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.
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 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.
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. The objective is to provide cross-sectorial and cross border services using data from various vendors and offering these services to customers world-wide. All industrial partners and service provider in the consortium have customers, subsidiaries and/or suppliers in many countries.
