CHORUS Deliverable 3.3: Vision Document - Intermediate version

The goal of the CHORUS vision document is to create a high level vision on audio-visual search engines in order to give guidance to the future R&D work in this area (in line with the mandate of CHORUS as a Coordination Action). This current intermediate draft of the CHORUS vision document (D3.3) is based on the previous CHORUS vision documents D3.1 to D3.2 and on the results of the six CHORUS Think-Tank meetings held in March, September and November 2007 as well as in April, July and October 2008, and on the feedback from other CHORUS events. The outcome of the six Think-Thank meetings will not just be to the benefit of the participants which are stakeholders and experts from academia and industry – CHORUS, as a coordination action of the EC, will feed back the findings (see Summary) to the projects under its purview and, via its website, to the whole community working in the domain of AV content search. A few subjections of this deliverable are to be completed after the eights (and presumably last) Think-Tank meeting in spring 2009

CHORUS Deliverable 4.5: Report of the 3rd CHORUS Conference

The third and last CHORUS conference on Multimedia Search Engines took place from the 26th to the 27th of May 2009 in Brussels, Belgium. About 100 participants from 15 European countries, the US, Japan and Australia learned about the latest developments in the domain. An exhibition of 13 stands presented 16 research projects currently ongoing around the world

RoboChain: A Secure Data-Sharing Framework for Human-Robot Interaction

Robots have potential to revolutionize the way we interact with the world around us. One of their largest potentials is in the domain of mobile health where they can be used to facilitate clinical interventions. However, to accomplish this, robots need to have access to our private data in order to learn from these data and improve their interaction capabilities. Furthermore, to enhance this learning process, the knowledge sharing among multiple robot units is the natural step forward. However, to date, there is no well-established framework which allows for such data sharing while preserving the privacy of the users (e.g., the hospital patients). To this end, we introduce RoboChain - the first learning framework for secure, decentralized and computationally efficient data and model sharing among multiple robot units installed at multiple sites (e.g., hospitals). RoboChain builds upon and combines the latest advances in open data access and blockchain technologies, as well as machine learning. We illustrate this framework using the example of a clinical intervention conducted in a private network of hospitals. Specifically, we lay down the system architecture that allows multiple robot units, conducting the interventions at different hospitals, to perform efficient learning without compromising the data privacy.Comment: 7 pages, 6 figure

Fog Computing: A Taxonomy, Survey and Future Directions

In recent years, the number of Internet of Things (IoT) devices/sensors has increased to a great extent. To support the computational demand of real-time latency-sensitive applications of largely geo-distributed IoT devices/sensors, a new computing paradigm named "Fog computing" has been introduced. Generally, Fog computing resides closer to the IoT devices/sensors and extends the Cloud-based computing, storage and networking facilities. In this chapter, we comprehensively analyse the challenges in Fogs acting as an intermediate layer between IoT devices/ sensors and Cloud datacentres and review the current developments in this field. We present a taxonomy of Fog computing according to the identified challenges and its key features.We also map the existing works to the taxonomy in order to identify current research gaps in the area of Fog computing. Moreover, based on the observations, we propose future directions for research

Towards a secure service provisioning framework in a Smart city environment

© 2017 Elsevier B.V. Over the past few years the concept of Smart cities has emerged to transform urban areas into connected and well informed spaces. Services that make smart cities “smart” are curated by using data streams of smart cities i.e., inhabitants’ location information, digital engagement, transportation, environment and local government data. Accumulating and processing of these data streams raise security and privacy concerns at individual and community levels. Sizeable attempts have been made to ensure the security and privacy of inhabitants’ data. However, the security and privacy issues of smart cities are not only confined to inhabitants; service providers and local governments have their own reservations — service provider trust, reliability of the sensed data, and data ownership, to name a few. In this research we identified a comprehensive list of stakeholders and modelled their involvement in smart cities by using the Onion Model approach. Based on the model we present a security and privacy-aware framework for service provisioning in smart cities, namely the ‘Smart Secure Service Provisioning’ (SSServProv) Framework. Unlike previous attempts, our framework provides end-to-end security and privacy features for trustable data acquisition, transmission, processing and legitimate service provisioning. The proposed framework ensures inhabitants’ privacy, and also guarantees integrity of services. It also ensures that public data is never misused by malicious service providers. To demonstrate the efficacy of SSServProv we developed and tested core functionalities of authentication, authorisation and lightweight secure communication protocol for data acquisition and service provisioning. For various smart cities service provisioning scenarios we verified these protocols by an automated security verification tool called Scyther

Big data for monitoring educational systems

This report considers “how advances in big data are likely to transform the context and methodology of monitoring educational systems within a long-term perspective (10-30 years) and impact the evidence based policy development in the sector”, big data are “large amounts of different types of data produced with high velocity from a high number of various types of sources.” Five independent experts were commissioned by Ecorys, responding to themes of: students' privacy, educational equity and efficiency, student tracking, assessment and skills. The experts were asked to consider the “macro perspective on governance on educational systems at all levels from primary, secondary education and tertiary – the latter covering all aspects of tertiary from further, to higher, and to VET”, prioritising primary and secondary levels of education

The Elements of Big Data Value

This open access book presents the foundations of the Big Data research and innovation ecosystem and the associated enablers that facilitate delivering value from data for business and society. It provides insights into the key elements for research and innovation, technical architectures, business models, skills, and best practices to support the creation of data-driven solutions and organizations. The book is a compilation of selected high-quality chapters covering best practices, technologies, experiences, and practical recommendations on research and innovation for big data. The contributions are grouped into four parts: · Part I: Ecosystem Elements of Big Data Value focuses on establishing the big data value ecosystem using a holistic approach to make it attractive and valuable to all stakeholders. · Part II: Research and Innovation Elements of Big Data Value details the key technical and capability challenges to be addressed for delivering big data value. · Part III: Business, Policy, and Societal Elements of Big Data Value investigates the need to make more efficient use of big data and understanding that data is an asset that has significant potential for the economy and society. · Part IV: Emerging Elements of Big Data Value explores the critical elements to maximizing the future potential of big data value. Overall, readers are provided with insights which can support them in creating data-driven solutions, organizations, and productive data ecosystems. The material represents the results of a collective effort undertaken by the European data community as part of the Big Data Value Public-Private Partnership (PPP) between the European Commission and the Big Data Value Association (BDVA) to boost data-driven digital transformation

Data Spaces

This open access book aims to educate data space designers to understand what is required to create a successful data space. It explores cutting-edge theory, technologies, methodologies, and best practices for data spaces for both industrial and personal data and provides the reader with a basis for understanding the design, deployment, and future directions of data spaces. The book captures the early lessons and experience in creating data spaces. It arranges these contributions into three parts covering design, deployment, and future directions respectively. The first part explores the design space of data spaces. The single chapters detail the organisational design for data spaces, data platforms, data governance federated learning, personal data sharing, data marketplaces, and hybrid artificial intelligence for data spaces. The second part describes the use of data spaces within real-world deployments. Its chapters are co-authored with industry experts and include case studies of data spaces in sectors including industry 4.0, food safety, FinTech, health care, and energy. The third and final part details future directions for data spaces, including challenges and opportunities for common European data spaces and privacy-preserving techniques for trustworthy data sharing. The book is of interest to two primary audiences: first, researchers interested in data management and data sharing, and second, practitioners and industry experts engaged in data-driven systems where the sharing and exchange of data within an ecosystem are critical

BETWEEN FOOTPRINTS: BALANCING ENVIRONMENTAL SUSTAINABILITY AND PRIVACY IN SMART TOURISM DESTINATIONS

Data lies at the core of all smart tourism activities as tourists engage in different and personalized touristic services whilst the pre/during/post traveling or in holidays. From these interactions, a digital data trail is seamlessly captured in a technology embedded environment, and then mined and harnessed in the context of STD - Smart Tourist Destinations to create enriched, high-value experiences, namely those related to eco-responsibility, as well as granting destinations with competitive advantages. At the same time, these technologies enable tourism destinations for an optimization of the use natural resources and energy, as well as for the preservation of natural spaces, in short, reducing the “ecological footprint” of tourism. However, this comes with a cost, an increased “data footprint”. Therefore, the perceived enjoyment of experiences must be considered within the legal framework of Privacy and Data Protection by exposing inherent risks, analysing the available answers given by the GDPR – the General Data Protection Regulation of the European Union. Hence the purpose of this paper is i. to singularize the specificities of Smart Tourism Destinations; ii. to show how the principles of personal data protection, as set forth by the GDPR, are allocated within the STD realm; iii. and, finally, to derive potential legal implications of this ecosystem. Our approach is based on a legal analysis engaged in scholarship research. We have mostly denoted the underestimation of the legal implications of technology-enhanced tourism experiences, and the marginalization of both informed involvement and awareness by the individual in these processes. This study is novel in having undertaken an initial exploration of the legal implications of experiences taking place by STD.Los datos están en la base misma de todas las actividades turísticas inteligentes ya que los turistas se quedan inmersos en servicios distintos y personalizados antes/durante/después de los viajes o de las vacaciones.  De estas interacciones, un rastro es obtenido de un modo imperceptible a través de un medioambiente embutido en tecnología, el cual es a continuación extraído y almacenado en el contexto de los DTI - Destinos Turísticos Inteligentes para crear experiencias valiosas, señaladamente las relacionadas con la eco-responsabilidad, y bien así proporcionando ventajas competitivas a eses destinos. Asimismo, estas tecnologías permiten a los destinos turísticos una optimización del uso de los recursos naturales y de la energía, además de la preservación de los espacios naturales, en síntesis, reducen la “huella ecológica” del turismo. Sin embargo, esto tiene un coste, el incremento de la “huella de los datos”. Por ello, el disfrute apercibido de experiencias tendrá de ser tenido en cuenta en el marco normativo del RGPD – Reglamento General sobre Protección de Datos de la Unión Europea. Por ende, los objetivos de este artículo son los siguientes: i. identificar las especificidades de los Destinos Turísticos Inteligentes; ii. enseñar como los principios de la protección de datos, tal como están en el RGPD, son relevantes para los DTI; iii, en último lugar, evaluar las consecuencias jurídicas potenciales de este ecosistema. Nuestro enfoque se basa en un análisis jurídico de naturaleza académica. En especial, buscamos poner en evidencia como las implicaciones jurídicas de las experiencias turísticas reforzadas por las tecnologías han sido subestimadas, al igual que la participación informada y consciente de las personas en estos procesos. Este estudio es novedoso al haber emprendido una exploración inicial de las implicaciones jurídicas que resultan de experiencias que ocurren en los DTI.Os dados estão na base de todas as atividades turísticas inteligentes pois os turistas ficam envolvidos em serviços diferentes e personalizados antes/durante/depois das viagens ou das férias. Para estas interações, um rastro de dados é imperceptivelmente obtido por um meio ambiente embebido em tecnologia, sendo depois minerado e armazenado no contexto de Destinos Turísticos Inteligentes para criar experiências valiosas, designadamente relacionadas com a eco-responsabilidade, assim como facultando vantagens competitivas a tais destinos. Ao mesmo tempo, estas tecnologias permitem aos destinos turísticos uma otimização do uso de recursos naturais e da energia, assim como a preservação dos espaços naturais, em síntese, reduzindo a “pegada ecológica” do turismo. Porém, isto ocorre com um custo, o de uma “pegada de dados” acrescida. Consequentemente, a fruição apercebida de experiências tem de ser considerada no contexto normativo da Privacidade e da Proteção de Dados proteção de dados expondo os riscos potencias relacionados que lhe são inerentes, analisando as respostas das pelo RGPD - Regulamento Geral sobre Proteção de Dados da União Europeia. Assim, os objetivos do artigo são os seguintes: i. identificar as especificidades dos Destinos Turísticos Inteligentes; ii. mostrar como os princípios da proteção de dados, tal como constam do RGPD, são relevantes para os DTI; iii, finalmente, avaliar as consequências jurídicas potenciais deste ecossistema. A nossa perspectiva assenta numa análise jurídica de natureza académica. Sobretudo, procuramos mostrar como as implicações jurídicas das experiências turísticas reforçadas pelas tecnologias têm sido subestimadas, tal como o envolvimento informado e consciente das pessoas nestes processos. Este estudo é novo ao ter empreendido uma exploração inicial das implicações jurídicas que resultam das experiências que têm lugar nos DTI