2026
Conference article
Open Access
A conversational assistant for geoscientists in virtual research environments
Peccerillo Biagio, Oliviero Alfredo, Procaccini Marco, Candela Leonardo, Frosini Luca, Mangiacrapa Francesco, Panichi Giancarlo, Assante Massimiliano, Pagano Pasquale
D4Science provides web-based Virtual Research Environments (VREs) that support FAIR, open, and reproducible science across multiple research domains, including Earth science. These environments integrate data access, computation, and collaboration services, offering powerful capabilities to researchers and enabling complex, data-intensive scientific activities within a shared digital infrastructure. This contribution introduces a conversational intelligent assistant integrated into D4Science VREs, designed to support Earth scientists in their research activity. The assistant provides a natural language interface that helps users interact with D4Science VREs' services, locate relevant datasets and research items, obtain guidance on common tasks, and support exploratory and operational activities within the VRE. The assistant is designed with a modular approach. The user interacts with a coordinator agent that orchestrates a multi-agent system, where specialized AI agents collaborate to perform a variety of tasks. This architecture allows the assistant to handle heterogeneous requests and to support users across different phases of their research activities, while also facilitating maintenance and extensibility. The conversational agent adopts a Retrieval-Augmented Generation (RAG) approach that leverages the knowledge already captured by the VRE through its regular use by research communities. In fact, as VREs naturally accumulate updated knowledge created and curated by researchers over time, the assistant's knowledge base evolves incorporating new information. This way, the assistant can ground its responses in domain-specific and up-to-date information, effectively acting as a domain-aware expert embedded within the research environment. By serving as an accessible entry point to the VRE, the assistant complements existing interfaces without altering established workflows. The presentation discusses the motivation, design choices, and integration strategy. It also presents various concrete use cases relevant to Earth scientists, demonstrating how the conversational assistant can be effectively employed to support their research activity.DOI: 10.5194/egusphere-egu26-13138
Metrics:
Peccerillo Biagio, Oliviero Alfredo, Procaccini Marco, Candela Leonardo, Frosini Luca, Mangiacrapa Francesco, Panichi Giancarlo, Assante Massimiliano, Pagano Pasquale
D4Science provides web-based Virtual Research Environments (VREs) that support FAIR, open, and reproducible science across multiple research domains, including Earth science. These environments integrate data access, computation, and collaboration services, offering powerful capabilities to researchers and enabling complex, data-intensive scientific activities within a shared digital infrastructure. This contribution introduces a conversational intelligent assistant integrated into D4Science VREs, designed to support Earth scientists in their research activity. The assistant provides a natural language interface that helps users interact with D4Science VREs' services, locate relevant datasets and research items, obtain guidance on common tasks, and support exploratory and operational activities within the VRE. The assistant is designed with a modular approach. The user interacts with a coordinator agent that orchestrates a multi-agent system, where specialized AI agents collaborate to perform a variety of tasks. This architecture allows the assistant to handle heterogeneous requests and to support users across different phases of their research activities, while also facilitating maintenance and extensibility. The conversational agent adopts a Retrieval-Augmented Generation (RAG) approach that leverages the knowledge already captured by the VRE through its regular use by research communities. In fact, as VREs naturally accumulate updated knowledge created and curated by researchers over time, the assistant's knowledge base evolves incorporating new information. This way, the assistant can ground its responses in domain-specific and up-to-date information, effectively acting as a domain-aware expert embedded within the research environment. By serving as an accessible entry point to the VRE, the assistant complements existing interfaces without altering established workflows. The presentation discusses the motivation, design choices, and integration strategy. It also presents various concrete use cases relevant to Earth scientists, demonstrating how the conversational assistant can be effectively employed to support their research activity.DOI: 10.5194/egusphere-egu26-13138
Metrics:
See at:
CNR IRIS 
| www.egu26.eu | CNR IRIS 
2026
Book
Open Access
Advancing Open Science: federated infrastructures and trustworthy ecosystems
Candela Leonardo, Di Cosmo Roberto
Open Science is a broad and evolving movement. The UNESCO framework describes it as an inclusive approach aimed at making scientific knowledge openly available, accessible, and reusable for everyone, opening the processes of knowledge creation and evaluation to stakeholders beyond the traditional research community [1]. Today, Open Science is no longer merely a normative ideal: it has become an operational requirement embedded in national strategies, funding conditions, and research assessment reforms across Europe and beyond. Yet the very breadth of Open Science is also its greatest challenge. The movement rests on several distinct pillars, each with its own history, infrastructure landscape, and degree of maturity — and each exposed to the same structural risk: fragmentation. The three pillars - and the fragmentation trap The oldest pillar is open access to publications. Decades of effort have produced undeniable progress, but also a cautionary tale. Because coordination came late, the landscape is now highly fragmented: OpenDOAR counts over 6,000 open access repositories worldwide, each requiring its own infrastructure, archival, backup, and metadata curation. Content is duplicated, metadata is inconsistent, and the cost of maintaining this patchwork is borne many times over. The recent move to fund, via national grants, the EU-originated Open Research Europe journal illustrates how difficult it is to retrofit coherence onto an ecosystem that grew without a shared architectural plan. The second pillar, open research data, has benefited from the lessons of publications and from the early adoption of the FAIR principles. Yet a similar proliferation of platforms and curation challenges is already visible, with a very long tail of research data that struggles to find a sustainable home. National initiatives such as Recherche Data Gouv in France and the PLATICA project in Spain point toward a promising model: shared, mutualized infrastructures that host curated research data as a public good, rather than leaving each institution to build and maintain its own silo. The third pillar — research software — has long pre-existed the others, since software has been at the heart of scientific computation for decades. Yet it was recognized as a pillar of Open Science only very recently. The French Second National Plan for Open Science (2021) was the first national strategy to dedicate a full chapter to software, establishing measures for archiving, referencing, and citing source code, creating a national research software award, and providing explicit support for Software Heritage as a key infrastructure [2]. Spain is now actively building on this momentum, as evidenced by the discussions at the recent second national days on Open Science held in Aranjuez in March 2026. For software, there is a unique opportunity to avoid the fragmentation that has plagued publications and data. Software Heritage was designed from the outset as a universal, open, non-profit archive for all software source code. It already preserves over 28 billion source files from more than 430 million projects collected across over 5,000 code hosting and distribution platforms worldwide, assigning intrinsic, cryptographically strong identifiers (SWHIDs, now standardized as ISO/IEC 18670). This provides a single, shared layer for archiving, referencing, describing, and citing software — a foundation that Open Science policy can build on directly, without the need to reconcile thousands of independent local repositories after the fact. Federating from the top: promise and friction Alongside bottom-up infrastructure efforts, Europe has invested heavily in top-down coordination through the European Open Science Cloud (EOSC), which aims to federate existing services into an interoperable, cross-border research environment. Several contributions to this issue illustrate both the promise and the complexity of this endeavour. Yet federation by decree is hard. Even in countries with active EOSC engagement, surveys show that a majority of researchers still store data primarily on personal computers, and awareness of federated infrastructure remains low. The gap between policy ambition and daily research practice is real, and bridging it requires not just technical platforms but sustained investment in skills, incentives, and institutional culture change. A map of the current landscape The contributions collected in this special theme offer a cross-section of the current European effort, organised into five thematic clusters. A first cluster addresses research assessment and scholarly representation. The OpenAIRE Graph (Manghi) provides a community-governed scholarly knowledge graph treating datasets and software as first-class outputs, offering an open alternative to proprietary research intelligence. MyResearchFolio (Amodeo and Xenou) builds on this to support richer researcher profiles aligned with responsible assessment principles, while BibTexViz (Horcas) demonstrates visual analytics for open bibliographic data. The EOSC Open Science Observatory (Szybisty) combines indicators, national narratives, and AI-assisted analysis to monitor Open Science progress across Europe. A second cluster explores the transition from FAIR data to AI-ready workflows. Contributions show how shared industrial datasets can feed collaborative knowledge pipelines (Gorissen and Brauner), how compute-to-data architectures enable scalable analysis on research infrastructures (Brus et al.), and how modular, open-source research software frameworks can support advanced biomedical analytics (Segura-Ortiz et al.). A third cluster highlights semantic foundations and knowledge graph infrastructures as critical enablers of interoperability, through the transformation of legacy databases into FAIR-by-design knowledge graphs (Marketakis et al.) and the evolution of the EOSC Interoperability Framework toward machine-actionable, composable service templates (Bardi et al.). A fourth cluster addresses the governance, skills, sovereignty, and ethical foundations without which technical infrastructure cannot function. Contributions cover human-centred threat modelling (Onofri and Corti), structured co-creation in data spaces (Stampfl and Palkovits-Rauter), Open Science education beyond purely technical skills (Flicker et al.), the Czech national experience with FAIR adoption (Dvořák et al.), the tension between Creative Commons licences and AI training (Spichtinger), and privacy-enhancing technologies for secure cross-border data sharing (Jimenez-Bejarano et al.). The fifth and final cluster presents operational experiences with federated science gateways, including the EOSC EU Node (Brunschweiger et al.), the Innovation Sandbox (Drago and Fiore), the Data Commons (Fernández and Fava), the ENVRI-Hub for environmental research (Drago et al.), the D4Science virtual research environments (Assante et al.), and the DAVE conversational AI assistant for navigating complex research workflows (Dell'Amico et al.). Looking ahead Taken together, these contributions make clear that the next phase of Open Science will be defined not just by openness, but by trustworthiness and integration. Several priorities stand out. First, avoiding fragmentation must become a conscious design principle, not an afterthought. For each pillar of Open Science — publications, data, and software — the question is whether we build shared, mutualized infrastructure from the start or spend decades trying to harmonize a patchwork. Second, research assessment must formally recognize the full range of research outputs — datasets, software, workflows — alongside publications, moving away from proprietary metrics toward transparent, community-governed research intelligence. Third, the intersection of open licensing and AI training remains legally ambiguous. As AI models increasingly consume open research data and code, robust opt-in/opt-out mechanisms and legal clarity are urgently needed. Finally, long-term financial sustainability for community-governed infrastructure remains an open problem. Short-term project funding cannot secure the digital commons on which European research increasingly depends. If the first phase of Open Science was about making research outputs accessible, the present phase is about making research ecosystems interoperable, intelligent, and trustworthy. The contributions in this issue offer both concrete experiences and forward-looking perspectives on how Europe is working to make that vision a reality.Source: ERCIM NEWS, vol. 144, pp. 6-40
Candela Leonardo, Di Cosmo Roberto
Open Science is a broad and evolving movement. The UNESCO framework describes it as an inclusive approach aimed at making scientific knowledge openly available, accessible, and reusable for everyone, opening the processes of knowledge creation and evaluation to stakeholders beyond the traditional research community [1]. Today, Open Science is no longer merely a normative ideal: it has become an operational requirement embedded in national strategies, funding conditions, and research assessment reforms across Europe and beyond. Yet the very breadth of Open Science is also its greatest challenge. The movement rests on several distinct pillars, each with its own history, infrastructure landscape, and degree of maturity — and each exposed to the same structural risk: fragmentation. The three pillars - and the fragmentation trap The oldest pillar is open access to publications. Decades of effort have produced undeniable progress, but also a cautionary tale. Because coordination came late, the landscape is now highly fragmented: OpenDOAR counts over 6,000 open access repositories worldwide, each requiring its own infrastructure, archival, backup, and metadata curation. Content is duplicated, metadata is inconsistent, and the cost of maintaining this patchwork is borne many times over. The recent move to fund, via national grants, the EU-originated Open Research Europe journal illustrates how difficult it is to retrofit coherence onto an ecosystem that grew without a shared architectural plan. The second pillar, open research data, has benefited from the lessons of publications and from the early adoption of the FAIR principles. Yet a similar proliferation of platforms and curation challenges is already visible, with a very long tail of research data that struggles to find a sustainable home. National initiatives such as Recherche Data Gouv in France and the PLATICA project in Spain point toward a promising model: shared, mutualized infrastructures that host curated research data as a public good, rather than leaving each institution to build and maintain its own silo. The third pillar — research software — has long pre-existed the others, since software has been at the heart of scientific computation for decades. Yet it was recognized as a pillar of Open Science only very recently. The French Second National Plan for Open Science (2021) was the first national strategy to dedicate a full chapter to software, establishing measures for archiving, referencing, and citing source code, creating a national research software award, and providing explicit support for Software Heritage as a key infrastructure [2]. Spain is now actively building on this momentum, as evidenced by the discussions at the recent second national days on Open Science held in Aranjuez in March 2026. For software, there is a unique opportunity to avoid the fragmentation that has plagued publications and data. Software Heritage was designed from the outset as a universal, open, non-profit archive for all software source code. It already preserves over 28 billion source files from more than 430 million projects collected across over 5,000 code hosting and distribution platforms worldwide, assigning intrinsic, cryptographically strong identifiers (SWHIDs, now standardized as ISO/IEC 18670). This provides a single, shared layer for archiving, referencing, describing, and citing software — a foundation that Open Science policy can build on directly, without the need to reconcile thousands of independent local repositories after the fact. Federating from the top: promise and friction Alongside bottom-up infrastructure efforts, Europe has invested heavily in top-down coordination through the European Open Science Cloud (EOSC), which aims to federate existing services into an interoperable, cross-border research environment. Several contributions to this issue illustrate both the promise and the complexity of this endeavour. Yet federation by decree is hard. Even in countries with active EOSC engagement, surveys show that a majority of researchers still store data primarily on personal computers, and awareness of federated infrastructure remains low. The gap between policy ambition and daily research practice is real, and bridging it requires not just technical platforms but sustained investment in skills, incentives, and institutional culture change. A map of the current landscape The contributions collected in this special theme offer a cross-section of the current European effort, organised into five thematic clusters. A first cluster addresses research assessment and scholarly representation. The OpenAIRE Graph (Manghi) provides a community-governed scholarly knowledge graph treating datasets and software as first-class outputs, offering an open alternative to proprietary research intelligence. MyResearchFolio (Amodeo and Xenou) builds on this to support richer researcher profiles aligned with responsible assessment principles, while BibTexViz (Horcas) demonstrates visual analytics for open bibliographic data. The EOSC Open Science Observatory (Szybisty) combines indicators, national narratives, and AI-assisted analysis to monitor Open Science progress across Europe. A second cluster explores the transition from FAIR data to AI-ready workflows. Contributions show how shared industrial datasets can feed collaborative knowledge pipelines (Gorissen and Brauner), how compute-to-data architectures enable scalable analysis on research infrastructures (Brus et al.), and how modular, open-source research software frameworks can support advanced biomedical analytics (Segura-Ortiz et al.). A third cluster highlights semantic foundations and knowledge graph infrastructures as critical enablers of interoperability, through the transformation of legacy databases into FAIR-by-design knowledge graphs (Marketakis et al.) and the evolution of the EOSC Interoperability Framework toward machine-actionable, composable service templates (Bardi et al.). A fourth cluster addresses the governance, skills, sovereignty, and ethical foundations without which technical infrastructure cannot function. Contributions cover human-centred threat modelling (Onofri and Corti), structured co-creation in data spaces (Stampfl and Palkovits-Rauter), Open Science education beyond purely technical skills (Flicker et al.), the Czech national experience with FAIR adoption (Dvořák et al.), the tension between Creative Commons licences and AI training (Spichtinger), and privacy-enhancing technologies for secure cross-border data sharing (Jimenez-Bejarano et al.). The fifth and final cluster presents operational experiences with federated science gateways, including the EOSC EU Node (Brunschweiger et al.), the Innovation Sandbox (Drago and Fiore), the Data Commons (Fernández and Fava), the ENVRI-Hub for environmental research (Drago et al.), the D4Science virtual research environments (Assante et al.), and the DAVE conversational AI assistant for navigating complex research workflows (Dell'Amico et al.). Looking ahead Taken together, these contributions make clear that the next phase of Open Science will be defined not just by openness, but by trustworthiness and integration. Several priorities stand out. First, avoiding fragmentation must become a conscious design principle, not an afterthought. For each pillar of Open Science — publications, data, and software — the question is whether we build shared, mutualized infrastructure from the start or spend decades trying to harmonize a patchwork. Second, research assessment must formally recognize the full range of research outputs — datasets, software, workflows — alongside publications, moving away from proprietary metrics toward transparent, community-governed research intelligence. Third, the intersection of open licensing and AI training remains legally ambiguous. As AI models increasingly consume open research data and code, robust opt-in/opt-out mechanisms and legal clarity are urgently needed. Finally, long-term financial sustainability for community-governed infrastructure remains an open problem. Short-term project funding cannot secure the digital commons on which European research increasingly depends. If the first phase of Open Science was about making research outputs accessible, the present phase is about making research ecosystems interoperable, intelligent, and trustworthy. The contributions in this issue offer both concrete experiences and forward-looking perspectives on how Europe is working to make that vision a reality.Source: ERCIM NEWS, vol. 144, pp. 6-40
See at:
ercim-news.ercim.eu | CNR IRIS | CNR IRIS
2026
Journal article
Open Access
Deploying conversational agents in virtual research environments: approaches and lessons learned
Assante Massimiliano, Candela Leonardo, Dell'Amico Andrea, Frosini Luca, Mangiacrapa Francesco, Oliviero Alfredo, Pagano Pasquale, Panichi Giancarlo, Peccerillo Biagio, Piccioli Tommaso, Procaccini Marco
Conversational agents have the potential to streamline tasks, provide support, and enhance user experience across various domains including Virtual Research Environments (VREs). The recent progress in conversational artificial intelligence and Large Language Models (LLMs) offers novel strategies for the development of these agents. This paper reports on the potential benefits, the challenges and the approaches resulting from concrete experiences in developing and equipping D4Science-based VREs with suitable conversational agents. The paper presents three successive implementation approaches and the resulting agent solution, each designed to address the limitations identified in the preceding iteration and to leverage the advantages offered by newer implementation and development options. The proposed approaches led to the progressive refinement of the agent design and functionality, resulting in DAVE, a conversational agent capable of securely interacting with multiple D4Science services and supporting a wide range of user workflows. The iterative process highlighted critical requirements—including authentication handling, usability, and extensibility—that can inform the design of conversational agents in similar research infrastructures. The study shows that conversational agents can effectively lower the barrier to accessing VRE functionalities and enhance user engagement. The resulting design principles and lessons learned provide a foundation for future work aimed at extending DAVE with an enhanced feedback mechanism and locally hosted LLM integration, and conducting systematic usability evaluations within active research communities.Source: SN COMPUTER SCIENCE, vol. 7
DOI: 10.1007/s42979-026-04863-3
Project(s): A federated European FAIR and Open Research Ecosystem for oceans, seas, coastal and inland waters, FOSSR—Fostering Open Science in Social Science Research
Metrics:
Assante Massimiliano, Candela Leonardo, Dell'Amico Andrea, Frosini Luca, Mangiacrapa Francesco, Oliviero Alfredo, Pagano Pasquale, Panichi Giancarlo, Peccerillo Biagio, Piccioli Tommaso, Procaccini Marco
Conversational agents have the potential to streamline tasks, provide support, and enhance user experience across various domains including Virtual Research Environments (VREs). The recent progress in conversational artificial intelligence and Large Language Models (LLMs) offers novel strategies for the development of these agents. This paper reports on the potential benefits, the challenges and the approaches resulting from concrete experiences in developing and equipping D4Science-based VREs with suitable conversational agents. The paper presents three successive implementation approaches and the resulting agent solution, each designed to address the limitations identified in the preceding iteration and to leverage the advantages offered by newer implementation and development options. The proposed approaches led to the progressive refinement of the agent design and functionality, resulting in DAVE, a conversational agent capable of securely interacting with multiple D4Science services and supporting a wide range of user workflows. The iterative process highlighted critical requirements—including authentication handling, usability, and extensibility—that can inform the design of conversational agents in similar research infrastructures. The study shows that conversational agents can effectively lower the barrier to accessing VRE functionalities and enhance user engagement. The resulting design principles and lessons learned provide a foundation for future work aimed at extending DAVE with an enhanced feedback mechanism and locally hosted LLM integration, and conducting systematic usability evaluations within active research communities.Source: SN COMPUTER SCIENCE, vol. 7
DOI: 10.1007/s42979-026-04863-3
Project(s): A federated European FAIR and Open Research Ecosystem for oceans, seas, coastal and inland waters, FOSSR—Fostering Open Science in Social Science Research
Metrics:
See at:
CNR IRIS | link.springer.com | CNR IRIS
2026
Journal article
Open Access
Editorial: data science and AI for marine science and the blue economy
Candela Leonardo, Pagano Pasquale, Bi Hongsheng, Schaap Dick
This editorial introduces the Special Collection “Data Science and AI for Marine Science and the Blue Economy” published in the International Journal of Data Science and Analytics. The collection explores how data-driven and AI-enabled approaches are advancing marine research, supporting operational monitoring, and enabling evidence-based decision-making across blue economy domains. The guest editors summarize the motivations for this initiative, briefly present the contributions included in the issue, and outline emerging themes and future perspectives in this evolving interdisciplinary field.Source: INTERNATIONAL JOURNAL OF DATA SCIENCE AND ANALYTICS, vol. 22 (issue 97)
DOI: 10.1007/s41060-026-01082-0
Project(s): Blue-Cloud 2026
Metrics:
Candela Leonardo, Pagano Pasquale, Bi Hongsheng, Schaap Dick
This editorial introduces the Special Collection “Data Science and AI for Marine Science and the Blue Economy” published in the International Journal of Data Science and Analytics. The collection explores how data-driven and AI-enabled approaches are advancing marine research, supporting operational monitoring, and enabling evidence-based decision-making across blue economy domains. The guest editors summarize the motivations for this initiative, briefly present the contributions included in the issue, and outline emerging themes and future perspectives in this evolving interdisciplinary field.Source: INTERNATIONAL JOURNAL OF DATA SCIENCE AND ANALYTICS, vol. 22 (issue 97)
DOI: 10.1007/s41060-026-01082-0
Project(s): Blue-Cloud 2026
Metrics:
See at:
CNR IRIS | link.springer.com | CNR IRIS
2025
Other
Open Access
ISTI-day 2025 Proceedings
Del Corso G., Pedrotti A., Federico G., Gennaro C., Carrara F., Amato G., Di Benedetto M., Gabrielli E., Belli D., Matrullo Zoe, Miori V., Tolomei Gabriele, Waheed T., Marchetti E., Calabrò Antonello., Rossetti G., Stella Massimo, Cazabet Rémy, Abramski K., Cau E., Citraro S., Failla A., Mesina V., Morini V., Pansanella V., Colantonio S., Germanese D., Pascali M. A., Bianchi L., Messina N., Falchi F., Barsellotti L., Pacini G., Cassese M., Puccetti G., Esuli A., Volpi L., Moreo Alejandro, Sebastiani F., Sperduti G., Nguyen Dong, Broccia G., Ter Beek M. H., Ferrari A., Massink M., Belmonte Gina, Ciancia V., Papini O., Canapa G., Catricalà B., Manca M., Paternò F., Santoro C., Zedda E., Gallo S., Maenza S., Mattioli A., Simeoli L., Rucci D., Carlini E., Dazzi P., Kavalionak H., Mordacchini M., Rulli C., Muntean Cristina Ioana, Nardini F. M., Perego R., Rocchietti G., Lettich F., Renso C., Pugliese C., Casini G., Haldimann Jonas, Meyer Thomas, Assante M., Candela L., Dell'Amico A., Frosini L., Mangiacrapa F., Oliviero A., Pagano P., Panichi G., Peccerillo B., Procaccini M., Mannocci A., Manghi P., Lonetti F., Kang Dongjae, Di Giandomenico F., Jee Eunkyoung, Lazzini G., Conti F., Scopigno R., D'Acunto M., Moroni D., Cafiso M., Paradisi P., Callieri M., Pavoni G., Corsini M., De Falco A., Sala F., Saraceni Q., Gattiglia Gabriele
ISTI-Day is an annual information and networking event organized by the Institute of Information Science and Technologies "A. Faedo" (ISTI) of the Italian National Research Council (CNR). This event features an opening talk of the Director of the Dept. DIITET (Emilio F. Campana) as well as an overview of the Institute's activities presented by the ISTI Director (Roberto Scopigno). Those institutional segments are complemented by dedicated presentations and round tables featuring former staff members, as well as internal and external collaborators. To foster a network of knowledge and collaboration among newcomers, the 2025 ISTI Day edition also includes a large poster session that provides a comprehensive overview of current research activities. Each of the 13 laboratories contributes 1–3 posters, highlighting the most innovative work and offering early-career researchers a platform for discussion. Thus these proceedings include the posters selected for ISTI-Day 2025, reflecting the diverse and innovative nature of the Institute's research.
Del Corso G., Pedrotti A., Federico G., Gennaro C., Carrara F., Amato G., Di Benedetto M., Gabrielli E., Belli D., Matrullo Zoe, Miori V., Tolomei Gabriele, Waheed T., Marchetti E., Calabrò Antonello., Rossetti G., Stella Massimo, Cazabet Rémy, Abramski K., Cau E., Citraro S., Failla A., Mesina V., Morini V., Pansanella V., Colantonio S., Germanese D., Pascali M. A., Bianchi L., Messina N., Falchi F., Barsellotti L., Pacini G., Cassese M., Puccetti G., Esuli A., Volpi L., Moreo Alejandro, Sebastiani F., Sperduti G., Nguyen Dong, Broccia G., Ter Beek M. H., Ferrari A., Massink M., Belmonte Gina, Ciancia V., Papini O., Canapa G., Catricalà B., Manca M., Paternò F., Santoro C., Zedda E., Gallo S., Maenza S., Mattioli A., Simeoli L., Rucci D., Carlini E., Dazzi P., Kavalionak H., Mordacchini M., Rulli C., Muntean Cristina Ioana, Nardini F. M., Perego R., Rocchietti G., Lettich F., Renso C., Pugliese C., Casini G., Haldimann Jonas, Meyer Thomas, Assante M., Candela L., Dell'Amico A., Frosini L., Mangiacrapa F., Oliviero A., Pagano P., Panichi G., Peccerillo B., Procaccini M., Mannocci A., Manghi P., Lonetti F., Kang Dongjae, Di Giandomenico F., Jee Eunkyoung, Lazzini G., Conti F., Scopigno R., D'Acunto M., Moroni D., Cafiso M., Paradisi P., Callieri M., Pavoni G., Corsini M., De Falco A., Sala F., Saraceni Q., Gattiglia Gabriele
ISTI-Day is an annual information and networking event organized by the Institute of Information Science and Technologies "A. Faedo" (ISTI) of the Italian National Research Council (CNR). This event features an opening talk of the Director of the Dept. DIITET (Emilio F. Campana) as well as an overview of the Institute's activities presented by the ISTI Director (Roberto Scopigno). Those institutional segments are complemented by dedicated presentations and round tables featuring former staff members, as well as internal and external collaborators. To foster a network of knowledge and collaboration among newcomers, the 2025 ISTI Day edition also includes a large poster session that provides a comprehensive overview of current research activities. Each of the 13 laboratories contributes 1–3 posters, highlighting the most innovative work and offering early-career researchers a platform for discussion. Thus these proceedings include the posters selected for ISTI-Day 2025, reflecting the diverse and innovative nature of the Institute's research.
See at:
CNR IRIS | www.isti.cnr.it | CNR IRIS
2025
Other
Open Access
Towards an infrastructure for responsible research assessment data management
Mannocci A., Candela L., Manghi P.
Research evaluation is undergoing a profound transformation, and it is now widely recognised that the true value of a researcher’s contribution extends far beyond the sheer volume of papers published in scientific outlets. Yet, despite the growing adoption of revised CV templates and assessment frameworks across many organisations participating in the research ecosystem, a critical gap remains: the lack of structured, interoperable metadata to represent the full spectrum of scholarly contributions. Essential contributions—such as organising conferences, mentoring, teaching, serving on scientific boards, or engaging in collaborative projects—are often undocumented or scattered across ephemeral sources, e.g. emails, web pages, or printouts. Without a robust system for capturing and preserving this information, much of the valuable scholarly record risks being lost as digital content is deleted, websites are updated or decommissioned, or institutional memory fades. To address this challenge, we propose piloting a suite of tools and services that harness the power of Scientific Knowledge Graphs (SKGs), Semantic Web technologies, and Artificial Intelligence. These tools will empower researchers applying for evaluation to capture, persist, and reference their diverse contributions in a CV-ready, machine-readable, and compelling format—on demand and with minimal friction. AI can complement this picture by assisting evaluands in generating narrative sections and impact stories, drafting text and retrieving supporting evidence online. Even more so, by aligning with SKG interoperability standards, this approach will enable the cross-institutional and transnational exchange of evaluation data, paving the way for a more streamlined, verifiable, and up-to-date research assessment process, which will reduce reliance on manual data entry, enhance transparency, and support the principles of Open Science and responsible research evaluation. This research endeavour—posing challenges including dynamic data collection and collation, data provenance and quality, data certification and reliability, generative AI—is not just a technical development; rather, it lays the foundations for a more inclusive, accurate, and future-proof evaluation ecosystem.Project(s): GraspOS
Mannocci A., Candela L., Manghi P.
Research evaluation is undergoing a profound transformation, and it is now widely recognised that the true value of a researcher’s contribution extends far beyond the sheer volume of papers published in scientific outlets. Yet, despite the growing adoption of revised CV templates and assessment frameworks across many organisations participating in the research ecosystem, a critical gap remains: the lack of structured, interoperable metadata to represent the full spectrum of scholarly contributions. Essential contributions—such as organising conferences, mentoring, teaching, serving on scientific boards, or engaging in collaborative projects—are often undocumented or scattered across ephemeral sources, e.g. emails, web pages, or printouts. Without a robust system for capturing and preserving this information, much of the valuable scholarly record risks being lost as digital content is deleted, websites are updated or decommissioned, or institutional memory fades. To address this challenge, we propose piloting a suite of tools and services that harness the power of Scientific Knowledge Graphs (SKGs), Semantic Web technologies, and Artificial Intelligence. These tools will empower researchers applying for evaluation to capture, persist, and reference their diverse contributions in a CV-ready, machine-readable, and compelling format—on demand and with minimal friction. AI can complement this picture by assisting evaluands in generating narrative sections and impact stories, drafting text and retrieving supporting evidence online. Even more so, by aligning with SKG interoperability standards, this approach will enable the cross-institutional and transnational exchange of evaluation data, paving the way for a more streamlined, verifiable, and up-to-date research assessment process, which will reduce reliance on manual data entry, enhance transparency, and support the principles of Open Science and responsible research evaluation. This research endeavour—posing challenges including dynamic data collection and collation, data provenance and quality, data certification and reliability, generative AI—is not just a technical development; rather, it lays the foundations for a more inclusive, accurate, and future-proof evaluation ecosystem.Project(s): GraspOS
2025
Contribution to conference
Open Access
Deploying Conversational Agents in Virtual Research Environments: Approaches and Lessons Learned
Massimiliano Assante, Leonardo Candela, Andrea Dell’amico, Luca Frosini, Francesco Mangiacrapa, Alfredo Oliviero, Pasquale Pagano, Giancarlo Panichi, Biagio Peccerillo, Marco Procaccini
The rapid progress of conversational artificial intelligence and Large Language Models (LLMs) has opened new opportunities to enhance user interaction, support, and accessibility in Virtual Research Environments (VREs). This poster presents the approaches, challenges, and lessons learned from a multi-year e!ort to design, develop, and deploy conversational agents within the D4Science infrastructure. Through three successive implementation cycles—Janet, D4Science AI Agent, and DAVE—the poster traces a process of iterative refinement aimed at improving flexibility, extensibility, usability, and integration with existing VRE services. Janet, the first prototype, explored modular NLP components but revealed limitations in adaptability and feedback integration. The second approach, based on the Cheshire Cat framework, improved modularity and LLM interoperability but remained constrained by a single-agent design. The latest solution, DAVE (D4Science Assistant for Virtual research Environments), introduces a multi-agent architecture built with Google’s Agent Development Kit, enabling secure and context-aware interaction with multiple D4Science services. DAVE combines specialized agents for tasks such as document analysis, catalogue navigation, social interaction summarization, and algorithm deployment within D4Science’s computational platform. Integrated feedback mechanisms and a Retrieval-Augmented Generation (RAG) knowledge base further enhance its learning and personalization capabilities. The findings demonstrate that conversational agents can lower barriers to VRE adoption, streamline workflows, and foster user engagement by o!ering intuitive, natural language interfaces. Lessons learned from this evolution suggest key design principles for future research infrastructure agents, emphasizing modularity, interoperability, and data security. Future work will involve usability evaluations, the integration of user-driven feedback, and experimentation with locally-hosted LLMs to strengthen privacy and operational sustainability.
Massimiliano Assante, Leonardo Candela, Andrea Dell’amico, Luca Frosini, Francesco Mangiacrapa, Alfredo Oliviero, Pasquale Pagano, Giancarlo Panichi, Biagio Peccerillo, Marco Procaccini
The rapid progress of conversational artificial intelligence and Large Language Models (LLMs) has opened new opportunities to enhance user interaction, support, and accessibility in Virtual Research Environments (VREs). This poster presents the approaches, challenges, and lessons learned from a multi-year e!ort to design, develop, and deploy conversational agents within the D4Science infrastructure. Through three successive implementation cycles—Janet, D4Science AI Agent, and DAVE—the poster traces a process of iterative refinement aimed at improving flexibility, extensibility, usability, and integration with existing VRE services. Janet, the first prototype, explored modular NLP components but revealed limitations in adaptability and feedback integration. The second approach, based on the Cheshire Cat framework, improved modularity and LLM interoperability but remained constrained by a single-agent design. The latest solution, DAVE (D4Science Assistant for Virtual research Environments), introduces a multi-agent architecture built with Google’s Agent Development Kit, enabling secure and context-aware interaction with multiple D4Science services. DAVE combines specialized agents for tasks such as document analysis, catalogue navigation, social interaction summarization, and algorithm deployment within D4Science’s computational platform. Integrated feedback mechanisms and a Retrieval-Augmented Generation (RAG) knowledge base further enhance its learning and personalization capabilities. The findings demonstrate that conversational agents can lower barriers to VRE adoption, streamline workflows, and foster user engagement by o!ering intuitive, natural language interfaces. Lessons learned from this evolution suggest key design principles for future research infrastructure agents, emphasizing modularity, interoperability, and data security. Future work will involve usability evaluations, the integration of user-driven feedback, and experimentation with locally-hosted LLMs to strengthen privacy and operational sustainability.
2025
Other
Restricted
InfraScience research activity report 2024
Angioni S., Artini M., Assante M., Atzori C., Baglioni M., Bardi A., Bosio C., Bove P., Calanducci A., Candela L., Casini G., Castelli D., Cirillo R., Coro G., De Bonis M., Debole F., Dell'Amico A., Frosini L., Ibrahim Ahmed, La Bruzzo S., Lelii L., Manghi P., Mangiacrapa F., Mangione D., Mannocci A., Molinaro E., Oliviero A., Pagano P., Panichi G., Teresa M. T., Pavone G., Peccerillo B., Piccioli T., Procaccini M., Straccia U., Vannini G. L., Versienti L.
InfraScience is a research group within the Institute of Information Science and Technologies (ISTI) of the National Research Council of Italy (CNR), based in Pisa. This activity report outlines the group's research achievements and initiatives throughout 2024. InfraScience focused its efforts on key challenges in the areas of Data Infrastructures, e-Science, and Intelligent Systems, maintaining a strong synergy between research and development and a firm commitment to open science principles. In 2024, the group played a leading role in the development and evolution of two major Open Science infrastructures: D4Science and OpenAIRE. InfraScience researchers contributed significantly to the scientific community through the publication of peer-reviewed papers, active participation in EU-funded research projects, organization of international conferences and training activities, and engagement in various working groups and task forces. This report highlights these contributions and underscores the group's ongoing dedication to advancing open, collaborative, and impactful science.DOI: 10.32079/isti-ar-2025/001
Metrics:
Angioni S., Artini M., Assante M., Atzori C., Baglioni M., Bardi A., Bosio C., Bove P., Calanducci A., Candela L., Casini G., Castelli D., Cirillo R., Coro G., De Bonis M., Debole F., Dell'Amico A., Frosini L., Ibrahim Ahmed, La Bruzzo S., Lelii L., Manghi P., Mangiacrapa F., Mangione D., Mannocci A., Molinaro E., Oliviero A., Pagano P., Panichi G., Teresa M. T., Pavone G., Peccerillo B., Piccioli T., Procaccini M., Straccia U., Vannini G. L., Versienti L.
InfraScience is a research group within the Institute of Information Science and Technologies (ISTI) of the National Research Council of Italy (CNR), based in Pisa. This activity report outlines the group's research achievements and initiatives throughout 2024. InfraScience focused its efforts on key challenges in the areas of Data Infrastructures, e-Science, and Intelligent Systems, maintaining a strong synergy between research and development and a firm commitment to open science principles. In 2024, the group played a leading role in the development and evolution of two major Open Science infrastructures: D4Science and OpenAIRE. InfraScience researchers contributed significantly to the scientific community through the publication of peer-reviewed papers, active participation in EU-funded research projects, organization of international conferences and training activities, and engagement in various working groups and task forces. This report highlights these contributions and underscores the group's ongoing dedication to advancing open, collaborative, and impactful science.DOI: 10.32079/isti-ar-2025/001
Metrics:
2025
Other
Open Access
Blue-Cloud2026 D5.4 - Blue Cloud VRE Common Services 2nd Release
Assante M., Candela L., Dalla Torre G., Dell'Amico A., Fernandez E., Frosini L., Lettere M., Mangiacrapa F., Molinaro E., Mugnaini M., Oliviero A., Pagano P., Panichi G., Peccerillo B., Piccioli T.
This deliverable documents the design principles and software architecture characterising the release and development of the Blue-Cloud Virtual Research Environment (VRE) common services, namely the analytics computing framework, the catalogue framework, the storage framework and the enabling framework components. This report is the second of two versions, each one describing the design associated with a specific version of the VRE. This deliverable D5.4 provides the updated and extended version of D5.1 “Blue-Cloud VRE Common Services 1st Release” [8]. The document presents the current state of the Blue-Cloud Virtual Research Environment (VRE) common services, detailing both the new components introduced in the period M13 to M36 and the enhancements applied to the existing ones to ensure compliance with interoperability, scalability, and robustness requirements. Overall, deliverable D5.4 provides a consolidated, fully up-to-date view of the Blue-Cloud VRE common services architecture, covering functional capabilities, API exposure, deployment configuration, and integration status as of the end of the second reporting period. The deliverable consists of six sections. ● Section 1 briefly introduces the role of this deliverable in the development and delivery of the Blue-Cloud VRE common services. ● Section 2 describes the Blue-Cloud VRE logical architecture of the common services and how they relate to the other services available in the VRE. ● Section 3, 4, 5 and 6 document the release of the Blue-Cloud VRE common services available at M36, reporting the design principles and reference software architecture of the released solutions. Specifically, Section 3 describes the analytics computing framework which includes the Analytics Engine, Galaxy workflows, the RStudio and the Jupyter Notebooks via JupyterHub. Section 4 presents the VRE Catalogue framework and its components, and section 5 reports on the Storage framework. ● Finally, section 6 concludes the report by illustrating the services composing the Enabling framework, which is used as a common ground for all the above-mentioned frameworks.DOI: 10.5281/zenodo.18189109
Project(s): A federated European FAIR and Open Research Ecosystem for oceans, seas, coastal and inland waters, Blue-Cloud+2026
Metrics:
Assante M., Candela L., Dalla Torre G., Dell'Amico A., Fernandez E., Frosini L., Lettere M., Mangiacrapa F., Molinaro E., Mugnaini M., Oliviero A., Pagano P., Panichi G., Peccerillo B., Piccioli T.
This deliverable documents the design principles and software architecture characterising the release and development of the Blue-Cloud Virtual Research Environment (VRE) common services, namely the analytics computing framework, the catalogue framework, the storage framework and the enabling framework components. This report is the second of two versions, each one describing the design associated with a specific version of the VRE. This deliverable D5.4 provides the updated and extended version of D5.1 “Blue-Cloud VRE Common Services 1st Release” [8]. The document presents the current state of the Blue-Cloud Virtual Research Environment (VRE) common services, detailing both the new components introduced in the period M13 to M36 and the enhancements applied to the existing ones to ensure compliance with interoperability, scalability, and robustness requirements. Overall, deliverable D5.4 provides a consolidated, fully up-to-date view of the Blue-Cloud VRE common services architecture, covering functional capabilities, API exposure, deployment configuration, and integration status as of the end of the second reporting period. The deliverable consists of six sections. ● Section 1 briefly introduces the role of this deliverable in the development and delivery of the Blue-Cloud VRE common services. ● Section 2 describes the Blue-Cloud VRE logical architecture of the common services and how they relate to the other services available in the VRE. ● Section 3, 4, 5 and 6 document the release of the Blue-Cloud VRE common services available at M36, reporting the design principles and reference software architecture of the released solutions. Specifically, Section 3 describes the analytics computing framework which includes the Analytics Engine, Galaxy workflows, the RStudio and the Jupyter Notebooks via JupyterHub. Section 4 presents the VRE Catalogue framework and its components, and section 5 reports on the Storage framework. ● Finally, section 6 concludes the report by illustrating the services composing the Enabling framework, which is used as a common ground for all the above-mentioned frameworks.DOI: 10.5281/zenodo.18189109
Project(s): A federated European FAIR and Open Research Ecosystem for oceans, seas, coastal and inland waters, Blue-Cloud+2026
Metrics:
2024
Other
Restricted
FOSSR D6.1B - Architecture System Specification
Marangio F., Assante M., Candela L., Nuzzolese A. G., Scisci D., Ciampi M., Damiano E.
This document aims to illustrate the FOSSR system architecture and design methodology used. First, the deliverable describes functional and non-functional requirements appropriately categorized (e.g. requirements for the web portal, a marketplace that allows users to use FOSSR tools, single sign-on, suitable services for data curation, discovery, harmonization, anonymization, and management). Second, the document will describe the identified functions of the system and related scenarios using UML Use Case and Sequence diagrams. Finally, the architecture to be developed will be shown, going on to describe the modules that will compose it and some critical aspects, such as those related to security and the actual deployment of data centres.Project(s): Fostering Open Science in Social Science Research
Marangio F., Assante M., Candela L., Nuzzolese A. G., Scisci D., Ciampi M., Damiano E.
This document aims to illustrate the FOSSR system architecture and design methodology used. First, the deliverable describes functional and non-functional requirements appropriately categorized (e.g. requirements for the web portal, a marketplace that allows users to use FOSSR tools, single sign-on, suitable services for data curation, discovery, harmonization, anonymization, and management). Second, the document will describe the identified functions of the system and related scenarios using UML Use Case and Sequence diagrams. Finally, the architecture to be developed will be shown, going on to describe the modules that will compose it and some critical aspects, such as those related to security and the actual deployment of data centres.Project(s): Fostering Open Science in Social Science Research
2024
Conference article
Open Access
Introducing Janet: early findings on a conversational agent for virtual research environments
Ibrahim A. S. T., Candela L.
Conversational agents have the potential to streamline tasks, provide support, and enhance user experience across various domains including Virtual Research Environments (VREs). The recent progress in conversational artificial intelligence and large language models (LLMs) offers novel strategies for the development of these agents. Janet is an attempt to develop an agent that, by leveraging the resources within the VRE, can engage in natural language conversations with VRE users to help them manage their daily activities, find relevant information, and use what the specific environment offers. It is developed following the Retrieval-Augmented Generation paradigm, a technique that reduces the effect of one of the limitations affecting LLMs; namely, hallucination. This paper highlights the lessons learned during the development of Janet.DOI: 10.5281/zenodo.13862920
Project(s): Blue-Cloud 2026, Skills4EOSC , SoBigData RI PPP
Metrics:
Ibrahim A. S. T., Candela L.
Conversational agents have the potential to streamline tasks, provide support, and enhance user experience across various domains including Virtual Research Environments (VREs). The recent progress in conversational artificial intelligence and large language models (LLMs) offers novel strategies for the development of these agents. Janet is an attempt to develop an agent that, by leveraging the resources within the VRE, can engage in natural language conversations with VRE users to help them manage their daily activities, find relevant information, and use what the specific environment offers. It is developed following the Retrieval-Augmented Generation paradigm, a technique that reduces the effect of one of the limitations affecting LLMs; namely, hallucination. This paper highlights the lessons learned during the development of Janet.DOI: 10.5281/zenodo.13862920
Project(s): Blue-Cloud 2026
, Skills4EOSC , SoBigData RI PPP Metrics:
See at:
CNR IRIS | zenodo.org | CNR IRIS
2024
Conference article
Open Access
D4Science: advancing ocean science through collaborative data analysis
Assante M., Candela L., Frosini L., Mangiacrapa F., Molinaro E., Pagano P.
In the realm of ocean science, addressing intricate challenges necessitates collaborative analysis of extensive datasets. This underscores the significance of infrastructures that facilitate multidisciplinary collaboration, effective communication, and timely data sharing. D4Science [Assante et al., 2019], an operational infrastructure initiated 18 years ago with European Commission funding, has evolved into an efficient solution. Utilizing the “as a Service” paradigm, D4Science provides webaccessible Virtual Laboratories [Assante et al., 2023; Candela et al., 2023] (VLabs) that proved to be also suitable for ocean science collaboration [Schaap et al., 2022]. These VLabs simplify access to marine datasets, concealing underlying complexities. Key functionalities include a cloudbased Workspace for file organization, a platform for largescale data analysis on a distributed computing infrastructure, a catalog for publishing research results, and a communication system based on social network practices. D4Science has been actively supporting diverse marine and ocean science Virtual Laboratories (VLabs), adapting to evolving research needs. Notable initiatives include contributions to the European Open Science Cloud (EOSC), starting with the ‘BlueCloud’ project in 2020 and its subsequent extension, ‘BlueCloud2026.’ In 2015, D4Science played a pivotal role in the BlueBRIDGE Horizon 2020 Project, which aimed to provide userfriendly data services and tools for the aquaculture, fisheries, and environmental sectors. Additionally, in 2013, D4Science contributed to the iMarine FP7 Project, which has since evolved into the current iMarine initiative. This ongoing effort is dedicated to establishing and operating an einfrastructure that aligns with the principles of the ecosystem approach to fisheries management and the conservation of marine living resources, further supporting the Food and Agriculture Organization’s (FAO) Blue Growth Initiative. D4Science is currently supporting over 20 scientific communities and over 150 VLabs, and pioneers Open Science in ocean research. It fosters collaboration, offers userfriendly environments, and provides service for accessing, sharing, analyzing, and publishing oceanographic data. A detailed description of these services is given in the followingSource: MISCELLANEA INGV, pp. 284-286. Bergen (Norway), 27-29/05/2024
DOI: 10.13127/misc/80/109
Project(s): Blue-Cloud 2026
Metrics:
Assante M., Candela L., Frosini L., Mangiacrapa F., Molinaro E., Pagano P.
In the realm of ocean science, addressing intricate challenges necessitates collaborative analysis of extensive datasets. This underscores the significance of infrastructures that facilitate multidisciplinary collaboration, effective communication, and timely data sharing. D4Science [Assante et al., 2019], an operational infrastructure initiated 18 years ago with European Commission funding, has evolved into an efficient solution. Utilizing the “as a Service” paradigm, D4Science provides webaccessible Virtual Laboratories [Assante et al., 2023; Candela et al., 2023] (VLabs) that proved to be also suitable for ocean science collaboration [Schaap et al., 2022]. These VLabs simplify access to marine datasets, concealing underlying complexities. Key functionalities include a cloudbased Workspace for file organization, a platform for largescale data analysis on a distributed computing infrastructure, a catalog for publishing research results, and a communication system based on social network practices. D4Science has been actively supporting diverse marine and ocean science Virtual Laboratories (VLabs), adapting to evolving research needs. Notable initiatives include contributions to the European Open Science Cloud (EOSC), starting with the ‘BlueCloud’ project in 2020 and its subsequent extension, ‘BlueCloud2026.’ In 2015, D4Science played a pivotal role in the BlueBRIDGE Horizon 2020 Project, which aimed to provide userfriendly data services and tools for the aquaculture, fisheries, and environmental sectors. Additionally, in 2013, D4Science contributed to the iMarine FP7 Project, which has since evolved into the current iMarine initiative. This ongoing effort is dedicated to establishing and operating an einfrastructure that aligns with the principles of the ecosystem approach to fisheries management and the conservation of marine living resources, further supporting the Food and Agriculture Organization’s (FAO) Blue Growth Initiative. D4Science is currently supporting over 20 scientific communities and over 150 VLabs, and pioneers Open Science in ocean research. It fosters collaboration, offers userfriendly environments, and provides service for accessing, sharing, analyzing, and publishing oceanographic data. A detailed description of these services is given in the followingSource: MISCELLANEA INGV, pp. 284-286. Bergen (Norway), 27-29/05/2024
DOI: 10.13127/misc/80/109
Project(s): Blue-Cloud 2026
Metrics:
See at:
CNR IRIS | imdis.seadatanet.org | doi.org | IRIS Cnr | CNR IRIS
2024
Other
Open Access
SoBigData++ - SoBigData e-Infrastructure Operation Report 3
Assante M., Candela L., Dell'Amico A., Frosini L., Mangiacrapa F., Molinaro E., Oliviero A., Pagano P., Panichi G., Piccioli T.
This Deliverable builds upon and updates the previous reports, D9.2 - “SoBigData e-Infrastructure Operation Report 2” [5] and D9.1 - “SoBigData e-Infrastructure Operation Report 1” [3]. The SoBigData e-Infrastructure has been pivotal in enabling the core services and research support required for the SoBigData++ project, including Virtual Research Environments (VREs), the Catalogue, and Analytics Services. It is accessible through the SoBigData gateway (https://sobigdata.d4science.org), which provides end-users with seamless access to tools, datasets, and services. The SoBigData e-Infrastructure is built upon the D4Science infrastructure, offering a comprehensive platform that facilitates collaborative, transparent, and interdisciplinary research. The deployment and operation of VREs followed a well-defined procedure, leveraging the consolidated process inherited from D4Science. Throughout the 60 months of the project, a total of 27 VREs were created and operated to meet project and community needs. These VREs were classified into five categories: Exploratories, Applications, Virtual Labs, Training, and Management. Notable examples include, (i) SoBigDataLab and SoBigDataLab-PlusPlus for method development and experiments, (ii) Training VREs created for events like Summer Schools and specialised workshops, and (iii) Research spaces (formerly known as Exploratories) supporting targeted domains, such as Migration Studies, Sports Data Science, and Social Impacts of AI. The SoBigData Catalogue (https://sobigdata.d4science.org/catalogue-sobigdata) emerged as a critical resource for both human users and integrated services, enabling access to datasets, services, and analytical methods. The catalogue supports customisable item profiles enriched with metadata fields, controlled vocabularies, and validation rules. By end of term, the Catalogue recorded significant growth, particularly in key item types such as Methods (192 items) and Datasets (250 items). This expansion underscores the Catalogue’s role in promoting resource discoverability and supporting research workflows. Its usage indicators demonstrate its active adoption, with 31,909 total accesses, 29,595 metadata views, and 4,171 resource views recorded. Monthly trends reveal consistent engagement, highlighting its importance in the research ecosystem. The Social Mining Analytics Engine (SMAE) transitioned through the development of a new service, namely Cloud Computing Platform (CCP), offering enhanced scalability and automation through container orchestrations. Methods hosted on the SMAE span multiple categories, such as Text Processing, Web Analytics, and Image Analysis. Over the last year, the platform executed an average of 6.4 million method invocations per month, peaking at 16 million executions in July 2024. As of mid-December ’24, the e-infrastructure serves more than 13,000 users, with an overall trend in the use of the SoBigData VREs from January 2020 to December 2024, highlighting their importance for the research community. The steady engagement through 2023 and 2024, with peaks like July 2024 (2,592 sessions), underscores the VREs continued relevance and utility.Project(s): SoBigData-PlusPlus
Assante M., Candela L., Dell'Amico A., Frosini L., Mangiacrapa F., Molinaro E., Oliviero A., Pagano P., Panichi G., Piccioli T.
This Deliverable builds upon and updates the previous reports, D9.2 - “SoBigData e-Infrastructure Operation Report 2” [5] and D9.1 - “SoBigData e-Infrastructure Operation Report 1” [3]. The SoBigData e-Infrastructure has been pivotal in enabling the core services and research support required for the SoBigData++ project, including Virtual Research Environments (VREs), the Catalogue, and Analytics Services. It is accessible through the SoBigData gateway (https://sobigdata.d4science.org), which provides end-users with seamless access to tools, datasets, and services. The SoBigData e-Infrastructure is built upon the D4Science infrastructure, offering a comprehensive platform that facilitates collaborative, transparent, and interdisciplinary research. The deployment and operation of VREs followed a well-defined procedure, leveraging the consolidated process inherited from D4Science. Throughout the 60 months of the project, a total of 27 VREs were created and operated to meet project and community needs. These VREs were classified into five categories: Exploratories, Applications, Virtual Labs, Training, and Management. Notable examples include, (i) SoBigDataLab and SoBigDataLab-PlusPlus for method development and experiments, (ii) Training VREs created for events like Summer Schools and specialised workshops, and (iii) Research spaces (formerly known as Exploratories) supporting targeted domains, such as Migration Studies, Sports Data Science, and Social Impacts of AI. The SoBigData Catalogue (https://sobigdata.d4science.org/catalogue-sobigdata) emerged as a critical resource for both human users and integrated services, enabling access to datasets, services, and analytical methods. The catalogue supports customisable item profiles enriched with metadata fields, controlled vocabularies, and validation rules. By end of term, the Catalogue recorded significant growth, particularly in key item types such as Methods (192 items) and Datasets (250 items). This expansion underscores the Catalogue’s role in promoting resource discoverability and supporting research workflows. Its usage indicators demonstrate its active adoption, with 31,909 total accesses, 29,595 metadata views, and 4,171 resource views recorded. Monthly trends reveal consistent engagement, highlighting its importance in the research ecosystem. The Social Mining Analytics Engine (SMAE) transitioned through the development of a new service, namely Cloud Computing Platform (CCP), offering enhanced scalability and automation through container orchestrations. Methods hosted on the SMAE span multiple categories, such as Text Processing, Web Analytics, and Image Analysis. Over the last year, the platform executed an average of 6.4 million method invocations per month, peaking at 16 million executions in July 2024. As of mid-December ’24, the e-infrastructure serves more than 13,000 users, with an overall trend in the use of the SoBigData VREs from January 2020 to December 2024, highlighting their importance for the research community. The steady engagement through 2023 and 2024, with peaks like July 2024 (2,592 sessions), underscores the VREs continued relevance and utility.Project(s): SoBigData-PlusPlus
2024
Other
Open Access
Skills 4 eosc - Sample of services toolset: a practical guideline
Candela L., Corleto A., Green D., Lembinen L., Liisi C., Vudragovic D., Zimniewicz M.
This Deliverable describes a minimal set of tools and technologies that proven effective in helping Skills4EOSC Competence Centres achieve their goals. These tools belong to four major classes: (i) tools and solutions for training management, (ii) tools and solutions for collaborative work, (iii) tools and solutions for publishing, (iv) tools and solutions for virtual laboratories. The list of tools is complemented by a set of recommendations helping Competence Centres to take informed decisions concerning tools and services to offer to their designated community.DOI: 10.5281/zenodo.14230226
Project(s): Skills4EOSC
Metrics:
Candela L., Corleto A., Green D., Lembinen L., Liisi C., Vudragovic D., Zimniewicz M.
This Deliverable describes a minimal set of tools and technologies that proven effective in helping Skills4EOSC Competence Centres achieve their goals. These tools belong to four major classes: (i) tools and solutions for training management, (ii) tools and solutions for collaborative work, (iii) tools and solutions for publishing, (iv) tools and solutions for virtual laboratories. The list of tools is complemented by a set of recommendations helping Competence Centres to take informed decisions concerning tools and services to offer to their designated community.DOI: 10.5281/zenodo.14230226
Project(s): Skills4EOSC
Metrics:
2024
Other
Open Access
Blue-Cloud VRE operation report
Assante M., Candela L., Calanducci A., Cirillo R., Dell’amico A., Frosini L., Lelii L., Molinaro E., Mangiacrapa F., Oliviero A., Pagano P., Panichi G., Piccioli T.
The Horizon Europe Blue-Cloud initiative started in 2019 with the aim of creating a European Open Science Cloud for marine data. This involves federating data and e-infrastructures to provide data products and technologies as open science resources for the wider marine research community. Since 2023, the Blue-Cloud 2026 follow-up project has sought to further evolve this pilot ecosystem into a Federated European Ecosystem, offering FAIR and open data and analytical services crucial for advancing research on oceans, EU seas, and coastal and inland waters. Building on the pilot Blue-Cloud project, the current technical framework is designed to be extensible and open, continually evolving to meet the community's needs. The Blue-Cloud platform architecture comprises two major components: (a) the Blue-Cloud Data Discovery and Access Service (DDAS) component, which facilitates federated discovery and access to 'blue data' infrastructures, and (b) the Blue-Cloud Virtual Research Environment (VRE) component, which provides a Blue-Cloud VRE as a federation of computing platforms and analytical services. The VLabs leverage both DDAS and VRE, co-created with leading marine researchers to demonstrate the power of the Blue-Cloud Open Science platform through real-life scientific cases. \ This deliverable focuses on the VRE operation, specifically on how the VRE services have been utilised and managed to support the development of the Blue-Cloud VRE gateway (https://blue-cloud.d4science.org), its underlying infrastructure, and the VLabs on top of it, during the reporting period from January 2023 (M1) to June 2024 (M18). A total of 13 VLabs were created and operated to meet the needs arising from the Blue-Cloud 2026 project. Additionally, 7 VLabs from the previous Blue-Cloud project are being maintained. These working environments serve more than 1,700 users from 34 countries. Between January 2023 and June 2024, users initiated more than 26,000 working sessions via the Blue-Cloud VRE, averaging 1,447 sessions per month. Operating the VRE and VLabs involves managing support requests, issues, and incidents. A total of 143 tickets have been created and managed in the Blue-Cloud Project Issue Trackers (23 in the project consortium tracker and 120 in the support tracker), with 85% of these tickets closed. Additionally, 24 tickets related to Blue-Cloud have been created within the D4Science overall context, with an 88% closure rate.DOI: 10.5281/zenodo.12667549
Project(s): Blue-Cloud 2026
Metrics:
Assante M., Candela L., Calanducci A., Cirillo R., Dell’amico A., Frosini L., Lelii L., Molinaro E., Mangiacrapa F., Oliviero A., Pagano P., Panichi G., Piccioli T.
The Horizon Europe Blue-Cloud initiative started in 2019 with the aim of creating a European Open Science Cloud for marine data. This involves federating data and e-infrastructures to provide data products and technologies as open science resources for the wider marine research community. Since 2023, the Blue-Cloud 2026 follow-up project has sought to further evolve this pilot ecosystem into a Federated European Ecosystem, offering FAIR and open data and analytical services crucial for advancing research on oceans, EU seas, and coastal and inland waters. Building on the pilot Blue-Cloud project, the current technical framework is designed to be extensible and open, continually evolving to meet the community's needs. The Blue-Cloud platform architecture comprises two major components: (a) the Blue-Cloud Data Discovery and Access Service (DDAS) component, which facilitates federated discovery and access to 'blue data' infrastructures, and (b) the Blue-Cloud Virtual Research Environment (VRE) component, which provides a Blue-Cloud VRE as a federation of computing platforms and analytical services. The VLabs leverage both DDAS and VRE, co-created with leading marine researchers to demonstrate the power of the Blue-Cloud Open Science platform through real-life scientific cases. \ This deliverable focuses on the VRE operation, specifically on how the VRE services have been utilised and managed to support the development of the Blue-Cloud VRE gateway (https://blue-cloud.d4science.org), its underlying infrastructure, and the VLabs on top of it, during the reporting period from January 2023 (M1) to June 2024 (M18). A total of 13 VLabs were created and operated to meet the needs arising from the Blue-Cloud 2026 project. Additionally, 7 VLabs from the previous Blue-Cloud project are being maintained. These working environments serve more than 1,700 users from 34 countries. Between January 2023 and June 2024, users initiated more than 26,000 working sessions via the Blue-Cloud VRE, averaging 1,447 sessions per month. Operating the VRE and VLabs involves managing support requests, issues, and incidents. A total of 143 tickets have been created and managed in the Blue-Cloud Project Issue Trackers (23 in the project consortium tracker and 120 in the support tracker), with 85% of these tickets closed. Additionally, 24 tickets related to Blue-Cloud have been created within the D4Science overall context, with an 88% closure rate.DOI: 10.5281/zenodo.12667549
Project(s): Blue-Cloud 2026
Metrics:
2024
Journal article
Open Access
The FAIR Assessment Conundrum: reflections on tools and metrics
Candela L., Mangione D., Pavone G.
Several tools for assessing FAIRness have been developed. Although their purpose is common, they use different assessment techniques, they are designed to work with diverse research products, and they are applied in specific scientific disciplines. It is thus inevitable that they perform the assessment using different metrics. This paper provides an overview of the actual FAIR assessment tools and metrics landscape to highlight the challenges characterising this task. In particular, 20 relevant FAIR assessment tools and 1180 relevant metrics were identified and analysed concerning (i) the tool’s distinguishing aspects and their trends, (ii) the gaps between the metric intents and the FAIR principles, (iii) the discrepancies between the declared intent of the metrics and the actual aspects assessed, including the most recurring issues, (iv) the technologies used or mentioned the most in the assessment metrics. The findings highlight (a) the distinguishing characteristics of the tools and the emergence of trends over time concerning those characteristics, (b) the identification of gaps at both metric and tool levels, (c) discrepancies observed in 345 metrics between their declared intent and the actual aspects assessed, pointing at several recurring issues, and (d) the variety in the technology used for the assessments, the majority of which can be ascribed to linked data solutions. This work also highlights some open issues that FAIR assessment still needs to address.Source: DATA SCIENCE JOURNAL, vol. 23
DOI: 10.5334/dsj-2024-033
Project(s): Blue-Cloud 2026, Blue Cloud , Skills4EOSC , SoBigData-PlusPlus
Metrics:
Candela L., Mangione D., Pavone G.
Several tools for assessing FAIRness have been developed. Although their purpose is common, they use different assessment techniques, they are designed to work with diverse research products, and they are applied in specific scientific disciplines. It is thus inevitable that they perform the assessment using different metrics. This paper provides an overview of the actual FAIR assessment tools and metrics landscape to highlight the challenges characterising this task. In particular, 20 relevant FAIR assessment tools and 1180 relevant metrics were identified and analysed concerning (i) the tool’s distinguishing aspects and their trends, (ii) the gaps between the metric intents and the FAIR principles, (iii) the discrepancies between the declared intent of the metrics and the actual aspects assessed, including the most recurring issues, (iv) the technologies used or mentioned the most in the assessment metrics. The findings highlight (a) the distinguishing characteristics of the tools and the emergence of trends over time concerning those characteristics, (b) the identification of gaps at both metric and tool levels, (c) discrepancies observed in 345 metrics between their declared intent and the actual aspects assessed, pointing at several recurring issues, and (d) the variety in the technology used for the assessments, the majority of which can be ascribed to linked data solutions. This work also highlights some open issues that FAIR assessment still needs to address.Source: DATA SCIENCE JOURNAL, vol. 23
DOI: 10.5334/dsj-2024-033
Project(s): Blue-Cloud 2026
, Blue Cloud , Skills4EOSC , SoBigData-PlusPlus Metrics:
See at:
IRIS Cnr | Data Science Journal | Data Science Journal | IRIS Cnr | CNR IRIS | CNR IRIS
2024
Conference article
Open Access
An overview of Open Science in Italy
Bardi A., Candela L., Mangione D., Pavone G.
Open Science is a phenomenon pervading scientific practices to make scientific research and its outputs more accessible, transparent, and collaborative. It is gaining momentum globally, and various initiatives were and are underway to promote it. However, implementation varies across disciplines, regions, and institutions. This paper overviews the current state of open science implementation in Italy by analysing the established policies, the scientific production, and the available services documented by several publicly available information systems.Source: CEUR WORKSHOP PROCEEDINGS, vol. 3643, pp. 126-139. Bressanone, Brixen, Italy, 22-23/02/2024
Project(s): Skills4EOSC, SoBigData RI PPP
Bardi A., Candela L., Mangione D., Pavone G.
Open Science is a phenomenon pervading scientific practices to make scientific research and its outputs more accessible, transparent, and collaborative. It is gaining momentum globally, and various initiatives were and are underway to promote it. However, implementation varies across disciplines, regions, and institutions. This paper overviews the current state of open science implementation in Italy by analysing the established policies, the scientific production, and the available services documented by several publicly available information systems.Source: CEUR WORKSHOP PROCEEDINGS, vol. 3643, pp. 126-139. Bressanone, Brixen, Italy, 22-23/02/2024
Project(s): Skills4EOSC
, SoBigData RI PPP
See at:
ceur-ws.org | CNR IRIS | CNR IRIS
2024
Conference article
Open Access
New tools for geo-scientific data management in the framework of the ITINERIS Project leveraging D4Science e-infrastructure capabilities
Gennaro S., Di Giuseppe P., Perrone E., Agostini S., Trumpy E., Assante M., Candela L., Pagano P., Procaccini M., Coro G., Provenzale A.
Open Science is a cultural movement based on transparency, inclusion, research integrity, collaboration, and cooperative work, promoting an enhancing approach to science. Benefits are expected from this approach, although doing open science can entail a contrast with several barriers, including: (i) cultural factors (e.g., the fear of the loss of control of the datasets); (ii) cost-base factors; and (iii) disincentive factors (Assante et al., 2019; 2023). The effectiveness of the Open Science approach of a project can be enhanced by using the D4Science infrastructure. This infrastructure promotes collaboration and cooperative work with Virtual Research Environments (VREs). As part of the ITINERIS Project, a comprehensive Italian Research Infrastructures (RDIs) hub in the geoscientific and environmental fields is under development, in which teams with a high level of trans-disciplinarity are working on the development of thematic VREs for topics that includes: (i) Critical Zone (CZ) VRE; (ii) Aquatic Biomass services (BIOMASS) VRE; (iii) Crops, Plants and Pests services (CPP VRE); (iv) Essential Variables (EV VRE); (v) Aerosol-biosphere (AERO VRE); (vi) Carbon Cycle services (CARBON VRE); (vii) Indicators and Impacts of Climate Change (CLIMA VRE); (viii) Downstream Effects of Environmental Change (DOWNSTREAM VRE); (ix) Isotope Database (ISOTOPE VRE). VREs are based on the D4Science infrastructure, and their development is based on the needs of the scientific communities and the specific stakeholders identified by the researcher. VREs are new eScience facilities that address scientifically and socially relevant topics, especially through the sharing of information and data produced. Research data and results products following international standards are managed and shared with the members of the VREs. In this context, these D4Science enabled VREs will become tools supporting the entire spectrum of the research lifecycle. Specifically, for data collection (i) the Collaborative Storage Framework promotes teamwork among users and offers a collaborative space to share digital objects. For data analytics, (ii) the Analytics Engine Framework equips VREs with Cloud Computing Platforms. For data publishing, (iii) the Publishing Framework facilitates the dissemination of research outcomes by means of the Metadata Catalogue and the Spatial Data Catalogue, which help organise and make research results available to the broader scientific community. Moreover, VREs are planned with a modular structure with semantic services for data discovery, harmonization and interoperability, and will contribute to share workflows, procedures and analysis tools which could be applied to analyse new datasets by the members of the VRE. Data from multiple sources, analysis and modelling tools will be integrated into the VREs, allowing users to gain insights into the problems at hand and add their data and analysis methods to respond to the changing scientific and practical needs.DOI: 10.3301/absgi.2024.02
Metrics:
Gennaro S., Di Giuseppe P., Perrone E., Agostini S., Trumpy E., Assante M., Candela L., Pagano P., Procaccini M., Coro G., Provenzale A.
Open Science is a cultural movement based on transparency, inclusion, research integrity, collaboration, and cooperative work, promoting an enhancing approach to science. Benefits are expected from this approach, although doing open science can entail a contrast with several barriers, including: (i) cultural factors (e.g., the fear of the loss of control of the datasets); (ii) cost-base factors; and (iii) disincentive factors (Assante et al., 2019; 2023). The effectiveness of the Open Science approach of a project can be enhanced by using the D4Science infrastructure. This infrastructure promotes collaboration and cooperative work with Virtual Research Environments (VREs). As part of the ITINERIS Project, a comprehensive Italian Research Infrastructures (RDIs) hub in the geoscientific and environmental fields is under development, in which teams with a high level of trans-disciplinarity are working on the development of thematic VREs for topics that includes: (i) Critical Zone (CZ) VRE; (ii) Aquatic Biomass services (BIOMASS) VRE; (iii) Crops, Plants and Pests services (CPP VRE); (iv) Essential Variables (EV VRE); (v) Aerosol-biosphere (AERO VRE); (vi) Carbon Cycle services (CARBON VRE); (vii) Indicators and Impacts of Climate Change (CLIMA VRE); (viii) Downstream Effects of Environmental Change (DOWNSTREAM VRE); (ix) Isotope Database (ISOTOPE VRE). VREs are based on the D4Science infrastructure, and their development is based on the needs of the scientific communities and the specific stakeholders identified by the researcher. VREs are new eScience facilities that address scientifically and socially relevant topics, especially through the sharing of information and data produced. Research data and results products following international standards are managed and shared with the members of the VREs. In this context, these D4Science enabled VREs will become tools supporting the entire spectrum of the research lifecycle. Specifically, for data collection (i) the Collaborative Storage Framework promotes teamwork among users and offers a collaborative space to share digital objects. For data analytics, (ii) the Analytics Engine Framework equips VREs with Cloud Computing Platforms. For data publishing, (iii) the Publishing Framework facilitates the dissemination of research outcomes by means of the Metadata Catalogue and the Spatial Data Catalogue, which help organise and make research results available to the broader scientific community. Moreover, VREs are planned with a modular structure with semantic services for data discovery, harmonization and interoperability, and will contribute to share workflows, procedures and analysis tools which could be applied to analyse new datasets by the members of the VRE. Data from multiple sources, analysis and modelling tools will be integrated into the VREs, allowing users to gain insights into the problems at hand and add their data and analysis methods to respond to the changing scientific and practical needs.DOI: 10.3301/absgi.2024.02
Metrics:
See at:
CNR IRIS | www.socgeol.it | doi.org | CNR IRIS
2024
Dataset
Open Access
An overview of Open Science in Italy - Data set
Bardi A., Candela L., Mangione D., Pavone G.
Data sets accompanying the paper "An Overview of Open Science in Italy", an overview of the current state of open science implementation in Italy. See the readme.txt for a detailed description of the data sets. The data sets atenei.csv and altri-istituti-ricerca.csv document the organisation selection resulting from the list of Italian universities recognised by the Ministero dell'Università e della Ricerca, the aggregation of data from a crowdsourcing activity born within the Open Access Italia mailing list, from the catalogue of policies of the open-science.it portal, as well as from the survey by the Open Science Working Group of CoPER on the monitoring of institutional policies for the management of scientific data. The data set policies.csv consists of the list of documents (among policies, guidelines and regulations) that are related to the observed organisations. The data set ita_publications_openaire.csv.zip includes records about italian publications selected from the OpenAIRE Graph based on affiliation relationships. The data set is created via the Zeppelin Note available at 10.5281/zenodo.10640721. The data set openaire_observatory_it.csv reports the aggregated data with respect to the Italian open access (OA) and closed research products, from 2015 to 2023, retrieved from the OpenAIRE Open Science Observatory. The data set openaire_observatory_eu.csv consists of the aggregated data on the top eleven European countries for the OA research production (publications, data sets, software, and other research products), from 2015 to 2023, retrieved from the OpenAIRE Open Science Observatory. The data set coki_years.csv consists of the aggregated indicators on the Italian OA production from 2000 to 2023. The data set coki_it.csv consists of the selection of indicators on open and closed publications (from 2015 to 2023) from the coki_years.csv. The data sets services_re3data.csv, services_opendoar.csv, services_eoscmarketplace.csv, and services_fairsharing.csv consist of the records identifying italian services for open science downloaded from re3data, OpenDOAR, the EOSC Marketplace, and FAIRsharing respectively.DOI: 10.5281/zenodo.10611000
Project(s): Skills4EOSC, SoBigData RI PPP
Metrics:
Bardi A., Candela L., Mangione D., Pavone G.
Data sets accompanying the paper "An Overview of Open Science in Italy", an overview of the current state of open science implementation in Italy. See the readme.txt for a detailed description of the data sets. The data sets atenei.csv and altri-istituti-ricerca.csv document the organisation selection resulting from the list of Italian universities recognised by the Ministero dell'Università e della Ricerca, the aggregation of data from a crowdsourcing activity born within the Open Access Italia mailing list, from the catalogue of policies of the open-science.it portal, as well as from the survey by the Open Science Working Group of CoPER on the monitoring of institutional policies for the management of scientific data. The data set policies.csv consists of the list of documents (among policies, guidelines and regulations) that are related to the observed organisations. The data set ita_publications_openaire.csv.zip includes records about italian publications selected from the OpenAIRE Graph based on affiliation relationships. The data set is created via the Zeppelin Note available at 10.5281/zenodo.10640721. The data set openaire_observatory_it.csv reports the aggregated data with respect to the Italian open access (OA) and closed research products, from 2015 to 2023, retrieved from the OpenAIRE Open Science Observatory. The data set openaire_observatory_eu.csv consists of the aggregated data on the top eleven European countries for the OA research production (publications, data sets, software, and other research products), from 2015 to 2023, retrieved from the OpenAIRE Open Science Observatory. The data set coki_years.csv consists of the aggregated indicators on the Italian OA production from 2000 to 2023. The data set coki_it.csv consists of the selection of indicators on open and closed publications (from 2015 to 2023) from the coki_years.csv. The data sets services_re3data.csv, services_opendoar.csv, services_eoscmarketplace.csv, and services_fairsharing.csv consist of the records identifying italian services for open science downloaded from re3data, OpenDOAR, the EOSC Marketplace, and FAIRsharing respectively.DOI: 10.5281/zenodo.10611000
Project(s): Skills4EOSC
, SoBigData RI PPP Metrics:
See at:
CNR IRIS | zenodo.org | CNR IRIS
2024
Other
Open Access
Dataset per il Geoportale Nazionale per l'Archeologia - Guida al Data-Viewer
Vannini G. L., Mangiacrapa F., Pagano P., Candela L.
The Dataset for the National Geoportal for Archeology (D4GNA) is a digital platform that allows access and consultation of archaeological data coming from 'Surveys carried out under concession regime (in Italian territory)' and from 'Italian archaeological missions to abroad'. This guide provides the necessary instructions to consult the datasets, navigate the interactive cartography and download the data. To access the D4GNA, you need to connect to the official website https://gna.d4science.org/.DOI: 10.5281/zenodo.12531823
DOI: https://doi.org/10.5281/zenodo.12531823
Project(s): ARIADNEplus
Metrics:
Vannini G. L., Mangiacrapa F., Pagano P., Candela L.
The Dataset for the National Geoportal for Archeology (D4GNA) is a digital platform that allows access and consultation of archaeological data coming from 'Surveys carried out under concession regime (in Italian territory)' and from 'Italian archaeological missions to abroad'. This guide provides the necessary instructions to consult the datasets, navigate the interactive cartography and download the data. To access the D4GNA, you need to connect to the official website https://gna.d4science.org/.DOI: 10.5281/zenodo.12531823
DOI: https://doi.org/10.5281/zenodo.12531823
Project(s): ARIADNEplus
Metrics: