CORDIS

Key motivation of Cross-CPP project is to give cross-sectorial industries access to the great spectrum of sensor data coming from high volume products from various industrial sectors (vehicles, smart home devices, etc.). With the increasing number of connected sensors and actuators within such mass products, this number will rise in short-term. This enormous amount of data continuously generated by mass products will represent:
- a NEW information resource to create new value, allowing the improvement of existing services or the establishment of diverse new cross-sectorial services, by combining data streams from various sources
- a major big data-driven business potential, not only for the manufacturers of Cyber Physical Products (CPP), but in particular also for cross-sectorial industries and various organisations with interdisciplinary applications

Cross-CPP project focuses on what CPP and their sensor data can bring to the outside world. Therefore, as key challenges, Cross-CPP has to overcome several obstacles by establishing a CPP Big Data Ecosystem, which should develop the following main characteristics:
- Brand independent concept, open for integration of diverse CPP data providers coming from different industrial areas, also providing a standardized cross industrial CPP data model which needs to be flexible enough to incorporate data coming from various industrial sectors.
- CPP Big Data marketplace providing to service providers a single CPP data access point with just one interface (one-stop-shop), as well as support functionalities for easy data mining/analytics. By these means, data customers (Service Providers) just need to set-up and maintain one interface to gather diverse CPP data from different CPP providers.
- Controlled access to diverse CPP data streams and optimal management of data ownership and data rights, applicable to various cross CPP data streams.

Work performed and results achieved so far:
- Cross-CPP Ecosystem definition: Industrial Requirements Analysis, (public) innovation concept, see 3 pillars of the Cross-CPP Ecosystem
- CPP Ecosystem with Big Data Marketplace: First Prototypes of Data Harvesting & Company Backend components, first prototype of Big Data Marketplace
- Agreed data model and context model: specification and first prototype of a shared system of entity identifiers; definition of a common data model to structure data belonging to different CPP from different industrial sectors; specification of a context model to capture relevant information from the CPP's context.
- Data analytics toolbox: First prototype of a big data analytis that will allow to the different service providers/vendors to have access to an integrated solution to process the data and apply the different analytical models
- Context sensitive privacy, security & ethics rules: Specification and first prototype of the proposed security framework for the Cross-CPP Ecosystem and the cross sectorial services
- Cross-sectorial services: Specification and first prototype of a set of reference services based using CPP data provided by the CPP Ecosystem

Cross-CPP will directly contribute to impacts set in the Work programme under the challenge Topic ICT-14-2016-2017: Big Data PPP: cross-sectorial and cross-lingual data integration and experimentation. The project concept is designed to provide benefits for industrial partners on both short and long term. On short term, the industrial partners will receive an innovative Ecosystem to ingrate data streaming from their products and toolbox with data analytics, as well as context modelling and extraction tools to support development of new services; the solution offers an open market for building services based on integrated data to high number of service providers, especially SMEs; on the long term, the Ecosystem and the Marketplace will be open for integration of data from other manufacturers of mass CPP in the same (automotive, home automation) or different sectors, opening new business possibilities among manufacturers from various sectors and service providers.

Benefiting communities: The communities most likely to benefit from the Cross-CPP results are: a) initially industrial manufactures of CPP – industrial vendors, b) services providers (service departments by CPP vendors themselves, but also external service providers, and particularly SMEs such as ML in the Cross-CPP consortium, c) SW providers particularly (such as ATOS) which may support the data trading over the Marketplace, data pre-processing, integration, analytics, visualisation etc. Within the requirements analysis phase, the consortium will analyse the needs of different communities.

Multi-sectorial potentials and transfer: By solving the critical problems related to integration of data streams from various products, the project will provide new opportunities for cross-sectorial cooperation among the CPP manufacturers. Cross-CPP is one of the first attempt to allow for cooperation among manufactures from very different sectors, opening new business models for both CPP manufacturers and service providers. The big advantage of the proposed solution is that it allows for various forms of cooperation among manufacturers from same or different sectors (where there is no direct competition on selling products), i.e. offering win-win situation for all stakeholders: CPP vendors, service providers, users of CPP.

Socio-economic impact: Big Data Analytics opens new opportunities to classical manufacturing industry. Many companies in these sectors still have not started to fully use the advantages of this technology. Cross-CPP is likely to bring impart contribution to overwhelming reluctance of many traditional companies to extend their business to trading with data and extend their products with services based on analytics of large volumes of data streaming from their products. Therefore, the encompassing and brand-neutral and cross sectorial Cross-CPP approach, which is based on the Agreed CPP Data Model, offers plenty of opportunities as incubator for cross-sectorial applications and services. This enhanced information, and ability to react dynamically to changes in the market landscape will enable smaller businesses to compete more effectively with larger and more-established ones, having reduced the 'barriers to entry' to the market. The total number of jobs created is expected to be 300,000 over the next five years in the EU as a result of business start-ups and increased demand for data-specific roles.

European Added Value: Cross-CPP addresses the urgent need of the European industry of easier generation of services based on data streams generated by CPP, which is of urgency for industry all over Europe, both in large and in small companies, manufacturers of CPP and service suppliers, especially SMEs. Therefore, the expected results are required by the EU as a whole, i.e. they are not specifically needed by just certain countries or regions. The objective is to provide cross-sectorial and cross border services using data from various vendors and offering the