In a first contribution, accepted as a talk, we present a novel method to detect anomalous paths in time series data on networks. In a second contribution, also accepted as a talk, we present a time-aware force-directed layout algorithm for temporal networks. A third contribution, accepted as a poster, will present our tool git2net, which can be used to extract temporal collaboration networks from git repositories. The last contribution, also accepted as a poster, presents an efficient algorithm to count causal paths in Big time series data on networks.