in close collaboration with Danish and international researchers to ensure high quality tools with a high level of relevance for their users.
Smurf visualises how use of language in Danish newspapers has evolved since the 18th century (beta).
Word2Vec is a high-dimensional word embedding based on an unsupervised machine learning algorithm using a simple neural network (beta).
LOAR (Library Open Access Repository) is an open access repository for long term preservation of research data.
At KB Labs, we seek to develop new inspiring tools for researchers and students as well as the everyday user to create alternative ways of interacting with the vast amount of digital data the library possess. We experiment with different tools and data to figure out which data we can use, what we can do with it, and how it can contribute to the users of the library, researchers, students and the public in general.
At labs.kb.dk, you will find different applications made by the Royal Danish Library to visualise, engage or display the different materials or collections that are available at the library to inspire and deepen the knowledge of what collections the library actually has. This will hopefully expand the use of these collections.