The CrowdNewsroom is an open source platform used for crowdbased investigations by CORRECTIV, a non-profit investigative journalism network and our partners in media and civil society. Hundreds of people share confidential and/ or personal information that can then be used for further investigation. Investigations range from issues as diverse as real estate ownership ("Who owns the city?"), children's safety on their way to school ("Achtung Schulweg!") or women's experiences on abortion. One of the major challenges we face is to analyze the huge amounts of data derived through the CrowdNewsroom with the aim of finding underlying causes or problems. We're looking for great ideas that will help to speed up this process and reduce the burden for any single individual involved. That could be a collaborative tool that allows a crowd to fact check, annotate and/ or tag the data either automatically or in a possibly fun way, i.e. using a game like approach that makes people want to participate. Questions we frequently face when analyzing the CrowdNewsroom data are: Does the proof that people provide really support their claims? Are some claims made repeatedly by different persons, making it more likely that they are true? Do some facts (i.e. names of companies, their legal form, their place of residence) frequently coincide with certain others (i.e. complaints)? And how can different claims be combined in meta issues? We will provide separate (anonymous) data sets that can be used for the challenge.

www.crowdnewsroom.org marc.engelhardt @ correctiv.org