Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
enhanced COntent distribUtion with Social INformation (ECOUSIN)

Framework: FP7 — Cooperation
Programme: Information and Communication Technologies
Destination: Pervasive and Trusted Network and Service Infrastructures
Action type: Collaborative project
Countries involved: France,Belgium,Spain,Germany,Germany,Italy,United Kingdom
Call:  (FP7-ICT-2011-8, 2011)
Start date: 2012-11-01
End date: 2015-04-30
Duration (months): 30.0
Total project cost (EUR): 4750793.0
EU funding (EUR): 2998000.0
Participants: 9
Project status: CLOSED

Content Distribution Services are booming and they will be responsible for the majority of future Internet traffic. In parallel, Online Social Networks (OSNs) have become today’s most popular Internet application. The widespread adoption of OSNs has drastically changed the way content is consumed in the Internet, as content consumption is nowadays highly impacted by the information shared by users through OSNs and the popularity of a given content is most often dictated by its “social” success. With such a “social-content revolution”, operators need to evolve and optimize their network to avoid being overwhelmed by the ever growing traffic volumes resulting from this paradigm change. To this aim, the goal of eCOUSIN is to design a novel social-aware network architecture with built-in content dissemination functionalities that exploits the social-content interdependencies to improve its efficiency. This goal translates into the following specific objectives: (i) the implementation of high performance distributed tools for collecting necessary data to study and model the social-content interdependencies; (ii) the improvement of the scalability of network infrastructures when handling content by exploiting social information; (iii) the design of an on-net operational framework that tightly integrates network functionalities and content-related service functionalities; and (iv) the design of algorithms that exploit social information for placing and delivering contents in an optimized manner with a special focus on mobile environments. We envision that all these will be fundamental components of the future Internet architecture. The eCOUSIN consortium comprises two leading network operators, two major manufacturers of telecommunication equipment, one research institute and four universities. All of them are strong actors in the areas of this project, and their complementary nature ensures the impact of the eCOUSIN outcomes on both the industrial and scientific domains.

Keywords: social-aware future internet architecture,on-net content dissemination,energy efficiency,information-centric networking,social-content interdependencies,mobile networks.
MOdel-Driven Approach for design and execution of applications on multiple Clouds (MODACLOUDS)

Framework: FP7 — Cooperation
Programme: Information and Communication Technologies
Destination: Pervasive and Trusted Network and Service Infrastructures
Action type: Collaborative project
Countries involved: Italy,Norway,Romania,United Kingdom,France,Romania,Spain,Spain,Austria
Call:  (FP7-ICT-2011-8, 2011)
Start date: 2012-10-01
End date: 2015-09-30
Duration (months): 36.0
Total project cost (EUR): 8997729.0
EU funding (EUR): 6048000.0
Participants: 10
Project status: CLOSED

Current Cloud’s offer is becoming day by day wider providing a vibrant technical environment, where SMEs can create innovative solutions and evolve their services. Cloud promises cheap and flexible services to end-users at a much larger scale than before. However, Cloud business models and technologies are still in their initial hype and characterized by critical early stage issues, which pose specific challenges and require advanced software engineering methods. The main goal of MODAClouds is to provide methods, a decision support system, an open source IDE and run-time environment for the high-level design, early prototyping, semi-automatic code generation, and automatic deployment of applications on multi-Clouds with guaranteed QoS. Model-driven development combined with novel model-driven risk analysis and quality prediction will enable developers to specify Cloud-provider independent models enriched with quality parameters, implement these, perform quality prediction, monitor applications at run-time and optimize them based on the feedback, thus filling the gap between design and run-time. Additionally, MODAClouds provides techniques for data mapping and synchronization among multiple Clouds. MODAClouds innovations thus are: (i)simplify Cloud provider selection favoring the emergence of European Clouds, (ii) avoid vendor lock-in problems supporting the development of Cloud enabled Future Internet applications, (iii) provide quality assurance during the application life-cycle and support migration from Cloud to Cloud when needed. The research is multi-disciplinary and will be grounded on expertise from several research areas. MODAClouds consortium consists of highly recognized Universities and research institutions that will assure a sound scientific progress, SME partners providing expertise on modelling tools, and large companies that assure industry relevance. The MODAClouds approach and tools will be applied on four industrial cases from different domains.

Keywords: model driven engineering,cloud design abstractions,quality assurance,non-functional requirements,decision support systems,self-adaptaition,lifecycle management,performance prediction models
Europe-Wide Platform for Cooperative Mobility Services (MOBINET)

Framework: FP7 — Cooperation
Programme: Information and Communication Technologies
Destination: ICT for a low carbon economy
Action type: Collaborative project
Countries involved: Belgium,France,Italy,Norway,Denmark,Finland,France,Spain,Sweden,Netherlands,Italy,United Kingdom,Spain,Germany,Netherlands,Germany,Greece,France,Netherlands,Belgium,Netherlands,Netherlands,Switzerland,Denmark,Spain
Call:  (FP7-ICT-2011-8, 2011)
Start date: 2012-11-01
End date: 2017-06-30
Duration (months): 56.0
Total project cost (EUR): 15085983.0
EU funding (EUR): 10963000.0
Participants: 39
Project status: CLOSED

MOBiNET will develop, deploy and operate the technical foundations of an open, multi-vendor platform for Europe-wide mobility services. Key MOBiNET innovations address the barriers to cooperative system-enabled service deployment, including the lack of harmonised services; availability of communication means; inaccessibility and incompatibility of transport-related data; fragmentation of end-user subscription; proprietary technologies in user devices; etc. MOBiNET will develop solutions for both business (B2B) users and end (B2C) users (drivers and travellers): - a comprehensive directory of Europe-wide mobility and transport-related data and services; - an e-Marketplace as an e-commerce network linking end users, content- and service-providers; - single sign-on MOBiNET membership; - membership of the MOBiNET B2B Provider Community enables providers to add third-party content and services contract-free to their own products; - a platform-independent agent on end-user devices, including access to a MOBiNET Service Directory and an intelligent communication & connectivity manager that hosts end-user services; - the project will develop both a Service Development Kit to enable easy creation of MOBiNET user services and a set of uniform Reference Services suitable for Europe-wide deployment, including “eco-traffic management-as-a-service” and a multimodal traveller assistant. The MOBiNET platform facilities will be hosted as cloud services available to the provider community, and will be operational early during the project. These facilities will be taken up at a group of diverse pilot sites that will validate MOBiNET in trials aimed at learning from operators’ and users’ experience how to create, deploy and operate services in a Europe-wide platform.

Keywords: cooperative systems,service platform,cooperative mobility,service directory,cloud computing,its
Topological Complex Systems (TOPOSYS)

Framework: FP7 — Cooperation
Programme: Information and Communication Technologies
Destination: Future and Emerging Technologies
Action type: Collaborative project
Countries involved: Slovenia,Austria,Sweden,Poland,Israel
Call:  (FP7-ICT-2011-8, 2011)
Start date: 2012-10-01
End date: 2015-09-30
Duration (months): 36.0
Total project cost (EUR): 3449204.0
EU funding (EUR): 2635000.0
Participants: 5
Project status: CLOSED

In dynamics, local behaviour is often very unstable, while global behaviour often is immensely hard to derive from local knowledge. Traditionally, topology has been used in abstracting the local behaviour into qualitative classes of behaviour — while we cannot describe the path a particular flow will take around a strange attractor in a chaotic system, we can often say meaningful things about the trajectory as an entirety, and its abstract properties. We propose to use computational topology, which takes notions from algebraic topology and adapts and extends them into more algorithmic forms, to enrich the study of the dynamics of multi-scale complex systems. With the algorithmic approach, we are able to consider inverse problems, such as reconstructing dynamical behaviorus from discrete point samples. This is the right approach to take for complex systems, where the precise behaviour is difficult if not impossible to analyse analytically. In particular we will extend the technique of persistence to include ideas from dynamical systems, as well as incorporating category theory and statistics. Persistence is inherently multi-scale, and provides a framework that will support the analysis of multi-scale systems, category theory provides a platform for a unified theory and joint abstraction layers, and statistics allows us to provide quality measures, inferences, and provide confidence intervals and variance measures for our analyses. The combination of these four areas: category theory, statistics, and dynamical systems with computational topology as the joint platform for the three other components, will allow for a mathematically rigorous description of the dynamics of a system from a local to a global scale. In this framework, multi-scale features have a natural place, and the focus on computation and algorithmics means we can easily verify and validate our theory. We propose to do this on two datasets, capturing robot configuration spaces and social media.

Keywords: topology,persistent homology,statistics,dynamical systems,category theory,machine leanring,data mining,robotics
Intelligent Tutoring Interface for Technology Enhanced Learning (INTUITEL)

Framework: FP7 — Cooperation
Programme: Information and Communication Technologies
Destination: ICT for Learning and Access to Cultural Resources
Action type: Collaborative project
Countries involved: Germany,Germany,United Kingdom,Austria,Spain,Israel,Germany,Netherlands,Spain,Germany,Italy
Call:  (FP7-ICT-2011-8, 2011)
Start date: 2012-10-01
End date: 2015-06-30
Duration (months): 33.0
Total project cost (EUR): 3674861.0
EU funding (EUR): 2900000.0
Participants: 12
Project status: CLOSED

The objective of INTUITEL is to enhance state-of-the-art e-learning content and Learning Management Systems (LMS) with features that so far have been provided only by human tutors. An INTUITEL-enabled system constitutes an integrated learning environment that configures itself in response to any learner, monitors his/her progress and behaviour, combines these data with pedagogical and methodological knowledge and then by automated reasoning deduces optimal guidance and feedback. The deductive process may include the current learner performance, the daily learning attitude and emotional setting of the learner, personal aspects like gender, culture and age as well as environmental aspects like available communication bandwidth, ambient noise level, screen size and type of access device. INTUITEL therefore will be a step towards a global learning cloud, where personalized technology-enhanced learning is available for any person at any place, with any access device and under any external condition, including mobile learning scenarios. In INTUITEL, learning goals will be defined according to the desired competency, which will be mapped to the available content. At the same time, high flexibility to choose a learning pathway is maintained by offering system driven and learner directed navigation tools, thereby increasing the empowerment of teachers and learners and fostering the acquisition of methodological knowledge. By interpreting the learner's responses INTUITEL will automatically determine his/her position in a cognitive model for the particular learning content. The INTUITEL-enabled LMS then plays the role of a pedagogically skilled teacher, transparently guiding the learner towards the required competencies. Particular emphasis will be put on a widespread dissemination of INTUITEL results across the e-learning industry as well as in schools, universities and to other educational key players in collaboration with a major e-learning conference.

Keywords: e-learning,learner modeling,pedagogy,mobile learning,semantic web,ontologies,personal learning environment,tutoring,adaptive system,ilias,moodle
SemaGrow: Data intensive techniques to boost the real-time performance of global agricultural data infrastructures (SEMAGROW)

Framework: FP7 — Cooperation
Programme: Information and Communication Technologies
Destination: Technologies for Digital Content and Languages
Action type: Collaborative project
Countries involved: Spain,Greece,Italy,Austria,Serbia,Netherlands,Italy
Call:  (FP7-ICT-2011-8, 2011)
Start date: 2012-11-01
End date: 2015-10-31
Duration (months): 36.0
Total project cost (EUR): 3146747.0
EU funding (EUR): 2470000.0
Participants: 8
Project status: CLOSED

As the trend to open up data and provide them freely on the Internet intensifies, the opportunities to create added value by combining and cross-indexing heterogeneous data at a large scale increase. To seize them, we need infrastructure that is not only efficient, real-time responsive and scalable but is also flexible and robust enough to welcome data in any schema and form and to transparently relegate and translate queries from a unifying end-point to the multitude of data services that make up the open data cloud. This, relies on detailed and accurate data summaries and other data source annotations, and with increased data volumes and heterogeneity managing these annotations, it becomes by itself a challenging data problem. SemaGrow will (a) develop scalable and robust semantic storage and indexing algorithms that can take advantage of resource naming conventions and other natural groupings of URIs to compress data source annotations about extremely large datasets; (b) develop query decomposition, source selection, and distributed querying methods that take advantage of such algorithms to implement a scalable and robust infrastructure for data service federation; and (c) rigorously test its components and overall architecture over real, complex, interconnected datasets comprising data and document collections, sensor data, and GIS data. SemaGrow will be rigorously tested on the large-scale and complex agricultural data service ecosystem, comprising more than 20 currently operating data services providing today Gigatriples of RDF data, projected to double before SemaGrow ends and to reach Teratriples by 2020. Being able to query across these datasets is a real and present need. SemaGrow envisages to develop the scalable, efficient, and robust data services needed to take full advantage of the data-intensive and inter-disciplinary Science of 2020 and to re-shape the way that data analysis techniques are applied to the heterogeneous data cloud.

Keywords: powder protocol,triple store compression,indexing algorithms,query decomposition,distributed triple store querying,large-scale & complex agricultural data service ecosystem
Working Environment with Social and Personal Open Tools for inquiry based learning. (WESPOT)

Framework: FP7 — Cooperation
Programme: Information and Communication Technologies
Destination: ICT for Learning and Access to Cultural Resources
Action type: Collaborative project
Countries involved: Netherlands,United Kingdom,Austria,Belgium,Bulgaria,Germany,Greece,Slovenia,Italy
Call:  (FP7-ICT-2011-8, 2011)
Start date: 2012-10-01
End date: 2015-09-30
Duration (months): 36.0
Total project cost (EUR): 3738930.0
EU funding (EUR): 2899996.0
Participants: 9
Project status: CLOSED

weSPOT aims at propagating scientific inquiry as the approach for science learning and teaching in combination with today’s curricula and teaching practices. It lowers the threshold for linking everyday life with science teaching in schools by technology. weSPOT supports the meaningful contextualization of scientific concepts by relating them to personal curiosity, experiences, and reasoning. weSPOT addresses several challenges in the area of science learning and technology support for building personal conceptual knowledge. The project focuses on inquiry-based learning with a theoretically sound and technology supported personal inquiry approach. In inquiry based-learning learners take the role of an explorer and scientist and are motivated by their personal curiosity, guided by self-reflection, and develop knowledge personal and collaborative sense-making and reasoning. weSPOT will work on a meta-inquiry level in that it will (a) define a reference model for inquiry-based learning skills, (b) create a diagnostic instrument for measuring inquiry skills, and (c) implement a working environment that allows the easy linking of inquiry activities with school curricula and legacy systems. The foreseen weSPOT Toolkit gives smart support for personal scientific inquiry to address a lack of scientific inquiry skills in an age group of 12-25. Furthermore, weSPOT will unleash support of triggering and leveraging curiosity that is missing in today’s learning technology. weSPOT will develop (1) an open source service framework for inquiry workflows, (2) tools for mobile data collection and personal experience sampling. Additionally, it will develop (3) learning analytics tools for collaborative and personal reflection, and (4) a badge system for linking formal and informal learning activities via social media. These products will be customized and evaluated in at least 8 primary test-beds in a European wide approach in 8 European member states.

Keywords: inquiry-based learning,curiosity for stem
POWER SoC With Integrated PassivEs (POWERSWIPE)

Framework: FP7 — Cooperation
Programme: Information and Communication Technologies
Destination: Alternative Paths to Components and Systems
Action type: Collaborative project
Countries involved: Ireland,Germany,Austria,France,Spain,Germany,France
Call:  (FP7-ICT-2011-8, 2011)
Start date: 2012-10-01
End date: 2016-03-31
Duration (months): 42.0
Total project cost (EUR): 5123890.0
EU funding (EUR): 3295000.0
Participants: 7
Project status: CLOSED

Europe is a world leader in innovative automotive systems with competencies covering the full supply chain from the main OEMs (Audi, BMW, Daimler, Fiat, PSA, RSA, VW) to Tier1 suppliers (Bosch, Continental, Magneti Marelli) to leading semiconductor companies (Infineon, ST). The vision for electronic automotive control units in 2020 is that the battery will supply multi-core µControllers via multiple power supplies using an on-chip, granular power management system architecture, known as PowerSoC (Power Supply on Chip). The PowerSwipe proposal will address a key roadblock for PowerSoC by, for the first time, miniaturising and integrating state-of-the-art, high density trench capacitor substrate technology with novel thin film magnetics on silicon to deliver a multi-component LC (inductor-capacitor) interposer which will be combined, in a 3D heterogeneous stack, using eWLB technology, with the µController chip. To achieve this miniaturisation of the power passives, the switching frequency of the switched mode dc-dc converter needs to be increased from the traditional 1 to 5 MHz space (with 90%+ converter efficiency) into the 20MHz to 100MHz+ range, at which point the footprint of the power passives is comparable to the footprint of the individual on-chip DC-DC converter blocks (i.e. 1 to 2mm2). PowerSwipe will deliver a European supply chain for PowerSoC by addressing the challenges of system design, engineering, technology and manufacturability of integrated power management systems or PowerSoC (Power Supply on Chip) for nanoCMOS System on Chip (SOC).

Keywords: power system integration,power management,on-chip passives,power supply in package (psip),power supply on chip (psoc),manufacturability
Efficient Integrated Real-time Monitoring and Control of Drinking Water Networks (EFFINET)

Framework: FP7 — Cooperation
Programme: Information and Communication Technologies
Destination: ICT for a low carbon economy
Action type: Collaborative project
Countries involved: Spain,Spain,Italy,Cyprus,Germany
Call:  (FP7-ICT-2011-8, 2011)
Start date: 2012-10-01
End date: 2015-09-30
Duration (months): 36.0
Total project cost (EUR): 3145583.0
EU funding (EUR): 2192290.0
Participants: 10
Project status: CLOSED

This project addresses three main management problems in urban water system: optimal operational control, real-time monitoring and demand forecasting/management. Real-time optimal control deals with operating the main flow and pressure actuators to meet demands using the most sustainable sources and minimizing electricity costs and is tackled using stochastic model predictive control techniques. Real-time monitoring of water quantity and quality refers to the continuous detection and location of leakage and or water quality problems. It uses fault detection and diagnosis techniques. Demand forecasting and management is based on smart metering techniques and includes detailed modelling of consumption patterns as well as a service of communication to consumers. The project will provide an integrated software platform and two real-life pilot demonstrations in Barcelona (Spain) and Lemesos (Cyprus), respectively.

Keywords: efficient water management ict technologies decision support system amr real-time optimal control demand forecast network monitoring predictive models quality control distribution water network