With the increase of criticality level of the GPS applications, products manufacturers and developers are now requesting a relevant mean to predict performances and reliability of their future applications. Often SMEs have ideas that sometimes cannot be implemented because they depend on the availability of data resources or specialised tools that are too expensive to obtain.
In this context, GAPFILLER project aims at filling the gap between big manufacturers and SMEs by providing the researchers and developers’ community with a unique extensible data pool enabling performances prediction and simulation of new Global Navigation Satellite System (GNSS) based applications and algorithms. GAPFILLER consortium aim is to create quality content and innovative services and to allow people to access and use online content and services across GNSS technologies barriers.
The main objective of the GAPFILLER project is to define, build and disseminate a powerful data pool of worldwide GNSS measurements enabling low cost tests campaigns, performances predictions and simulations of new GNSS based applications. Main targeted benefits are:

• The development of an innovative use of a common GNSS database for performances assessment that will drastically reduce the cost of tests campaigns and certification process.
• The adaptation of the EGNOS aeronautical integrity concept to new application domains that will allow SMEs to gain the know-how for exploiting it and getting competitive advantage.
• The knowledge transfer between technology providers/data brokers and content providers (especially SMEs) boosting development speed of EGNOS and GALILEO services.

By promoting adoption of EGNOS and emergence of a new data economy related to GALILEO, the consortium will maximize the Return Of Investment of one of the most important budget line of the European Commission that has already plan to invest 3.4 billion Euros for the implementation and launch of the GALILEO satellites constellation.

GPS positioning devices are becoming a commodity sensor platform with the emergence and popularity of smartphones and ubiquitous networking. While the positioning capability has been exploited in location-based services, so has its spatiotemporal cousin, tracking, so far only been considered in costly and complex fleet management applications.
The proposed project, SimpleFleet will make it easy for SMEs, both, from a technological and business perspective, to create (Mobile) Web-based fleet management applications. For this purpose, we build a large data pool comprising base data such as maps and traffic data from dedicated providers. A simple interface will provide a means to connect user-contributed data streams to this pool. In addition and to increase the market potential of the data pool, we also want to address the related geomarketing domain, which uses travel information in various geo-statistical analysis methods as well as visualizations of the data to be used in online
and print publications.
An algorithmic framework dubbed “TrafficIntelligence” that includes map-matching algorithms, vehicle routing services and a statistics package will utilize the collected data and provide value-added service. SMEs will be able to access the data and services by means of a Web-based API, a Software Development Kit (SDK) wrapping API access for specific languages and environments and Application Frameworks for rapid application development for target platforms such as Web (JavaScript), and iPhone and Android mobile platforms.
GPS positioning devices are becoming a commodity sensor platform with the emergence and popularity of smartphones and ubiquitous networking. While the positioning capability has been exploited in location-based services, so has its spatiotemporal cousin, tracking, so far only been considered in costly and complex fleet management applications. The proposed project, SimpleFleet will make it easy for SMEs, both, from a technological and business perspective, to create (Mobile) Web-based fleet management applications. For this purpose, we build a large data pool comprising base data such as maps and traffic data from dedicated providers. A simple interface will provide a means to connect user-contributed data streams to this pool. In addition and to increase the market potential of the data pool, we also want to address the related geomarketing domain, which uses travel information in various geo-statistical analysis methods as well as visualizations of the data to be used in online and print publications. An algorithmic framework dubbed “TrafficIntelligence” that includes map-matching algorithms, vehicle routing services and a statistics package will utilize the collected data and provide value-added service. SMEs will be able to access the data and services by means of a Web-based API, a Software Development Kit (SDK) wrapping API access for specific languages and environments and Application Frameworks for rapid application development for target platforms such as Web (JavaScript), and iPhone and Android mobile platforms.

The design of wind farms is a complex task with the optimal siting of each wind turbine as the most critical aspect for the productivity of the farm. There are a number of data which are critical to determine the best location of a wind farm. Among them there are the wind potential of a region, local environment characteristics, potential interference on communication systems, visual impact, the existence of archaeological sites, socio‐economic factors, etc. The data to evaluate the above‐mentioned issues come from different sources such as public administrations and private companies, with different approaches and interests, and data of different formats and nature. This is usually a handicap for SMEs that have to consider all these collateral but crucial aspects.
The main objective of SOPCAWIND is to create new services and products for SMEs based on the development of a software tool being able to optimise the location for a wind farm based on a large and heterogeneous set of data containing information from different fields (weather, geography, environment, archaeology, radiocommunications and socialeconomy), that will be treated, converted, validated, and maintained for this purpose.

Nowadays it has become common practice to take digital images of thin slices of biopsies that are obtained for studying the composition of cells, glands, tissues and organs, and the possible pathologies that may affect them. These images are of high interest in medical diagnostics, research and education.
Pathology departments in hospitals and Biobanks are usually the facilities that provide archived biological samples for use in life sciences. They manage the tissue samples, the associated digital images and other complementary digital data (health information such as pathologies or treatments followed by the patient). Although most of the pathology departments and biobanks adequately capture and store digital images of the different biologic materials, it is not so usual for biobanks to adequately associate the representative health information to the digital images of their samples and it is even less usual sharing these images in a network. So, the digital images are usually spread all over different systems stored in different formats, databases and facilities belonging to different types of institutions and they are not easily identifiable and reachable. This creates a difficult environment for sharing and reusing this type of data between different interested organisations.
The BIOPOOL consortium project has been created to carry out a new approach, that arises from the need of pathology departments and biobanks of sharing, exchanging, processing, understanding and exploiting the digital histology images and the data associated to the biologic material stored in these institutions. The project will develop the needed technology to extract and gather this digital information from different pools, analyse it, and being able to compare it and to score images similar to one provided as a search pattern based on an innovative Content Based Image Retrieval (CBIR) system capable of searching histological images using different mixed text and image queries. BIOPOOL will establish a complete intelligent biobank and pathology department network, building a constructive basis for pan-European cooperation in diagnosis and medical research.
Seven partners from four different countries collaborate together in BIOPOOL. A great effort is done by the SMEs within this consortium project. The results coming from BIOPOOL will be translated into new services and products using the technologies and data pools provided by the other organisations allowing more precise actuations in digital pathology, especially in diagnosis.
 

PortDial will set up a platform for creating, cleaning-up and publishing multilingual domain ontologies and grammars for prototyping of spoken dialogue systems in the domains of entertainment, banking and customer service. The platform will enable rapid and cost-effective porting of voice applications into new domains and languages, serving in particular the SMEs in the mobile application development industry, but also the research community.

Linked Open Data (LOD) shows enormous potential in becoming the next big evolutionary step of the WWW. However, this potential remains largely untapped due to missing usage and commercialisation strategies.
CODE’s vision is to establish the foundation for a web-based, commercially oriented ecosystem for Linked Open Data. This ecosystem establishes a sustainable and commercial value-creation-chain among traditional (e.g. data provider and consumer) and non-traditional (e.g. data analyst) roles in data marketplaces. Monetary incentives will motivate people to analyse, organise and integrate LOD with unstructured information sources thereby increasing data quality and quantity.
Our use case focuses on research papers as a source for mining facts and their integration into LOD repositories and light-weight ontologies. Hence, we will leverage the wealth of knowledge contained in research publications on a semantic, machine-readable level by creating the Linked Science Data cloud. This cloud will have an impact on innovation driven businesses by making scientific knowledge more accessible and transparent.
Therefore, we will research and develop:

1. crowd-sourcing enabled semantic enrichment & integration techniques for integrating facts contained in unstructured information into the LOD cloud
2. federated, provenance-enabled querying methods for fact discovery in LOD repositories
3. web-based visual analysis interfaces to support human based analysis, integration and organisation of facts
4. socio-economic factors - roles, revenue-models and value chains - realisable in the envisioned ecosystem.