CORE - A Contextual Reader based on Linked Data

demonstrative video

CORE is a contextual reader application intended to improve user reading experience, particularly with regard to material in an unfamiliar domain.

CORE works by utilizing Linked Data reference vocabularies and datasets to identify entities in any PDF file or web page. For each discovered entity, pertinent information such as short descriptions, pictures, or maps are sourced and presented on a mouse-over, to allow users to familiarize themselves with any unfamiliar concepts, places, etc in the texts they are reading.

If further information is needed, an entity can be clicked to open a full context pane, which supports deeper contextualization (also visually, e.g. by displaying interactive timelines or maps). Here, CORE also facilitates serendipidous discovery of further related knowledge, by being able to bring in and suggest related resources from various repositories. Clicking on any such resource loads it into the contextual reader for endless further browsing.

In contrast to many other such systems, a CORE instance is always configured for a particular domain, thereby ensuring the contextual information provided is actually of use and interest to the end-user.

To provide its services, CORE makes use of dynamic, configurable entity recognition, in which modular lexical analysis services are combined with SPARQL queries to allow multilingual entity recognition against any vocabulary stored at a Linked Data endpoint. While in the future, it is intended for the application to be fully configurable using a web user interface, currently new instances have to be configured from the source code, which is released under the MIT open source license.

Credits: conceptual design by Thea Lindquist and Eetu Mäkelä, implementation by the latter. CORE was created as part of the WWI Linked Data project initiated and directed in Aalto University by Eero Hyvönen and by Thea Lindquist in University of Colorado Boulder.