MoKMaSD 2015 aims at bringing together practitioners and researchers from academia, industry and research institutions to present research results and exchange experience, ideas, and solutions for modelling and analysing complex systems and using knowledge management and discovery methodologies in various domain areas such as social systems, ecology, biology, medicine, smart cities, governance, education and social software engineering.
In the last years we witnessed to a shift from static network analysis to a dynamic networks analysis, i.e., the study of networks whose structure change over time. As time goes by, all the perturbations which occur on the network topology due to the rise and fall of nodes and edges have repercussions on the network phenomena we are used to observe. As an example, evolution over time of social interactions in a network can play an important role in the diffusion of an infectious disease.
Aula Gerace, Department of Computer Science, Pisa, Italy
Science 2.0 refers to the rapid and systematic changes in doing Research and organising Science driven by the rapid advances in ICT and digital technologies combined with a growing demand to do Science for Society (actionable research) and in Society (co-design of knowledge). Nowadays, teams of researchers around the world can easily access a wide range of open data across disciplines and remotely process them on the Cloud, combining them with their own data to generate knowledge, develop information products for societal applications, and tackle complex integrative complex problems that could not be addressed a few years ago.
The summer school "Constraint Programming meets Data Mining" provides an intensive training opportunity to learn the essentials of recent research on constraint solving, machine learning and data mining, and the key aspects related to their integration.
Social mining has the potential to provide a privacy-respectful social microscope, or socioscope,
needed to observe the hidden mechanisms of socio-economic complexity.
There is a fertile ground for further aggregation of researchers and stakeholders, towards the
creation of a European Laboratory on Big Data Analytics and Social Mining, capable of boosting
research and innovation in the deployment of big data analytics, social mining and privacy/trust
technologies to face global challenges.