Data has been termed to be the „oil of the 21st century“. Data will also be what the smart city of the future runs on. To make this a reality, cities need a platform where data from a variety of sources – IoT and sensor data, open government data, social media, and other 3rd party data providers – can be processed, linked, and analysed in order to extract valuable information that in turn can also be provided as linked open data, and with which new types of services are created and provisioned. Both cities as well as private service providers can build novel applications and services on top of this platform; the platform thus becomes an economically valuable driver for Smart City Innovation. The main goal of this project is to develop such a City Platform as a Service (CPaaS) that can be federated to support regional or even global applications, and that forms the basis for a smart city data infrastructure. Technical challenges that need to be addressed include data provenance, data quality, adaptive privacy levels, policies and adaptive processes for distributing and deploying processing intelligence to the cloud or to the edge. Other important aspects include data governance, data management and the empowerment of the citizen to control access and sharing of data about her using a MyData approach. In addition to the development of the platform, several use cases in the domains of event and transport management, water management, and health emergency services will be implemented and validated with cities in Europe and Japan. Blue prints – both from a technical as well as from a process perspective – for these domains that can easily be transferred and adapted from one region to another will be developed. This will for example allow transferring the learnings from the Asian Winter Games 2017 to the Tokyo Olympics 2020. And finally, the results from the project are used to develop standardisation proposals in the related areas to ensure impact beyond the project.

Urban environments are awash with data from fixed and mobile sensors and monitoring infrastructures from public, private, or industry sources. Making such data useful would enable developing novel big data applications to benefit the citizens of Europe in areas such as transportation, infrastructures, and crime prevention. Urban data is heterogeneous, noisy, and unlabeled, which severely reduces its usability. Succinctly stated, urban data are difficult to understand. The goal of the VaVel project is to radically advance our ability to use urban data in applications that can identify and address citizen needs and improve urban life. Our motivation comes from problems in urban transportation. This project will develop a general purpose framework for managing and mining multiple heterogeneous urban data streams for cities become more efficient, productive and resilient. The framework will be able to solve major issues that arise with urban transportation related data and are currently not dealt by existing stream management technologies. The project brings together two European cities that provide diverse large scale data of cross-country origin and real application needs, three major European companies in this space, and a strong group of researchers that have uniquely strong expertise in analyzing real-life urban data. VaVel aims at making fundamental advances in addressing the most critical inefficiencies of current (big) data management and stream frameworks to cope with emerging urban sensor data thus making European urban data more accessible and easy to use and enhancing European industries that use big data management and analytics. The consortium develops end-user driven concrete scenaria that are addressing real, important problems with the potential of enormous impact, and a large spectrum of technology requirements, thus enabling the realization of the fundamental capabilities required and the realistic evaluation of the success of our methods.

The Internet of Things offers an incredible innovation potential for developing smarter applications and services, transforming business models and impacting our society both positively. To be able to unlock IoT’s full potential many fundamental technological challenges still need to be solved. Today we see solutions in the development of vertical applications and services reflecting what used to be the early days of the web, leading to fragmentation and intra-nets of Things. To achieve an open IoT ecosystem of systems and platforms, several key enablers are needed: adaptive and scalable crawling, indexing, semantic data/service search and integration, privacy and security, combined with real world and large-scale enablers and products driven by innovative use-case scenarios and new business models. IoTCrawler will focus on integration and interoperability across different platforms, dynamic and reconfigurable solutions for discovery and integration of data and services from legacy and new systems, adaptive, privacy-aware and secure algorithms and mechanisms for crawling, indexing, search in distributed IoT systems. IoTCrawler will provide extensive development and demonstrations with a focus on Industry 4.0, Social IoT, Smart City and Smart Energy. IoTCrawler will seek to provide high impact through research excellence, innovation and technology advancement. It will address open challenges and issues in crawling, discovery, indexing, semantic integration and security/privacy/trust for an IoT ecosystem. IoTCrawler will achieve this through end-user engagement via its industry and city partners, trials and collaborative scenario developments, validations and show casing. IoTCrawler will also offer new business models and will extend the product line of industry and SME partners, and will create a wider awareness and third-party exploitation via dissemination and standardisation activities and by providing open and generic enablers and APIs.

Linked Data has gained significant momentum over the last years. It is now used at industrial scale in many sectors in which an increasingly large amount of rapidly changing data needs to be processed. HOBBIT is an ambitious project that aims to push the development of Big Linked Data (BLD) processing solutions by providing a family of industry-relevant benchmarks for the BLD value chain through a generic evaluation platform. We aim to make open deterministic benchmarks available to test the performance of existing systems and push the development of innovative industry-relevant solutions. The underlying data will mimic real industrial data assembled during the course of the project. At the beginning of the project, HOBBIT will work on roughly 1PB of real industry-relevant data from 4 different domains. The data will be extended through collaborations during the project. To push the use of the benchmarks, we will organize or join challenges that aim to measure the performance of technologies for the different steps of the BLD lifecycle. In contrast to existing benchmarks, we will provide modular and easily extensible benchmarks for all industry-relevant BLD processing steps that allow to assess whole suites of software that cover more than one step. The infrastructure necessary to run the evaluation campaigns will be made available. Our architecture will rely on web interfaces and cloud infrastructures to ensure scalability. The open HOBBIT platform will make human- and machine-readable, public periodic reports available. As exit strategy, the project will create an association after the second project year that will be sustained by the means of subscriptions from industry and academia and associated with existing benchmarking associations. The clear portfolio of added value for the members will be defined in the early project stages and disseminated throughout the evaluation campaigns.