Modern automatic systems are able to collect huge volumes of data, often with a complex structure (e.g. multi-table data, XML data, web data, time series and sequences, graphs and trees). This fact poses new challenges for current information systems with respect to storing, managing and mining these sets of complex data. The purpose of this workshop is to bring together researchers and practitioners of data mining who are interested in the advances and latest developments in the area of extracting patterns from complex data sources like blogs, event or log data, medical data, spatio-temporal data, social networks, mobility data, sensor data and streams, and so on. The workshop aims at integrating recent results from existing fields such as data mining,statistics, machine learning and relational databases to discuss and introduce new algorithmic foundations and representation formalisms in pattern discovery. We are interested in advanced techniques which preserve the informative richness of data and allow us to efficiently and efficaciously identify complex information units present in such data.