ERCIM News 133
April 2023
Special theme Data Infrastructures and Management
Guest editors Manolis Terrovitis (ATHENA RC) and Dominik Ślęzak (University of Warsaw)
Data Infrastructures and Management - Introduction to the Special Theme
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by Manolis Terrovitis (ATHENA RC) and Dominik Ślęzak (University of Warsaw)
Data infrastructures are critical for efficient handling of large-scale datasets in any domain, and they are required for industrial, commercial, scientific and policy-making purposes. Robust data infrastructures ensure data security and integrity, which is essential for compliance and maintaining the trust of users and stakeholders. They allow for scalability and flexibility, which is needed to handle the constant influx of new data and changing the data processing pipelines. A well-designed data infrastructure ensures that data is properly integrated, standardised, and secure, which is crucial for accurate and reliable analysis.
D4SCIENCE: A Unique Infrastructure Delivering Virtual Research Environments as a Service
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by Leonardo Candela (CNR-ISTI), Donatella Castelli (CNR-ISTI) and Pasquale Pagano (CNR-ISTI)
Nowadays, research challenges – often based on the collaborative analysis of a large amount of data – require suitable infrastructures and user-facing solutions promoting multidisciplinary collaboration and appropriate communication and sharing of data, processes, and outcomes. The D4Science infrastructure and its virtual research environments proved to be a viable and effective solution for many communities of practice and use cases.
ARIADNE: A Data Infrastructure for the Archaeological Research Community
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by Alessia Bardi, Massimiliano Assante and Francesco Mangiacrapa (CNR-ISTI)
The ARIADNE infrastructure provides tools and services for researchers to address archaeological grand challenges that require discovery and analysis of information scattered across different thematic and geographically distributed sources.
Boosting Open Science in the IPERION HS Research Infrastructure with OpenAIRE
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by Alessia Bardi (CNR-ISTI) and Laura Benassi (CNR-INO)
IPERION HS is a research infrastructure that supports researchers in the field of heritage science, an interdisciplinary domain studying cultural and natural tangible heritage. This article describes how IPERION HS makes the research outputs open and accessible to the community and monitors its impact thanks to the services offered by the OpenAIRE infrastructure.
The Data Portal of the European Plate Observing System – A New Tool for the Solid-earth Sciences in Europe
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by Vasco Avramo (EPOS-ERIC), Daniele Bailo (EPOS-ERIC, INGV) and Rossana Paciello (EPOS-ERIC, INGV)
EPOS, the European Plate Observing System, is currently the only research infrastructure for solid-earth sciences in Europe. It integrates a multitude of different data, metadata, software and services through one single portal, the EPOS Data Portal, released on January 1st 2023.
RISER: The First All-European RISC-V Cloud Server Infrastructure
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by Manolis Marazakis and Stelios Louloudakis (ICS-FORTH)
The European cloud market is estimated to grow from EUR 32 billion to EUR 127 billion from 2020 to 2026, playing a key role in the European economic growth and social development. RISER will develop the first all-European RISC-V cloud server infrastructure, significantly enhancing Europe's strategic autonomy in open-source technologies.
Open and Shared Infrastructure for Software Research
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by Jurgen Vinju (CWI and TU Eindhoven)
Research software engineers, scientific programmers, PhD students and postdocs alike spend their time and energy on engineering the software for their research infrastructure. Sometimes this can be reused in follow-up research projects, but most often valuable software output falls like trees in the forest, without an audience, and without users. Surprisingly, even in the academic field of software engineering, research software infrastructure is not sustained, leaving a wide gap of opportunity for more reuse and more impact.
Creating a Privacy-aware Framework for Fine-grained Data Access
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Eliot Salant (IBM Israel Research Lab)
We have created a framework to enable secure, policy-driven data exchange, applying sophisticated, fine-grained access control to data stores. Incorporated into the EU Horizon2020 HEIR project, we have demonstrated the flexibility and power of our Privacy-aware Framework (PAF) in a number of use cases, including automatic anonymisation of data on export to a third party, and redaction of data based on user role and organisation affiliation.
Outsourced Computations Maintaining Confidentiality and Authenticity
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by Stephan Krenn, Thomas Lorünser, Sebastian Ramacher, Florian Wohner (AIT Austrian Institute of Technology)
Performing joint computations on data coming from different data owners offers great potential for more efficient resource use, cost reductions, a reduction in certain industry's carbon footprint and improved societal benefits. However, these synergies are often not exploited because stakeholders have high confidentiality requirements for business-sensitive data and are distrusting of each other. To address this gap, in a series of projects, we have developed provably privacy-preserving and verifiable protocols based on multi-party computation.
A Secure Trustworthy Privacy-preserving Framework for Cross-federation of Data
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by Emmanouil Spanakis (ICS-FORTH), Evangelos Markakis (HMU), Dimitra Papatsaroucha (HMU), Ilias Polits (INQBIT) and Vangelis Sakkalis (ICS-FORTH)
Utilising self-sovereign technologies and with state-of-the-art homomorphic encryption, TRUSTEE offers a socially and environmentally aware framework for cross-discipline federation of data.
Privacy-Preserving Data Sharing for Collaborative Analytics in Multi-Modal Transportation Systems
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by Daniele Albanese, Giuseppe Crincoli, Marco De Vincenzi, Giacomo Iadarola, Fabio Martinelli, Ilaria Matteucci and Paolo Mori (CNR-IIT)
Allowing data producers to retain some control of the data they share is of paramount importance to encourage data sharing for collaborative analytics.
Extensive and Secure Personal Data Management Systems
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by Nicolas Anciaux and Luc Bouganim (Inria, UVSQ and Univ. Paris-Saclay)
Personal Data Management Systems (PDMS) are emerging to provide individuals with appropriate tools to collect, manage and allow applications to access their personal data. At the same time, the deployment of Trusted Execution Environments (TEE) both on the cloud (Intel SGX processors) and on smartphones (ARM TrustZone) opens new architectural perspectives for these PDMS. The PETRUS project [L1] proposes new solutions for PDMS, allowing third-party applications to exploit the individual's personal data while guaranteeing individuals the legitimacy of uses and privacy. A first proof-of-concept implementation of this new architecture has just been developed on Intel SGX processor.
CyberSec4Europe - Securing and Preserving Privacy Sharing Health Data
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by Raquel Cortés Carreras, Juan Carlos Pérez Baún and Miryam Villegas Jiménez (Atos Spain S.A.)
In the context of EU Horizon 2020 CyberSec4Europe project the medical data exchange demonstrator creates a trusted ecosystem for sharing medical data in a secure and privacy preserving manner.
On Reducing Complexity in AI Pipelines: Modularisation to Retain Control
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by Dennis Hemker, Stefan Kreutter and Harald Mathis (Fraunhofer FIT)
Data is the key factor for solving problems with modern approaches like AI but only a part of the whole. To reduce complexity in the AI life cycle, we propose a modularised tooling approach and describe the data-related parts of it.
Recent developments like ChatGPT [L1] or Stable Diffusion [L2] have shown the high potential of data-driven approaches to tackle a wide range of problems across different domains.
SEDAR: A Semantic Data Reservoir for Integrating Heterogeneous Datasets and Machine Learning
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by Sayed Hoseini and Christoph Quix (Hochschule Niederrhein University of Applied Sciences)
SEDAR is a comprehensive semantic data lake that includes support for data ingestion, storage, processing, analytics and governance. The key element of SEDAR is semantic metadata management, suitable for many use cases, e.g. provenance, versioning, lineage, dataset similarity or profiling. The generic ingestion interface can deal with any external data source ranging from files to databases and streams change and incorporates data capture with data versioning and automatic metadata extraction. Machine learning (ML) is integrated into the data lake as its artefacts (e.g., ML pipelines, notebooks, models) are stored in the data lake to allow a coherent development of data preparation and ML pipelines. As all these artefacts are related, their relationships and versions are maintained in the extended metadata repository.
NET-IT: A Next Generation Intelligent Network Research Agenda
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by Karin Anna Hummel (Johannes Kepler University Linz), Paul Smith (Austrian Institute of Technology), Markus Tauber (Research Studios Austria), Peter Dorfinger (Salzburg Research) and Olga Saukh (Graz University of Technology)
The NET-IT initiative at the Austrian Computer Society is making networks intelligent to ease adjustment to the digital evolution and societal needs: Let the network learn and act driven by goals!
A Research Infrastructure where Artificial Intelligence Meets Persons and Society
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by Roberto Trasarti, Katia Genovali and Beatrice Rapisarda (CNR-ISTI)
In our complex society, the ethical use and storage of data are essential for the scientific community and institutions to build trust in citizens. SoBigData is a pan-European and cross-disciplinary Research Infrastructure on social mining and data analytics, which bases its research activities on ethics and fairness. SoBigData doesn't apply science only to the most challenging societal issues; in fact, it provides data and facilities to researchers and services to firms and public administrations to develop innovative tools and respond to societal needs. Above all, it works to create an ecosystem for data research that respects the founding principles of Europe for the benefit of the whole community.
Data Analytics and AI Testing Facility Based on Research and Technology Infrastructure
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by Samuel Renault and Patrik Hitzelberger (Luxembourg Institute of Science and Technology)
Opening a high-performance data analytics and AI research and technology infrastructure to small companies will support digitisation and co-development of Industry 4.0 projects. A test-before-invest approach is supported by the local digital innovation hub.
Curatorial Companionship: A New Framework for Managing High-quality Digital Cultural Content and Data
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by Thomas Ballhausen (University Mozarteum Salzburg) and Stefan Gindl and Markus Tauber (Research Studios Austria FG)
In this paper, we present a novel approach for the intense management of data and creation of digital, cultural artefacts. We propose using interdisciplinary synergies between two new concepts, cultural companionship and ArtScrum. The former is an approach to combine skills and expertise from various, possibly disjunct domains; the latter is a structured, iterative concept adopted from digital engineering and specifically adapted to the needs of digital art creation.
Data-aware Declarative Application Management in the Cloud-IoT Continuum
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by Jacopo Massa (University of Pisa / CNR-ISTI), Stefano Forti, Patrizio Dazzi and Antonio Brogi (University of Pisa)
Nowadays billions of devices are connected to the Internet of Things and can reach computing facilities along the Cloud-IoT continuum to process the data they produce, leading to a dramatic increase in the number of deployed applications as well as in the amount of data they need to crunch. Following a continuous reasoning approach to speed up the decision-making process, our research proposes a declarative and data-aware solution to determine service-based application placements over the Cloud-IoT continuum while meeting functional and non-functional application requirements.
IndeGx: An Index of Linked Open Datasets on the Web
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by Pierre Maillot, Catherine Faron, Fabien Gandon and Franck Michel (Inria)
Where can we find the data we need for a given task? IndeGx aims to create an index of knowledge graphs published on the web, in the form of linked open datasets, for humans and machines alike. This framework provides descriptions of the knowledge graphs to draw a picture of their content, quality and compliance with the standards. A companion webpage is also provided to support data providers in the description of their datasets in compliance with the latest best practices.
Promoting Federated and Trusted Sharing and Trading of Interoperable Data Assets and Data-Driven Intelligence – The PISTIS Platform
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by Kyriakos Stefanidis (ISI/ATHENA), Sotiris Kousouris (SUITE5), Yury Glikman (Fraunhofer FOKUS) and Christos Alexakos (ISI/ATHENA).
PISTIS is a European research project that includes 29 partners (universities, research institutes, SMEs and industry) spanning eleven EU countries and brings forward a reference-federated data sharing/trading and monetisation platform for secure, trusted and controlled exchange and usage of proprietary data assets and data-driven intelligence (derivative data assets).
Dealing with UAV-downwash Effects during Airborne Detection of Localised Gas Plumes
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- Category: Research and Innovation
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by Philip Taupe (AIT Austrian Institute of Technology), Martin Litzenberger (AIT Austrian Institute of Technology), Dieter Rothbacher (CBRN Protection GmbH) and David Monetti (Skyability GmbH)
Unmanned Aerial Vehicle (UAV)-borne gas detection and measurement can drastically reduce operational risks for the involved first responders in scenarios where hazardous gases may be present, e.g. accidents in industrial plants or gas leaks/accumulations in urban settings. However, measurement accuracy and detection abilities of gas sensors can be severely affected by the UAV’s rotor downwash, thus leading to erroneously low gas-concentration readings. We have investigated the applicability and operational parameters of probing tubes extending from under the UAV to escape downwash effects and thereby improve measurement results.
Documenting Data and Knowledge about Feminisms and Politics in the Interwar Balkans with Synthesis-Core
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by Pavlos Fafalios, Lida Charami (FORTH-ICS) and Katerina Dalakoura (University of Crete)
The project FE.P.I.B., hosted by the University of Crete and funded by the Hellenic Foundation for Research and Innovation (HFRI), explores the contacts, relationships and cooperation between the feminist/women's organisations of the Balkan and Central European countries, and particularly the entanglement of their emancipatory policies with the politics in the region during the interwar period. Researchers of FE.P.I.B. collaborate with the Centre for Cultural Informatics of FORTH-ICS for exploiting the information system Synthesis-Core as the project's data and knowledge management platform.
Survival Skills in the Digital Era: Helping Teachers to Develop Digital Competences
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by Angela Fessl and Katharina Maitz (TU Graz), Monica Divitini (NTNU)
Digital technologies have a great potential in supporting teaching practices. However, as also experienced during the COVID-19 pandemic, many teachers lack both the training and support they need to effectively use technologies in class or lecture halls. The DIGIVID project addresses this challenge with a system providing a comprehensive curriculum accessible through an innovative learning tool.
Digital Battery Passports for a Circular Economy
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by Veronika Siska (Austrian Institute of Technology) and Theresa Schredelseker (University of Duisburg-Essen)
The digital battery passport is an essential driver of sustainable production and circular economy by storing and tracking data for batteries throughout their life cycles. The BatWoMan project is paving the way towards carbon-neutral Li-ion battery cell production via new sustainable and cost-efficient methods, and by building a prototype for a digital battery passport.
Remote Sensing: Detecting and Tracking Vehicles on Satellite Images and Videos
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by Josiane Zerubia and and Louis Hauseux (Inria)
Remote sensing present various interests for civilian and military applications: automatic traffic monitoring, driving behavioral research, surveillance, etc. We work on images taken by satellite. This particular type of data has specific characteristics, quite different from those obtained by other aerial sensors (drones, planes, high-altitude balloons). The new Pléiades Neo satellites have high native resolution (i.e. without algorithmic processing) of 0.30 meter per pixel; and an impressive swath (photograph’s width) of 14 kilometers. These technical characteristics make classical shape-based detection methods unsatisfactory.
The Institute for Software Engineering and Sortware Technology of the University of Malaga Joins ERCIM
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The Institute of Software Engineering and Technology (ITIS, or ITIS Software) is a unit of the University of Malaga dedicated to scientific and technical research [L1]. The main objective of ITIS is to contribute to the development and application of software technologies through research, innovation, training, and technology transfer. Due to the transversal characteristics of software, the Institute is an interdisciplinary center in which specialists in different technological areas and application domains work together to advance these technologies. ITIS is oriented towards the foundations, tools, and applications of Software Technologies and Software Engineering for industry and society, with a special focus on five main areas: Automated Software Engineering, Data Science and Engineering and Artificial Intelligence, Cybersecurity, Smart Networks and Services, and Applications of Software Technologies and Software Engineering. The working language at the Institute is English.
Remembering Harry Rudin
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It is with great sadness that the Editorial Board of ERCIM News marks the passing of our esteemed colleague and friend Harry Rudin in October 2022.
CWI and Inria Intensify their Collaboration
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In the presence of Ministers Sylvie Retailleau and Robbert Dijkgraaf, Inria and CWI signed an agreement to extend their cooperation in the fields of Quantum Computing, Human interaction, Energy, Cryptography, Digital Health, Machine Learning and Software Engineering. New in this collaboration is the creation of European joint research teams. CWI and Inria, both founding members of ERCIM, have already collaborated successfully over the past decades and have come to know each other as reliable research partners. Both institutes have an excellent scientific reputation. By strengthening their cooperation through a partnership agreement, both parties join forces to support their research on a European scale and thus achieve important scientific results. This intensified collaboration will include a joint research and innovation agenda to strengthen networking, external partnership opportunities and funding. Scientific cooperation will be strengthened by creating joint projects as well as joint research teams.
CWI Spin-off DuckDB Labs Partners with MotherDuck
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CWI spin-off company DuckDB Labs helped create startup MotherDuck, which aims to connect DuckDB to the cloud and which raised $47.5 million. The open-source DuckDB system was launched in 2019 by Hannes Mühleisen and Mark Raasveldt from the Database Architectures group of CWI. They designed and implemented an innovative lightweight database system that manages and analyzes large amounts of data in a highly efficient way, using state-of-the-art techniques, including CWI inventions such as vectorized query processing, and also introduced new techniques.
Dagstuhl Seminars and Perspectives Workshops
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Call for Proposals
Schloss Dagstuhl – Leibniz-Zentrum für Informatik is accepting proposals for scientific seminars/workshops in all areas of computer science, in particular also in connection with other fields.