The European Parliament should return to a ‘dual mandate’ system which uses national politicians as representatives instead of directly elected MEPs

One of the key criticisms of European Parliament elections is that low turnout prevents the Parliament from genuinely being able to confer legitimacy on the EU’s legislative process. Herman Lelieveldt writes that while there was a small increase in turnout in the 2014 European elections, the overall trend of declining turnout necessitates a radical reform to improve the EU’s democratic legitimacy. He suggests returning to a ‘dual mandate’ system through which national parliaments appoint a proportion of their members to split time between the European Parliament and the national level

Gastronationalism? How Europe’s food production is becoming entangled in nationalist politics

A number of actors have called for the extension of EU rules on food labelling under which food products sold in the EU are required to indicate their country of origin. Herman Lelieveldt writes that this debate is part of a wider rise in so called ‘gastronationalism’ across Europe, where food production is assigned symbolic value by those who articulate nationalist sentiments, and domestically produced food is assumed to be safer than food imported from abroad

Approximated and User Steerable tSNE for Progressive Visual Analytics

Progressive Visual Analytics aims at improving the interactivity in existing analytics techniques by means of visualization as well as interaction with intermediate results. One key method for data analysis is dimensionality reduction, for example, to produce 2D embeddings that can be visualized and analyzed efficiently. t-Distributed Stochastic Neighbor Embedding (tSNE) is a well-suited technique for the visualization of several high-dimensional data. tSNE can create meaningful intermediate results but suffers from a slow initialization that constrains its application in Progressive Visual Analytics. We introduce a controllable tSNE approximation (A-tSNE), which trades off speed and accuracy, to enable interactive data exploration. We offer real-time visualization techniques, including a density-based solution and a Magic Lens to inspect the degree of approximation. With this feedback, the user can decide on local refinements and steer the approximation level during the analysis. We demonstrate our technique with several datasets, in a real-world research scenario and for the real-time analysis of high-dimensional streams to illustrate its effectiveness for interactive data analysis