A Scalable Analytics Platform (ASAP)

http://www.asap-fp7.eu/
The ASAP FP7 research project develops a dynamic open-source execution framework for scalable data analytics. The underlying idea is that no single execution model is suitable for all types of tasks, and no single data model (and store) is suitable for all types of data. Complex analytical tasks over multi-engine environments therefore require integrated profiling, modeling, planning and scheduling functions. The project has four goals:

A general-purpose task-parallel programming model and a runtime system to execute it in the cloud. The runtime will incorporate and advance state-of-the-art task-parallel programming models features: irregular general-purpose computations, resource elasticity,synchronization, data-transfer, locality and scheduling abstraction, ability to handle large sets of irregular distributed data and fault-tolerance.
A modeling framework that constantly evaluates the cost, quality and performance of data and computational resources in order to decide on the most advantageous store, indexing and execution pattern available.
A unique adaptation methodology that will enable the analytics expert to amend the task she has submitted at an initial or later stage.
A state-of-the-art visualization engine that will enable the analytics expert to obtain accurate, intuitive results of the analytics tasks she has initiated in real-time.

CELAR: Automatic, multi-grained elasticity-provisioning for the Cloud

http://www.celarcloud.eu/
Auto-scaling resources is one of the top obstacles and opportunities for Cloud Computing: consumers can minimize the execution time of their tasks without exceeding a given budget; cloud providers maximize their financial gain while keeping their customers satisfied and minimizing administrative costs. Many systems claim to offer adaptive elasticity, yet the “throttling” is usually performed manually, requiring the user to figure out the proper scaling conditions. In order to harvest the benefits of elastic provisioning, it is imperative that it be performed in an automated, fully customizable manner. CELAR delivers a fully automated and highly customizable system for elastic provisioning of resources in cloud computing platforms.

ARCOMEM: More than an Archive. Social Web History

http://www.arcomem.eu/
ARCOMEM is about memory institutions like archives, museums, and libraries in the age of the Social Web. Memory institutions are more important now than ever: as we face greater economic and environmental challenges we need our understanding of the past to help us navigate to a sustainable future. This is a core function of democracies, but this function faces stiff new challenges in face of the Social Web, and of the radical changes in information creation, communication and citizen involvement that currently characterise our information society (e.g., there are now more social network hits than Google searches). Social media are becoming more and more pervasive in all areas of life. In the UK, for example, it is now not unknown for a government minister to answer a parliamentary question using Twitter, and this material is both ephemeral and highly contextualised, making it increasingly difficult for a political archivist to decide what to preserve.

MoDisSENSE: A Distributed Platform for the Development of Social Networking Services over Mobile Devices

http://www.modissense.gr
MoDisSENSE enriches social networking services by exploiting the continuous data flow from the daily use of mobile phones. This flow includes data from user visited locations, contacts, calls and calendar combined with data acquired from the user’s social network (list of friends, profile and preferences). The project combines these heterogeneous data sources (geographic and social log files, user profiles and preferences and context information) and offers innovative services based on advanced searches and combined queries that exploit all these aforementioned sources by utilizing state-of-the art distributed data processing techniques. Furthermore, the project deals with the development and deployment of services that exploit spatiotemporal data generated by user paths.