We are happy to announce that the second version of the tool new/s/leak has been completed. New/s/leak supports journalists in the evaluation of very large volumes of documents, such as those that repeatedly emerge from leaks of internal company or government data. The approach of the open-source software is the automatic identification of proper names as well as their visualization and filtering along relationship networks in the documents. In this way, one can quickly gain insight into otherwise unmanageable amounts of data and find starting points for journalistic reporting.

We are happy to announce that the new/s/leak project receives some additional funding from the Volkswagen Stiftung. Until summer 2018, new/s/leak will be extended and refactored to achieve the following goals: * easy deployment for own usage * comprehensive and detailed documentation * improved user interface * improved information extraction (better keyterm extraction, named entity recognition, support of user dictionaries) * support for multiple languages (among others english, german, spanish, french, arabic, chinese) Follow the updates on this blog to see how far we got :)

We already explained the language-related data wrangling happening under new/s/leak’s hood. For the success of new/s/leak, our second scientific field is the game changer: interactive visualization. No matter how much accurate information we can produce - if we cannot present them to the user in an appealing way, the tool will fail its goals. So how exactly is visualization science influencing new/s/leak? Your daily dose of visualization science It might seem easy to create some kind of visualization (with Excel or even pen and paper) - however, there are lots of pitfalls that you need to avoid to create good visualizations.

There are many reasons why data journalism needs new scientific approaches, and we have discussed some of them at length. So far we haven’t talked much about the reverse claim, which is, however, equally true: this journalistic project also advances science. So why are our scientists so passionate about the new/s/leak project? And what kind of scientific challenges do we face? /S/cience on a Mission All our scientists agree that it’s an invaluable experience to work on real use cases, solving real-world problems and collecting extensive feedback from real users.

Because of the Easter holiday season and several conference deadlines, this blog had to take a little break. Being back, we want to give a glimpse on the science behind of new/s/leak. We have two camps of scientists working together: computational linguists contribute software that extract semantic knowledge from texts, and visualization experts who bring the results to smart interactive interfaces that are easy to use for journalists (after the computational linguists made the dataset even more complicated than before).

User requirements management is something that happens far too rarely, especially in scientific software. (And it can definitely be challenging.) For our project that brings together so different worlds of science and journalism, and also different academic disciplines, it’s even more important. We dedicated this a whole day on which we had Franziska and Kathrin over at SPIEGEL in Hamburg - and we proved that requirements analysis can be both, challenging and fun at the same time.

Happy news: VW foundation officially decided to fund our project with the working title DIVID-DJ: Data Extraction and Interactive Visualization of Unexplored Textual Datasets for Investigative Data-Driven Journalism. We are one out of eight projects funded as a part of the initiative “Science and Data Journalism”. Our goal is to create a piece of software that visualizes the content of large text data collections, to help journalists working with data leaks.