Periodic Reporting for period 2 - Cross-CPP (Ecosystem for Services based on integrated Cross-sectorial Data Streams from multiple Cyber Physical Products and Open Data Sources) Reporting period: 2019-06-01 to 2021-02-28 Summary of the context and overall objectives of the project Key motivation of Cross-CPP project was 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 continuously. This enormous amount of data 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 applicationsIn contrast to sporadic proprietary CPP ecosystems, which are in most cases restricted to CPP manufacturer' specific services and which are not open for third parties interested in these CPP data, the Cross-CPP project focuses on what CPP and their sensor data can bring to the outside world. Therefore, Cross-CPP has solved above obstacles by establishing a CPP Big Data Ecosystem, which provides following main characteristics: • Brand independent concept, open for integration of diverse CPP data providers coming from different industrial areas, also providing a standardized common cross industrial CPP data model that 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 from the beginning of the project to the end of the period covered by the report and main results achieved so far Overview of the main results and their exploitation and dissemination:• Standardized Common Industrial Data Model (CIDM): One of the most important objectives of this project is to come up with a standardized common industrial data model. This model is flexible enough to incorporate data coming from various industrial sectors.A description and demonstrator video, as well as the specification of the CIDM is accessible via our public project library: https://www.cross-cpp.eu/library • Data Marketplace with Analytics Toolbox: The “One-Stop-Shop” Big Data Marketplace provides Service Providers with a single point of access to data streams from multiple mass products. The marketplace also offers a data analytics toolbox, which will provides easy to use big data analytic functionalities for Service Providers with low big data expertise and knowledge.A description and demonstrator video of the Marketplace and Toolbox, as well as detailed user and developer Guidelines on how to apply/use these tools can be found in our public project library: https://www.cross-cpp.eu/library • Cross Industrial Services: Cross industrial data streams are new information resources enabling new and innovative business ideas. In the scope of the Cross-CPP project, the consortium partners have developed innovative cross-sectorial services using the data streams available.Demonstrator videos of our three Service Providers Volkswagen, Siemens and Meteologix, describing innovative services build upon cross-sectorial data streams can be found in our public project library: https://www.cross-cpp.eu/library Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far) 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. The 3 pillars of the Cross-CPP Ecosystem The Cross-CPP Vision
