KB Labs

It's not just about data.
It's about connecting data with people.

About

KB Labs seeks to find new ways to combine the library’s digital cultural heritage collections and research, with the latest methods within machine learning. The lab is an initiative taken by the IT department at the Royal Danish Library.

Here you will find different applications made by the Royal Danish Library to visualize, engage or showcase the different materials or collections that we have available, to inspire and deepen the knowledge of what collections we actually have, and hopefully expand the use of these.

At the moment, applications and builds found here are considered experimental projects, and as such, can change or even be taken down without warning. This includes the data being presented by the applications.

Feel free to contact us, if you have any questions or wish to know more about a given project.

Projects

JUXTA Experimental project
Visualisation


Image collections presented as collages, with seamless zooming from full collection to full-screen single images. Context-sensitive meta data with link-back to the originating sources makes it easy to explore large collections.

Go to Juxta - Postcards
This collection visualizes the Royal Danish Library's collection: Postkortsamlingen (The Postcard Collection)

Go to Juxta - Maps
This collection visualizes the Royal Danish Library's collection: Kort og Atlas (The Maps and Atlas Collection)

DOTS Experimental project
Visualisation


DOTS visualizes Danish cities referenced in articles related to your search in the Royal Library's Danish newspaper archive.

Go to DOTS

PIXPLOT Experimental project
Visualisation


PixPlot (https://github.com/YaleDHLab/pix-plot) is a product of Yale Digital Humanities Lab that uses Google Tensorflow to provide a spatial layout for a collections of images, where similar images are grouped together.

This works surprisingly well for all collections we have tried. In this demo, we used our collection of Dansk-Vestindien images (http://www.kb. dk/images/billed/2010/okt/billeder/subject5259/da/). The clusters on the left hand side are automatically generated.

Extending PixPlot is on our to-do. Our primary needs are display of metadata for the individual images and rendering of the images in higher resolution.

Go to PixPlot

SMURF Experimental project
Visualisation


Smurf visualises how use of language in Danish newspapers has evolved since the 18th century.

Go to smurf

TAGS Experimental project
Visualisation


TAGS visualizes the use of HTML tags in the Royal Library's Danish Netarchive. In the app you can search and compare the use of different tags from 2007 until today.

Go to TAGS

MERMEID Experimental project
Dataset


Metadata Editor and Repository for MEI Data.

Go to MerMEId

ZOOM Experimental project
Visualisation


A serendipitous presentation of 1 million newspaper pages from Mediestream. For your convenience, the 20 terapixels from the scanned papers are packed into a single image. Only thing needed is to zoom a bit.

Go to ZOOM

WORD2VEC Experimental project
Machine learning


Word2Vec is a high-dimensional word embedding based on an unsupervised machine learning algorithm using a simple neural network. It maps each unique word in a large text corpus to a vector.
The vector representation of the words reflects interesting semantic properties of the words. Words that appear in the same context will be close in the vector-space (similar words). But distance between words can also be used to find analogies. The word2vec demo features several corpora and a very large one based on over 65.000 Gutenberg E-books.

Go to Word2Vec

LOAR Experimental project
Dataset


LOAR (Library Open Access Repository) is an open access repository for long term preservation of research data. LOAR also contains some of the Royal Danish Library’s open data sets.

Go to LOAR