The main objective of this work package is to support key points in the lifecycle of information and data in the COSMOS project. The amount of data which is 'born digital' in today's world is increasing exponentially, especially as more devices and Things are connected to the internet. This data has the potential to become an extremely valuable asset, if it can be harnessed effectively. Harnessing the data is challenging because of its vast quantity, its distributed and heterogeneous nature, and its birth in a huge number of devices, some of which are connected only intermittently to the network and have limited storage or compute resources. The data needs to be managed from (i) its birth, (ii) as it is streamed across networks, and when it is (iii) stored persistently. The data needs to be modelled in a meaningful way in order to extract value from it. Moreover, tools are needed, both in order to process the data in real time, and in order to save it persistently and support longer term analysis.
In particular, this WP will focus on:

• The specification of a new rich metadata structure capturing the social behaviour of objects through attributes
  enabling high reliability, security and as well as autonomous management.
• Mechanisms to extract social-related information from data flows with respect to objects collaboration,
  information exchange, lifecycle, access and QoS properties.
• Implementing Complex Event Processing based mechanisms for real-time analysis of streaming data.
• Analysing the streaming data in order to obtain: raw data pre-processing, detection of temporal or structural patterns between the events originating from various objects and generation of value added information from the basic events.
• Representing raw data as storage objects and annotating those objects with enriching metadata.
• Scalable data management through workload optimized data object stores and analytics that can be performed on networks of storage data objects.