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Coordinated approach for establishing data spaces to live up to European ambitions for a thriving data economy The position paper "Design Principles for Data Spaces" underlines the importance of data spaces and though the sovereign sharing of data in creating the future data economy. It is the first approach to define the design principles for data spaces, agreements on the building blocks for a soft infrastructure and governance for data spaces. In February 2020, the European Commission announced the European Strategy for Data, aiming at creating a single market for data to be shared and exchanged across sectors efficiently and securely within the EU. Behind this endeavour stands the Commission's goal to get ahead with the European data economy in a way that fits European values of self-determination, privacy, transparency, security and fair competition. For this to achieve, the rules of accessing and using data must be fair, clear and practicable. This is especially important as the European data economy continues to grow rapidly – from 301 billion euros (2,4 % of GDP) in 2018 to an estimated 829 billion euros (5,8 % of GDP) by 2025. The centrepiece of the European Data Strategy is the concept of "data spaces", for which the Commission defined nine initial domains, all driven by sector-specific requirements. From a technical perspective, a data space can be seen as a data integration concept which does not require common database schemas and physical data integration, but is rather based on distributed data stores and integration on an "as needed" basis on a semantic level. Abstracted from this technical definition, a data space can be defined as a federated data ecosystem within a certain application domain and based on shared policies and rules. The users of such data spaces are enabled to access data in a secure, transparent, trusted, easy and unified fashion. These access and usage right can only be granted by those persons or organisations who are entitled to dispose of the data. As individuals and ...

[EN] The maritime industry expects several improvements to efficiently manage the operation processes by introducing Industry 4.0 enabling technologies. Seaports are the most critical point in the maritime logistics chain because of its multimodal and complex nature. Consequently, coordinated communication among any seaport stakeholders is vital to improving their operations. Currently, Electronic Data Interchange (EDI) and Port Community Systems (PCS), as primary enablers of digital seaports, have demonstrated their limitations to interchange information on time, accurately, efficiently, and securely, causing high operation costs, low resource management, and low performance. For these reasons, this contribution presents the Seaport Data Space (SDS) based on the Industrial Data Space (IDS) reference architecture model to enable a secure data sharing space and promote an intelligent transport multimodal terminal. Each seaport stakeholders implements the IDS connector to take part in the SDS and share their data. On top of SDS, a Big Data architecture is integrated to manage the massive data shared in the SDS and extract useful information to improve the decision-making. The architecture has been evaluated by enabling a port authority and a container terminal to share its data with a shipping company. As a result, several Key Performance Indicators (KPIs) have been developed by using the Big Data architecture functionalities. The KPIs have been shown in a dashboard to allow easy interpretability of results for planning vessel operations. The SDS environment may improve the communication between stakeholders by reducing the transaction costs, enhancing the quality of information, and exhibiting effectiveness ; This work was supported in part by the European Union's Horizon 2020 Research and Innovation Programme through the PIXEL Port Project under Grant 769355, and in part by the Secretaria Nacional de Educacion Superior, Ciencia, Tecnologia e Innovacion (SENESCYT), Ecuador ; Sarabia-Jácome, D.; Palau Salvador, ...

4372 4382 8 ; S ; [EN] The maritime industry expects several improvements to efficiently manage the operation processes by introducing Industry 4.0 enabling technologies. Seaports are the most critical point in the maritime logistics chain because of its multimodal and complex nature. Consequently, coordinated communication among any seaport stakeholders is vital to improving their operations. Currently, Electronic Data Interchange (EDI) and Port Community Systems (PCS), as primary enablers of digital seaports, have demonstrated their limitations to interchange information on time, accurately, efficiently, and securely, causing high operation costs, low resource management, and low performance. For these reasons, this contribution presents the Seaport Data Space (SDS) based on the Industrial Data Space (IDS) reference architecture model to enable a secure data sharing space and promote an intelligent transport multimodal terminal. Each seaport stakeholders implements the IDS connector to take part in the SDS and share their data. On top of SDS, a Big Data architecture is integrated to manage the massive data shared in the SDS and extract useful information to improve the decision-making. The architecture has been evaluated by enabling a port authority and a container terminal to share its data with a shipping company. As a result, several Key Performance Indicators (KPIs) have been developed by using the Big Data architecture functionalities. The KPIs have been shown in a dashboard to allow easy interpretability of results for planning vessel operations. The SDS environment may improve the communication between stakeholders by reducing the transaction costs, enhancing the quality of information, and exhibiting effectiveness This work was supported in part by the European Union's Horizon 2020 Research and Innovation Programme through the PIXEL Port Project under Grant 769355, and in part by the Secretaria Nacional de Educacion Superior, Ciencia, Tecnologia e Innovacion (SENESCYT), Ecuador Sarabia-Jácome, D.; ...

Science Europe welcomes that the European Commission intends improve cross-sectoral data access, not only for the economic sector, but also for research and innovation. Data from all sectors have cross-cutting value for R&I and consequently for society at large. In its response to the EC Roadmap for an upcoming legislative proposal on the governance of common European data spaces Science Europe reinforces the need to consider sectoral policies to ensure coherence.

Stellenausschreibung des Leibniz-Instituts für Sozialwissenschaften in Mannheim. Deadline: 12. Juni 2024

The availability of timely, accessible and well documented data plays a central role in the process of digital transformation in our societies and businesses. Considering this, the European Commission has established an ambitious agenda that aims to leverage on the favourable technological and political context and build a society that is empowered by data-driven innovation. Within this context, geospatial data remains critically important for many businesses and public services. The process of establishing Spatial Data Infrastructures (SDIs) in response to the legal provisions of the European Union INSPIRE Directive has a long history. While INSPIRE focuses mainly on &rsquo ; unlocking&rsquo ; data from the public sector, there is need to address emerging technological trends, and consider the role of other actors such as the private sector and citizen science initiatives. The objective of this paper, given those bounding conditions is twofold. Firstly, we position SDI-related developments in Europe within the broader context of the current political and technological scenery. In doing so, we pay particular attention to relevant technological developments and emerging trends that we see as enablers for the evolution of European SDIs. Secondly, we propose a high level concept of a pan-European (geo)data space with a 10-year horizon in mind. We do this by considering today&rsquo ; s technology while trying to adopt an evolutionary approach with developments that are incremental to contemporary SDIs.