ATRIUM will exploit and strengthen complementarities between leading Εuropean infrastructures: DARIAH, ARIADNE, CLARIN and OPERAS in order to provide vastly improved access to a rich portfolio of state-of-the-art services available to researchers across countries, languages, domains and media, building on a shared understanding and interoperability principles established in the SSHOC cluster project and other previous collaborations. Research infrastructures in the Arts and Humanities domain must cater to a very wide range of stakeholders and offer services that cut across discipline-specific boundaries.

ATRIUM will tackle this heterogeneity within the Arts and Humanities by going deep and wide at the same time: on the one hand, ATRIUM will make a groundbreaking contribution to the consolidation and expansion of services, including data services, specifically in the field of archaeology, while, on the other hand, facilitating access to a wide array of essential text, image and sound-based services that benefit a number of other disciplines within the Arts and Humanities, and cover all phases of the research data lifecycle (creating, processing, analyzing, preserving, providing access to and reusing).

Athena’s contribution

Athena (ILSP and IMSI) participates in the following tasks, coupled with the relevant demonstrators:

  • speech recognition on non-native English speech and noisy/low-quality recordings,
  • application of automatic linguistic processing workflows (tokenization, PoS tagging lemmatization, and named entity recognition on the transcribed spoken data produced),
  • overview of data and metadata formats, schemas, ontologies and controlled vocabularies used in the Arts & Humanities domain, aiming at semantic interoperability between catalogues and repositories,
  • metadata harmonisation and enrichment – geotagging of texts and collaborative reusable map annotation,
  • ontology-driven extraction of work processes from published articles in Archaeology and other Humanities fields.

Additionally, Athena undertakes a significant activity which aims to facilitate access to research facilities in the Art and Humanities with a complimentary offer of advanced technologies and local expertise; to enhance researcher mobility and cross-disciplinary knowledge transfer of best practices throughout Europe; and to provide specific transnational training and access linked to the new types of Arts and Humanities data showcased in the project.

Status
Active
Type
European
Partners

Archeologický ústav AV ČR, Brno, v. v. i. / Institute of Archaeology of the Czech Academy of Sciences, Brno  

 

Archeologický ústav AV ČR, Praha, v. v. i. / Institute of Archaeology of the Czech Academy of Sciences, Prague  

 

ARIADNE Research Infrastructure  

 

Athena Research Centre  

 

Athens University of Economics and Business  

 

Centar Za Digitalne Humanisticke Nauke / Belgrade Center for Digital Humanities  

 

Common Language Resources and Technology Infrastructure (CLARIN ERIC)  

 

Consiglio Nazionale delle Ricerche – National Research Council (CNR)  

 

Digital Research Infrastructure for the Arts and Humanities (DARIAH ERIC)  

 

Foundation for Research and Technology Hellas (FORTH)

Foxcub  

 

Institut National De Recherche Eninformatique et Automatique (INRIA)  

 

Instytut Chemii Bioorganicznej Polskiej Akademii Nauk / Institute of Bioorganic Chemistry of the Polish Academy of Sciences  

 

Laboratório Nacional de Engenharia Civil (LNEC) / National Laboratory for Civil Engineering  

 

Ludwig-Maximilians-Universität München  

 

NET7 SRL  

 

Open Access in the European Area through Scholarly Communication  

 

Österreichische Akademie der Wissenschaften  

 

PIN S.c.r.l. – Servizi didattici e scientifici per l’Università di Firenze / Educational and Scientific Services for the University of Florence  

 

Prisma Cultura S.r.l.

Radboud University  

 

The Cyprus Institute Limited  

 

Université de Tours  

 

University of Gothenburg  

 

University of Sheffield  

 

University of South Wales  

 

University of York  

 

Univerzita Karlova

ARGUS

Non-destructive, scalable, smart monitoring of remote cultural treasures

Embarking on a Groundbreaking Odyssey: The ARGUS Project Takes Flight. December 2023 marks the commencement of an ambitious and pioneering venture as we proudly announce the launch of the ARGUS project. Focused on the intersection of cutting-edge technology, cultural heritage preservation, and climate change mitigation, ARGUS aims to revolutionize the landscape of remote heritage asset management.

The ARGUS team is set to embark on a 3-year journey of innovation and discovery. The project’s mission is to develop and implement advanced solutions that will redefine how we safeguard and manage heritage assets in diverse locations, from the historic island of Delos in Greece, a UNESCO World Heritage site since 1990, to the rural charm of the cellar town of Baltanás in North Spain, the serene Monti Lucretili upland landscape in Italy, the sacred walls of the Abbey of Sant’Antonio di Ranverso, Italy, and the majestic Schenkenberg Castle in Switzerland.

The project’s multifaceted approach includes cutting-edge technology integration, data-driven decision support systems, and collaboration with local communities and experts. Through its five pilot studies—including Delos Island’s ancient ruins, Baltanás’s subterranean architecture, Monti Lucretili’s natural beauty, Sant’Antonio di Ranverso’s monastic heritage, and Schenkenberg Castle’s medieval fortifications—ARGUS will address unique challenges posed by different cultural and environmental contexts.

ARGUS is made possible through the support of the Horizon Europe program. As the project unfolds, regular updates and insights into its progress will be shared with the public, stakeholders, and the wider scientific community.

The widespread use of sensor and IoT devices is generating huge volumes of time series data in various industries like finance, energy, factories, medicine, manufacturing and others. Industries use these data for monitoring, but their main potential is still untapped. Existing techniques and software for time series management do not provide tools sufficiently scalable and sophisticated for managing the huge volumes of data or adequate forecasting, prediction and diagnostics.
MORE will create a platform that will address the technical challenges in time series and stream management, focusing on the RES industry. MORE’s platform will introduce an architecture that combines edge computing and cloud computing to be able to guarantee both responsiveness and provide sophisticated analytics simultaneously. This architecture will be combined with the usage of time series summarization techniques, or as we more accurately term them in MORE, modelling techniques for sensor data. Models are any compressed representations that allow the reconstruction of the original data points of a time series (e.g. a linear function) within a known error-bound (possibly zero). This approach has synergies with the edge computing approach, since summarization can be done at the edge, reducing the load in the whole data processing pipeline.
MORE will introduce advanced analytics tools for prediction, forecasting and diagnostics based on two technological directions: machine learning and pattern extraction, with emphasis to motifs, which is the state-of-the-art for time series. MORE will adjust these techniques to work directly on models of data, thus enabling them to scale beyond state-of-the-art. The ability to ingest huge volumes of data will have an important impact to the accuracy of the prediction and diagnostics models.
Status
Active
Type
European
Partners
AAU
INACCESS
IBM-IE
PERD
Laborelec
MOD

ENERMAN envisions the factory as a living organism that can manage its energy consumption in an autonomous way. It will create an Energy sustainability management framework collecting data from the factory and holistically process them to create dedicated energy sustainability metrics. These values will be used to predict energy trends using industrial processes, equipment and energy cost models. ENERMAN will deliver an autonomous, intelligent decision support engine that will evaluate the predicted trends and access if they match predefined energy consumption sustainability KPIs. If the KPIs are not met, ENERMAN will suggest and implement changes in energy affected production lines control processes: an energy aware flexible control loop on various factory processes will be deployed. The ENERMAN administrators will be able to use the above mechanisms in order to identify how future changes in the production lines can impact energy sustainability using the ENERMAN prediction engine (based on digital twins) to visualize possible sustainability results when in-factory changes are made in equipment, production line. The ENERMAN digital twin will predict the economic cost of the consumed energy based on the collected and predicted Energy Peak load tariff, Renewable Energy System self-production, the variations in demand response, possible virtual generation and prosumer aggregation. Finally, ENERMAN considers the operators actions within the production chain as part of a factory’s energy fingerprint since their activity within the factory impacts the various production lines. In ENERMAN, we include a training mechanism with suggested personnel good practices for energy sustainability improvement through the production lines. Current and predicted energy consumption/sustainability trends on specific assets of the factory are collected and visualized in a Virtual, eXtended reality model of the factory to enhance the situational energy awareness of the factory personnel.

Status
Active
Type
European
During the past decade, the European cybersecurity landscape has evolved on the fragmented grounds of differing national priorities, and was lacking major projects possessing a technological and economical “lighthouse effect” for a long time. With the Horizon 2020 (H2020) programme, the EU has created opportunities for such strategic projects. One of the major interests of the European Union is to secure its digital economy, infrastructures, society and democracy.
 
CONCORDIA is one of four H2020 pilot projects that have been launched in order to support this aim. More specifically, CONCORDIA is a four-year, multi-disciplinary research and innovation project, launched in January 2019. 
 
CONCORDIA has the following objectives:
  1. Position the CONCORDIA ecosystem, a Cybersecurity Competence Network with leading research, technology, industrial and public competences to build the European Secure, Resilient and Trusted Ecosystem, with the CODE research center as coordinator and hub, and ENISA as secretary.
  2. Using an open, agile and adaptive governance model and processes.
  3. Devise a cybersecurity roadmap to identify powerful research paradigms, to do hands-on experimental validation, prototype and solution development in an agile way to quickly identify successful but also unsuccessful potential product development.
  4. Develop next-generation cybersecurity solutions by taking a holistic end-to-end data-driven approach from data acquisition, data transport and data usage, and addressing device-centric, network-centric, software- and system-centric, data- and application-centric and user-centric security.
  5. Scale up existing research and innovation with CONCORDIA’s virtual lab and services.
  6. Identify marketable solutions and grow pioneering techniques towards fully developing their transformative potential.
  7. Develop sector-specific (vertical) and cross-sector (horizontal) industrial pilots with building incubators.
  8. Launch Open Calls to allow entrepreneurs and individuals to stress their solutions with the development.
  9. Set up an Advisory Board, comprised by leaders of industry, standardization, policy and politics to give strategic advice and also to connect with possible clients and users of the developed solutions, other projects and research initiatives, as well as important standardization and certification institutions.
  10. Mediate between multiple communities: Different communities have different priorities and perspectives.
  11. Establish an European Education Ecosystem for Cybersecurity. CONCORDIA, therefore, extends traditional training courses with new virtual courses (MOOCs and SPOCs) and a variety of outreach activities, including high-school curricula development, competitions, cyber ranges.
  12. Provide expertise to European policy makers and industry.
'
Status
Active
Type
European

nIoVe

A novel Adaptive Cybersecurity Framework for the Internet-of-Vehicles
nIoVe aims to deploy a novel multi-layered interoperable cybersecurity solution for the Internet-of-Vehicles (IoV), with emphasis of the Connected and Autonomous Vehicles (CAVs) ecosystem by employing an advanced cybersecurity system enabling all relevant stakeholders and incident response teams to share cyber threat intelligence, synchronize and coordinate their cybersecurity strategies, response and recovery activities. To do so the project develops a set of in-vehicle and V2X data collectors that will feed nIoVe’s machine learning platform and tools for threat analysis and situational awareness across the IoV ecosystem. Advanced visual and data analytics are further enhanced and adapted to boost cyberthreat detection performance under complex attack scenarios, while IoV stakeholders are jointly engaged in incident response activities through trusted mechanisms. The proposed approach is supported by interoperable data exchange between existing and newly proposed cybersecurity tools. nIoVe solution will be demonstrated and validated in 3 pilots: Hybrid execution environment, simulated environment and real-world conditions.
 
Overall, nIoVe ambitiously expects to (i) reduce the attack surface of the overall IoV ecosystem, (ii) showcase effective and real-time detection of novel advanced threats and cyber-attacks in IoV ecosystems; (iii) reduce substantially the response time and reduce drastically the impact of breaches; (iv) contribute to the establishment and sustainable operation of Computer Security Incident Response Teams (CSIRTs) stimulating information and knowledge sharing across the IoV ecosystem; and (v) paves the way for the next generation robust, scalable and resilient IoV infrastructure. nIoVe draws and builds upon the accumulated experience from its consortium consisted of 13 partners from 6 European countries and Israel, will implement the project, which is organized in 8 workpackages and will be completed within 36 months.
'
Status
Active
Type
European

European Language Equality (ELE) is a pilot project aiming to draw up a sustainable evidence-based strategic research agenda and roadmap, setting out actions, processes, tools and actors, to achieve full digital language equality of all languages (official or otherwise) used within the Union through the effective use of language technologies. The research agenda will lay out the current state of language technologies and language equality within the Union and give a detailed picture of the desired situation that is needed to achieve digital language equality. The roadmap will then provide the path and the means needed to implement the agenda and ensure that digital language equality becomes a reality by 2030.

IntelComp

A Competitive Intelligence Cloud/HPC Platform for AI-based STI Policy Making
IntelComp sets out to build an innovative Cloud Platform that will offer Artificial Intelligence based services to public administrators and policy makers across Europe for data- and evidence-driven policy design and implementation in the field of Science, Technology and Innovation (STI) policy. Large STI datasets are processed on High Performance Computing (HPC) environment part of the European Open Science Cloud (EOSC) imitative. Public administration at all geographical and organizational levels, STI stakeholders and civil society produce a great amount of dynamic, multilingual and heterogeneous data (i.e. national STI strategies, plans and work programmes, calls, projects, reports, scientific publications, patents, dissemination articles, etc.), so understanding and analyzing this data is crucial for evidence-based policy making. The objective of IntelComp is to deliver a platform that provides tools for assisting the whole spectrum of STI policy, i.e., agenda setting, modeling design, implementation, monitoring and evaluation. It will do so by involving multi-disciplinary teams to co-develop innovative analytics services, Natural Language Processing pipelines and Artificial Intelligence workflows and by exploiting open data, services and computational resources from the EOSC, HPC environments and federated distributed operations at the European Union, national and regional level. It will ensure a cooperative environment where different actors can visualize, interact and analyze information. Through co-creation, IntelComp will adopt a living labs approach and will engage public policy makers, academia, industry, SMEs, local actors, civil society and citizens to explore, experiment with and evaluate STI policies at all stages. IntelComp will be targeting domains aligned with the European Agenda and the Horizon Europe Missions: Artificial Intelligence, Climate Change and Health.

This project will create a tool to improve Deaf / hearing communication by developing technology to automatically translate sign languages into spoken or written language and vice versa. It will not be limited to a single spoken/signed language pair, but will be able to translate among multiple signed and spoken languages within the EU domain. The design of the app will be user-driven, while exhaustive evaluation procedures will be carried out by different stakeholders.
Using the app, Deaf users will be able to use their web cams to sign to a hearing user. Hearing users will be able to read the translation of the signed communication as text or hear the translation as speech. Hearing users will be able to speak or type into the app and Deaf users will be able to see the translation signed by an avatar that goes significantly beyond the state-of-the-art by incorporating a number of innovative grammatical and pragmatic features that convey more of the communicative information of the translated message than was previously possible.
For the purposes of the app development, state-of-the-art machine translation technologies will exploit a significant amount of structured European sign language resources along with unstructured big data of sign language videos from less resourced sign languages.
Moreover, in addition to the mobile app, other project outcomes will be a set of computer-assisted (human) interpretation tools, computer vision based language analysis tools and corpora building tools. These last two will assist users of under-resourced signed languages to develop additional corpora for use in the sign language technology pipeline that is at the core of the mobile app.

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