Farola - making sense of big data

Farola - making sense of big data

Organisation: VPRO (Netherlands)

Publication Date: 06/02/2014


A visual browsing tool to quickly get an overview of big, unstructured textual databases. If an editor receives a big data file, like the Wikileaks cables, a set of emails or another large collection of text files, Farola can be used to make sense of this database. Upload the database and our tool will filter persons, locations, organisations and times and present them in a visual attractive and comprehensive way. As an editor you can make selections of the results you've found and use it to make an (interactive) graphic for your paper, tv episode or website. You can make a network of people or organisations, a map with relevant locations or a timeline. You can manually add or alter information for people, organisations or locations. This can all be done by editors or the audience can contribute to this. With Farola you can start making sense out of big, unstructured textual databases. This tool is mainly aimed at a male audience from ages 20 up to 40.

Technologies used for this project:

The tool is based on the open source tool Named Entity Recognition (NER) and Information Extraction (IE) from Stanford University. These are parts of Natural Language Processing. Our own tool is based on of-the-shelf open source tools like PHP and MySQL. For showing Wikipedia data we make use of DBPedia. We also use Bootstrap for layout, JQuery for DOM manipulation and Stapes for the implementation of the MVC pattern. On the backend we use components like Idiorm and the Slim framework for easy decoupling of database and API processes.
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