2026
Journal article
Open Access
Charting the landscape of Italian Diamond Open Access publishing
Angioni Simone, Baglioni Miriam, Bardi Alessia, Manghi Paolo, Mannocci Andrea, Pavone Gina
Diamond Open Access (DOA) is a non-commercial model of scholarly publishing that removes financial barriers for authors and readers. While international studies have outlined the global uptake of DOA, this paper investigates the presence and characteristics of the DOA landscape in Italy. We conducted a quantitative analysis on the 168 Italian journals classified as Diamond by EZB, and we studied their publishing volume, disciplinary distribution and citation impact by integrating information from the following open resources: DOAJ, OpenAIRE, ROAD, SCImago Journal Rank, and the ANVUR classification used in the Italian Research Assessment Framework (VQR). Key findings include the significant growth of DOA journals, particularly in the social sciences and humanities, as well as the high level of international citations, indicating strong global relevance. The study also highlights challenges such as the need for better indexing and comprehensive data to fully capture the DOA landscape.Source: QUANTITATIVE SCIENCE STUDIES
DOI: 10.1162/qss.a.466
Metrics:
Angioni Simone, Baglioni Miriam, Bardi Alessia, Manghi Paolo, Mannocci Andrea, Pavone Gina
Diamond Open Access (DOA) is a non-commercial model of scholarly publishing that removes financial barriers for authors and readers. While international studies have outlined the global uptake of DOA, this paper investigates the presence and characteristics of the DOA landscape in Italy. We conducted a quantitative analysis on the 168 Italian journals classified as Diamond by EZB, and we studied their publishing volume, disciplinary distribution and citation impact by integrating information from the following open resources: DOAJ, OpenAIRE, ROAD, SCImago Journal Rank, and the ANVUR classification used in the Italian Research Assessment Framework (VQR). Key findings include the significant growth of DOA journals, particularly in the social sciences and humanities, as well as the high level of international citations, indicating strong global relevance. The study also highlights challenges such as the need for better indexing and comprehensive data to fully capture the DOA landscape.Source: QUANTITATIVE SCIENCE STUDIES
DOI: 10.1162/qss.a.466
Metrics:
See at:
direct.mit.edu 
| CNR IRIS | CNR IRIS 
2025
Journal article
Open Access
A survey of knowledge organization systems of research fields: resources and challenges
Salatino A., Aggarwal T., Mannocci A., Osborne F., Motta E.
Knowledge organization systems (KOSs), such as term lists, thesauri, taxonomies, andontologies, play a fundamental role in categorizing, managing, and retrieving information. Inthe academic domain, KOSs are often adopted for representing research areas and theirrelationships, primarily aiming to classify research articles, academic courses, patents, books,scientific venues, domain experts, grants, software, experiment materials, and several otherrelevant products and agents. These structured representations of research areas, widelyembraced by many academic fields, have proven effective in empowering AI-based systems toenhance the retrievability of relevant documents, enable advanced analytic solutions toquantify the impact of academic research, and analyze and forecast research dynamics.We aim to present a comprehensive survey of the current KOS for academic disciplines.We analyzed and compared 45 KOSs according to five main dimensions: scope, structure,curation, usage, and links to other KOSs. Our results reveal a very heterogeneous scenario interms of scope, scale, quality, and usage, highlighting the need for more integrated solutionsfor representing research knowledge across academic fields. We conclude by discussing themain challenges and the most promising future directions.Source: QUANTITATIVE SCIENCE STUDIES, vol. 6, pp. 567-610
DOI: 10.1162/qss_a_00363
Metrics:
Salatino A., Aggarwal T., Mannocci A., Osborne F., Motta E.
Knowledge organization systems (KOSs), such as term lists, thesauri, taxonomies, andontologies, play a fundamental role in categorizing, managing, and retrieving information. Inthe academic domain, KOSs are often adopted for representing research areas and theirrelationships, primarily aiming to classify research articles, academic courses, patents, books,scientific venues, domain experts, grants, software, experiment materials, and several otherrelevant products and agents. These structured representations of research areas, widelyembraced by many academic fields, have proven effective in empowering AI-based systems toenhance the retrievability of relevant documents, enable advanced analytic solutions toquantify the impact of academic research, and analyze and forecast research dynamics.We aim to present a comprehensive survey of the current KOS for academic disciplines.We analyzed and compared 45 KOSs according to five main dimensions: scope, structure,curation, usage, and links to other KOSs. Our results reveal a very heterogeneous scenario interms of scope, scale, quality, and usage, highlighting the need for more integrated solutionsfor representing research knowledge across academic fields. We conclude by discussing themain challenges and the most promising future directions.Source: QUANTITATIVE SCIENCE STUDIES, vol. 6, pp. 567-610
DOI: 10.1162/qss_a_00363
Metrics:
See at:
direct.mit.edu | CNR IRIS | CNR IRIS
2025
Journal article
Open Access
Towards the interoperability of scholarly repository registries
Baglioni M., Pavone G., Mannocci A., Manghi P.
The enactment of Open Science relies on scholarly repositories that make research products findable and accessible, while scholarly repository registries maintain authoritative metadata and persistent identifiers (PIDs) to help researchers and infrastructure providers discover and access needed repositories. However, the proliferation of repositories targeting different research products (e.g., publications, data, and software) or serving specific disciplines has led to the creation of multiple registries whose scope is not mutually exclusive. Such a fragmented landscape poses significant concerns regarding authoritativeness, disambiguation, and coverage for scholarly communication service and infrastructure providers who consume content from these registries. These providers must either limit their focus to a single registry or manage complex data fusion strategies to integrate diverse repository profiles from various sources. While favouring the existence of a plurality of registries, this paper advocates for their interoperability, which is essential to eliminate the aforementioned barriers and enable their full, unambiguous utilisation. We analyse the data models of four prominent registries—FAIRsharing, re3data, OpenDOAR, and ROAR—and classify their properties and overlap. We provide a crosswalk between their data models and suggest a common data model shared across the examined registries to pave the way toward interoperability. As a means of validation, we include a coverage evaluation of the proposed data model.The paper adopts a pragmatic approach towards scholarly registry interoperability and suggests a common metadata model to foster the exchange of information across these platforms. The purpose of the paper is to serve as a cornerstone, initiating and engaging the community in discussions surrounding the interoperability of scholarly repository registries.Source: INTERNATIONAL JOURNAL ON DIGITAL LIBRARIES, vol. 26 (issue 1)
DOI: 10.1007/s00799-025-00414-y
Project(s): EOSC Future
, OpenAIRE Nexus
Metrics:
Baglioni M., Pavone G., Mannocci A., Manghi P.
The enactment of Open Science relies on scholarly repositories that make research products findable and accessible, while scholarly repository registries maintain authoritative metadata and persistent identifiers (PIDs) to help researchers and infrastructure providers discover and access needed repositories. However, the proliferation of repositories targeting different research products (e.g., publications, data, and software) or serving specific disciplines has led to the creation of multiple registries whose scope is not mutually exclusive. Such a fragmented landscape poses significant concerns regarding authoritativeness, disambiguation, and coverage for scholarly communication service and infrastructure providers who consume content from these registries. These providers must either limit their focus to a single registry or manage complex data fusion strategies to integrate diverse repository profiles from various sources. While favouring the existence of a plurality of registries, this paper advocates for their interoperability, which is essential to eliminate the aforementioned barriers and enable their full, unambiguous utilisation. We analyse the data models of four prominent registries—FAIRsharing, re3data, OpenDOAR, and ROAR—and classify their properties and overlap. We provide a crosswalk between their data models and suggest a common data model shared across the examined registries to pave the way toward interoperability. As a means of validation, we include a coverage evaluation of the proposed data model.The paper adopts a pragmatic approach towards scholarly registry interoperability and suggests a common metadata model to foster the exchange of information across these platforms. The purpose of the paper is to serve as a cornerstone, initiating and engaging the community in discussions surrounding the interoperability of scholarly repository registries.Source: INTERNATIONAL JOURNAL ON DIGITAL LIBRARIES, vol. 26 (issue 1)
DOI: 10.1007/s00799-025-00414-y
Project(s): EOSC Future
, OpenAIRE Nexus Metrics:
See at:
International Journal on Digital Libraries | CNR IRIS | link.springer.com | Software Heritage | Software Heritage | GitHub | GitHub | 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
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:
2024
Conference article
Open Access
Exploring scientometrics with the OpenAIRE Graph: introducing the OpenAIRE Beginner's Kit
Mannocci A., Baglioni M.
The OpenAIRE Graph is an extensive resource housing diverse information onresearch products, including literature, datasets, and software, alongsideresearch projects and other scholarly outputs and context. It stands as acornerstone among contemporary research information databases, offeringinvaluable insights for scientometric investigations. Despite its wealth ofdata, its sheer size may initially appear daunting, potentially hindering itswidespread adoption. To address this challenge, this paper introduces theOpenAIRE Beginner's Kit, a user-friendly solution providing access to a subsetof the OpenAIRE Graph within a sandboxed environment coupled with a Jupyternotebook for analysis. The OpenAIRE Beginner's Kit is meticulously designed todemocratise research and data exploration, offering accessibility from standarddesktop and laptop setups. Within this paper, we provide a brief overview ofthe included dataset and offer guidance on leveraging the kit through aselection of illustrative queries tailored to address common scientometricinquiries.
Mannocci A., Baglioni M.
The OpenAIRE Graph is an extensive resource housing diverse information onresearch products, including literature, datasets, and software, alongsideresearch projects and other scholarly outputs and context. It stands as acornerstone among contemporary research information databases, offeringinvaluable insights for scientometric investigations. Despite its wealth ofdata, its sheer size may initially appear daunting, potentially hindering itswidespread adoption. To address this challenge, this paper introduces theOpenAIRE Beginner's Kit, a user-friendly solution providing access to a subsetof the OpenAIRE Graph within a sandboxed environment coupled with a Jupyternotebook for analysis. The OpenAIRE Beginner's Kit is meticulously designed todemocratise research and data exploration, offering accessibility from standarddesktop and laptop setups. Within this paper, we provide a brief overview ofthe included dataset and offer guidance on leveraging the kit through aselection of illustrative queries tailored to address common scientometricinquiries.
2024
Conference article
Open Access
Exploring the Italian research landscape on Digital Library in the Conference IRCDL
Bernasconi E., Mannocci A., Tammaro A. M.
This study aims to explore the structure of knowledge around digital libraries embedded in IRCDL Conference presentations and examine research trends over time. It also analysed the published articles' subject, the authors, their affiliations and provenance and the collaboration network in IRCDL. We applied several bibliometric techniques, including productivity visualisation, authorship network analysis, and subject analysis.Source: CEUR WORKSHOP PROCEEDINGS, vol. 3643, pp. 230-245. Brixen, 22-23 February 2024.
Bernasconi E., Mannocci A., Tammaro A. M.
This study aims to explore the structure of knowledge around digital libraries embedded in IRCDL Conference presentations and examine research trends over time. It also analysed the published articles' subject, the authors, their affiliations and provenance and the collaboration network in IRCDL. We applied several bibliometric techniques, including productivity visualisation, authorship network analysis, and subject analysis.Source: CEUR WORKSHOP PROCEEDINGS, vol. 3643, pp. 230-245. Brixen, 22-23 February 2024.
See at:
ceur-ws.org | CNR IRIS | CNR IRIS
2024
Book
Open Access
Preface for Joint Proceedings of Posters, Demos, Workshops, and Tutorials of SEMANTiCS 2024
Garijo D., Gentile A. L., Kurteva A., Mannocci A., Osborne F., Vahdati S.
This volume contains the proceedings of the Poster and Demo Track of the 20th International Conference on Semantic Systems, SEMANTiCS 2024, which took place from September 17-19, 2024, in Amsterdam. It also features the proceedings of the First International Workshop on Scaling Knowledge Graphs for Industry, along with an overview of the NeXt-generation Data Governance Workshop 2024 (NXDG 2024), both of which were co-located with SEMANTiCS 2024. SEMANTiCS is the annual meeting place for professionals who make semantic computing work, understand its benefits, and encounter its limitations. Every year, SEMANTiCS attracts information managers, IT architects, software engineers, and researchers from organizations ranging from research facilities and NPOs through public administrations to the largest and/or most innovative companies in the world. Conference participants learn from top researchers and industry experts about emerging trends and topics in the wide area of semantic computing. The SEMANTiCS community is highly diverse; attendees have responsibilities in interlinking areas such as Artificial Intelligence, knowledge discovery and management, bigdata analytics, e-commerce, enterprise search, technical documentation, document management, business intelligence, and enterprise vocabulary management.Source: CEUR WORKSHOP PROCEEDINGS, vol. 3759
Garijo D., Gentile A. L., Kurteva A., Mannocci A., Osborne F., Vahdati S.
This volume contains the proceedings of the Poster and Demo Track of the 20th International Conference on Semantic Systems, SEMANTiCS 2024, which took place from September 17-19, 2024, in Amsterdam. It also features the proceedings of the First International Workshop on Scaling Knowledge Graphs for Industry, along with an overview of the NeXt-generation Data Governance Workshop 2024 (NXDG 2024), both of which were co-located with SEMANTiCS 2024. SEMANTiCS is the annual meeting place for professionals who make semantic computing work, understand its benefits, and encounter its limitations. Every year, SEMANTiCS attracts information managers, IT architects, software engineers, and researchers from organizations ranging from research facilities and NPOs through public administrations to the largest and/or most innovative companies in the world. Conference participants learn from top researchers and industry experts about emerging trends and topics in the wide area of semantic computing. The SEMANTiCS community is highly diverse; attendees have responsibilities in interlinking areas such as Artificial Intelligence, knowledge discovery and management, bigdata analytics, e-commerce, enterprise search, technical documentation, document management, business intelligence, and enterprise vocabulary management.Source: CEUR WORKSHOP PROCEEDINGS, vol. 3759
See at:
ceur-ws.org | CNR IRIS | CNR IRIS
2024
Conference article
Open Access
The ARIADNEplus Knowledge Base: a Linked Open Data set for archaeological research
Bardi A., Baglioni M., Artini M., Mannocci A., Pavone G.
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. The ARIADNEplus Knowledge Base (KB) is an archaeological Linked Open Data set modelled according to the ARIADNE ontology, based on CIDOC-CRM, and provided by an international network of organisations leaders in different domains of archaeological sciences. In February 2024, the ARIADNEplus KB features about 4 million archaeological resources. Thanks to the ARIADNE infrastructure, data providers increased the level of fairness of their resources and contributed to a unique asset for the archaeology research community, the European Open Science Cloud and society at large.Source: CEUR WORKSHOP PROCEEDINGS, vol. 3741, pp. 91-100. Viallasimius, Italy, 23-26/06/2024
Project(s): ARIADNEplus, ATRIUM
Bardi A., Baglioni M., Artini M., Mannocci A., Pavone G.
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. The ARIADNEplus Knowledge Base (KB) is an archaeological Linked Open Data set modelled according to the ARIADNE ontology, based on CIDOC-CRM, and provided by an international network of organisations leaders in different domains of archaeological sciences. In February 2024, the ARIADNEplus KB features about 4 million archaeological resources. Thanks to the ARIADNE infrastructure, data providers increased the level of fairness of their resources and contributed to a unique asset for the archaeology research community, the European Open Science Cloud and society at large.Source: CEUR WORKSHOP PROCEEDINGS, vol. 3741, pp. 91-100. Viallasimius, Italy, 23-26/06/2024
Project(s): ARIADNEplus
, ATRIUM
See at:
ceur-ws.org | CNR IRIS | CNR IRIS
2024
Dataset
Open Access
OpenAIRE Graph Dataset v8.0.0 (July 2024)
Manghi P., Atzori C., Bardi A., Baglioni M., Dimitropoulos H., La Bruzzo S., Foufoulas I., Mannocci A., Horst M., Iatropoulou K., Kokogiannaki A., De Bonis M., Artini M., Lempesis A., Ioannidis A., Manola N., Principe P., Vergoulis T., Chatzopoulos S.
The OpenAIRE Graph is a large and rich collection of open and linked scholarly records from trusted data sources, such as journals, repositories, and registries. It aims to foster Open Science practices and enable the scientific community to discover, monitor, and evaluate science. The Graph is cleaned, deduplicated, enriched, and full-text mined to generate statistics and insights. The Graph is accessible via various services, such as OpenAIRE MONITOR, EXPLORE, ScholeXplorer (Scholix API for the retrieval of literature-data links), search APIs and snapshots in json format updated every six months. The Graph data are openly available with CC-BY license for third-parties to reuse and create added value services. The documentation is available at: https://graph.openaire.euDOI: 10.5281/zenodo.12819872
Project(s): FAIRCORE4EOSC, SciLake , EOSC Beyond , GraspOS , OSTrails
Metrics:
Manghi P., Atzori C., Bardi A., Baglioni M., Dimitropoulos H., La Bruzzo S., Foufoulas I., Mannocci A., Horst M., Iatropoulou K., Kokogiannaki A., De Bonis M., Artini M., Lempesis A., Ioannidis A., Manola N., Principe P., Vergoulis T., Chatzopoulos S.
The OpenAIRE Graph is a large and rich collection of open and linked scholarly records from trusted data sources, such as journals, repositories, and registries. It aims to foster Open Science practices and enable the scientific community to discover, monitor, and evaluate science. The Graph is cleaned, deduplicated, enriched, and full-text mined to generate statistics and insights. The Graph is accessible via various services, such as OpenAIRE MONITOR, EXPLORE, ScholeXplorer (Scholix API for the retrieval of literature-data links), search APIs and snapshots in json format updated every six months. The Graph data are openly available with CC-BY license for third-parties to reuse and create added value services. The documentation is available at: https://graph.openaire.euDOI: 10.5281/zenodo.12819872
Project(s): FAIRCORE4EOSC
, SciLake , EOSC Beyond , GraspOS , OSTrails Metrics:
See at:
CNR IRIS | zenodo.org | CNR IRIS
2024
Book
Open Access
Preface to the proceedings of IRCDL 2024 - 20th conference on Information and Research science Connecting to
Digital and Library Science
Bernasconi E., Mannocci A., Poggi A., Salatino A., Silvello G.
The IRCDL 2024 conference, marking its 20th edition since its inception in 2005, celebrates two decades of advancements in the field of Digital Libraries (DL). Originating at the University of Padua, the conference has traversed various locations, embodying the evolution of DL over time. The 20th-anniversary edition featured a special panel titled “20 Years of IRCDL,” where Prof. Maristella Agosti explored the history of Information Retrieval in the DL landscape. Prof. Floriana Esposito emphasized the pivotal role of Machine Learning in DL and IRCDL. At the same time, Prof. Domenico Saccà provided insights into the significance of databases in Italy and within DL, focusing on structured, semi-structured, and unstructured data. The conference addressed diverse topics, including applications of DL, machine learning in research data, cultural heritage analysis, data citation and provenance, digital preservation, document analysis, knowledge acquisition, user experience, and more. These topics underscored the multidisciplinary nature of IRCDL and its role in shaping the future of DL.Source: CEUR WORKSHOP PROCEEDINGS, vol. 3643
Bernasconi E., Mannocci A., Poggi A., Salatino A., Silvello G.
The IRCDL 2024 conference, marking its 20th edition since its inception in 2005, celebrates two decades of advancements in the field of Digital Libraries (DL). Originating at the University of Padua, the conference has traversed various locations, embodying the evolution of DL over time. The 20th-anniversary edition featured a special panel titled “20 Years of IRCDL,” where Prof. Maristella Agosti explored the history of Information Retrieval in the DL landscape. Prof. Floriana Esposito emphasized the pivotal role of Machine Learning in DL and IRCDL. At the same time, Prof. Domenico Saccà provided insights into the significance of databases in Italy and within DL, focusing on structured, semi-structured, and unstructured data. The conference addressed diverse topics, including applications of DL, machine learning in research data, cultural heritage analysis, data citation and provenance, digital preservation, document analysis, knowledge acquisition, user experience, and more. These topics underscored the multidisciplinary nature of IRCDL and its role in shaping the future of DL.Source: CEUR WORKSHOP PROCEEDINGS, vol. 3643
See at:
ceur-ws.org | CNR IRIS | CNR IRIS
2023
Contribution to book
Open Access
A primer on open science-driven repository platforms
Bardi A, Manghi P, Mannocci A, Ottonello E, Pavone G
Following Open Science mandates, institutions and communities increasingly demand repositories with native support for publishing scientific literature together with research data, software, and other research products. Such repositories may be thematic or general-purpose and are deeply integrated with the scholarly communication ecosystem to ensure versioning, persistent identifiers, data curation, usage stats, and so on. Identifying the most suitable off-the-shelf repository platform is often a non-trivial task as the choice depends on functional requirements, programming and technical skills, and infrastructure resources. This work analyses four state-of-the-art Open Source repository platforms, namely Dryad, Dataverse, DSpace, and InvenioRDM, from both a functional and a software perspective. This work intends to provide an overview serving as a primer for choosing repository platform solutions in different application scenarios. Moreover, this paper highlights how these platforms reacted to some key Open Science demands, moving away from the original and old-fashioned concept of a repository serving as a static container of files and metadata.DOI: 10.1007/978-3-031-39141-5_19
Project(s): OpenAIRE Nexus
Metrics:
Bardi A, Manghi P, Mannocci A, Ottonello E, Pavone G
Following Open Science mandates, institutions and communities increasingly demand repositories with native support for publishing scientific literature together with research data, software, and other research products. Such repositories may be thematic or general-purpose and are deeply integrated with the scholarly communication ecosystem to ensure versioning, persistent identifiers, data curation, usage stats, and so on. Identifying the most suitable off-the-shelf repository platform is often a non-trivial task as the choice depends on functional requirements, programming and technical skills, and infrastructure resources. This work analyses four state-of-the-art Open Source repository platforms, namely Dryad, Dataverse, DSpace, and InvenioRDM, from both a functional and a software perspective. This work intends to provide an overview serving as a primer for choosing repository platform solutions in different application scenarios. Moreover, this paper highlights how these platforms reacted to some key Open Science demands, moving away from the original and old-fashioned concept of a repository serving as a static container of files and metadata.DOI: 10.1007/978-3-031-39141-5_19
Project(s): OpenAIRE Nexus
Metrics:
See at:
CNR IRIS | link.springer.com | ISTI Repository | CNR IRIS | CNR IRIS | CNR IRIS
2023
Conference article
Open Access
(Semi)automated disambiguation of scholarly repositories
Baglioni M, Mannocci A, Pavone G, De Bonis M, Manghi P
The full exploitation of scholarly repositories is pivotal in modern Open Science, and scholarly repository registries are kingpins in enabling researchers and research infrastructures to list and search for suitable repositories. However, since multiple registries exist, repository managers are keen on registering multiple times the repositories they manage to maximise their traction and visibility across different research communities, disciplines, and applications. These multiple registrations ultimately lead to information fragmentation and redundancy on the one hand and, on the other, force registries' users to juggle multiple registries, profiles and identifiers describing the same repository. Such problems are known to registries, which claim equivalence between repository profiles whenever possible by cross-referencing their identifiers across different registries. However, as we will see, this "claim set" is far from complete and, therefore, many replicas slip under the radar, possibly creating problems downstream. In this work, we combine such claims to create duplicate sets and extend them with the results of an automated clustering algorithm run over repository metadata descriptions. Then we manually validate our results to produce an "as accurate as possible" de-duplicated dataset of scholarly repositories.Source: CEUR WORKSHOP PROCEEDINGS, pp. 47-59. Bari, Italy, 23-24/02/2023
Project(s): OpenAIRE Nexus
Baglioni M, Mannocci A, Pavone G, De Bonis M, Manghi P
The full exploitation of scholarly repositories is pivotal in modern Open Science, and scholarly repository registries are kingpins in enabling researchers and research infrastructures to list and search for suitable repositories. However, since multiple registries exist, repository managers are keen on registering multiple times the repositories they manage to maximise their traction and visibility across different research communities, disciplines, and applications. These multiple registrations ultimately lead to information fragmentation and redundancy on the one hand and, on the other, force registries' users to juggle multiple registries, profiles and identifiers describing the same repository. Such problems are known to registries, which claim equivalence between repository profiles whenever possible by cross-referencing their identifiers across different registries. However, as we will see, this "claim set" is far from complete and, therefore, many replicas slip under the radar, possibly creating problems downstream. In this work, we combine such claims to create duplicate sets and extend them with the results of an automated clustering algorithm run over repository metadata descriptions. Then we manually validate our results to produce an "as accurate as possible" de-duplicated dataset of scholarly repositories.Source: CEUR WORKSHOP PROCEEDINGS, pp. 47-59. Bari, Italy, 23-24/02/2023
Project(s): OpenAIRE Nexus
See at:
ceur-ws.org | CNR IRIS | ISTI Repository | CNR IRIS
2023
Journal article
Open Access
A novel curated scholarly graph connecting textual and data publications
Irrera O, Mannocci A, Manghi P, Silvello G
In the last decade, scholarly graphs became fundamental to storing and managing scholarly knowledge in a structured and machine-readable way. Methods and tools for discovery and impact assessment of science rely on such graphs and their quality to serve scientists, policymakers, and publishers. Since research data became very important in scholarly communication, scholarly graphs started including dataset metadata and their relationships to publications. Such graphs are the foundations for Open Science investigations, data-article publishing workflows, discovery, and assessment indicators. However, due to the heterogeneity of practices (FAIRness is indeed in the making), they often lack the complete and reliable metadata necessary to perform accurate data analysis; e.g., dataset metadata is inaccurate, author names are not uniform, and the semantics of the relationships is unknown, ambiguous or incomplete.This work describes an open and curated scholarly graph we built and published as a training and test set for data discovery, data connection, author disambiguation, and link prediction tasks. Overall the graph contains 4,047 publications, 5,488 datasets, 22 software, 21,561 authors; 9,692 edges interconnect publications to datasets and software and are labeled with semantics that outline whether a publication is citing, referencing, documenting, supplementing another product.To ensure high-quality metadata and semantics, we relied on the information extracted from PDFs of the publications and the datasets and software webpages to curate and enrich nodes metadata and edges semantics. To the best of our knowledge, this is the first ever published resource, including publications and datasets with manually validated and curated metadata.Source: ACM JOURNAL OF DATA AND INFORMATION QUALITY, vol. 15 (issue 3)
DOI: 10.1145/3597310
Project(s): OpenAIRE Nexus
Metrics:
Irrera O, Mannocci A, Manghi P, Silvello G
In the last decade, scholarly graphs became fundamental to storing and managing scholarly knowledge in a structured and machine-readable way. Methods and tools for discovery and impact assessment of science rely on such graphs and their quality to serve scientists, policymakers, and publishers. Since research data became very important in scholarly communication, scholarly graphs started including dataset metadata and their relationships to publications. Such graphs are the foundations for Open Science investigations, data-article publishing workflows, discovery, and assessment indicators. However, due to the heterogeneity of practices (FAIRness is indeed in the making), they often lack the complete and reliable metadata necessary to perform accurate data analysis; e.g., dataset metadata is inaccurate, author names are not uniform, and the semantics of the relationships is unknown, ambiguous or incomplete.This work describes an open and curated scholarly graph we built and published as a training and test set for data discovery, data connection, author disambiguation, and link prediction tasks. Overall the graph contains 4,047 publications, 5,488 datasets, 22 software, 21,561 authors; 9,692 edges interconnect publications to datasets and software and are labeled with semantics that outline whether a publication is citing, referencing, documenting, supplementing another product.To ensure high-quality metadata and semantics, we relied on the information extracted from PDFs of the publications and the datasets and software webpages to curate and enrich nodes metadata and edges semantics. To the best of our knowledge, this is the first ever published resource, including publications and datasets with manually validated and curated metadata.Source: ACM JOURNAL OF DATA AND INFORMATION QUALITY, vol. 15 (issue 3)
DOI: 10.1145/3597310
Project(s): OpenAIRE Nexus
Metrics:
See at:
dl.acm.org | CNR IRIS | ISTI Repository | CNR IRIS | CNR IRIS
2023
Other
Open Access
InfraScience research activity report 2023
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 A. S. T., La Bruzzo S., Lelii L., Manghi P., Mangiacrapa F., Mangione D., Mannocci A., Molinaro E., Pagano P., Panichi G., Paratore M. T., Pavone G., Piccioli T., Sinibaldi F., Straccia U., Vannini G. L.
InfraScience is a research group of the National Research Council of Italy - Institute of Information Science and Technologies (CNR - ISTI) based in Pisa, Italy. This report documents the research activity performed by this group in 2023 to highlight the major results. In particular, the InfraScience group engaged in research challenges characterising Data Infrastructures, e-Science, and Intelligent Systems. The group activity is pursued by closely connecting research and development and by promoting and supporting open science. In fact, the group is leading the development of two large scale infrastructures for Open Science, i.e. D4Science and OpenAIRE. During 2023 InfraScience members contributed to the publishing of several papers, to the research and development activities of several research projects (primarily funded by EU), to the organization of conferences and training events, to several working groups and task forces.DOI: 10.32079/isti-ar-2023/002
DOI: https://doi.org/10.32079/isti-ar-2023/002
Project(s): Blue Cloud, EOSC Future , TAILOR
Metrics:
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 A. S. T., La Bruzzo S., Lelii L., Manghi P., Mangiacrapa F., Mangione D., Mannocci A., Molinaro E., Pagano P., Panichi G., Paratore M. T., Pavone G., Piccioli T., Sinibaldi F., Straccia U., Vannini G. L.
InfraScience is a research group of the National Research Council of Italy - Institute of Information Science and Technologies (CNR - ISTI) based in Pisa, Italy. This report documents the research activity performed by this group in 2023 to highlight the major results. In particular, the InfraScience group engaged in research challenges characterising Data Infrastructures, e-Science, and Intelligent Systems. The group activity is pursued by closely connecting research and development and by promoting and supporting open science. In fact, the group is leading the development of two large scale infrastructures for Open Science, i.e. D4Science and OpenAIRE. During 2023 InfraScience members contributed to the publishing of several papers, to the research and development activities of several research projects (primarily funded by EU), to the organization of conferences and training events, to several working groups and task forces.DOI: 10.32079/isti-ar-2023/002
DOI: https://doi.org/10.32079/isti-ar-2023/002
Project(s): Blue Cloud
, EOSC Future , TAILOR Metrics:
2023
Conference article
Open Access
Tracing data footprints: formal and informal data citations in the scientific literature
Irrera O, Mannocci A, Manghi P, Silvello G
Data citation has become a prevalent practice within the scientific community, serving the purpose of facilitating data discovery, reproducibility, and credit attribution. Consequently, data has gained significant importance in the scholarly process. Despite its growing prominence, data citation is still at an early stage, with considerable variations in practices observed across scientific domains. Such diversity hampers the ability to consistently analyze, detect, and quantify data citations.We focus on the European Marine Science (MES) community to examine how data is cited in this specific context. We identify four types of data citations: formal, informal, complete, and incomplete. By analyzing the usage of these diverse data citation modalities, we investigate their impact on the widespread adoption of data citation practices.DOI: 10.1007/978-3-031-43849-3_7
Metrics:
Irrera O, Mannocci A, Manghi P, Silvello G
Data citation has become a prevalent practice within the scientific community, serving the purpose of facilitating data discovery, reproducibility, and credit attribution. Consequently, data has gained significant importance in the scholarly process. Despite its growing prominence, data citation is still at an early stage, with considerable variations in practices observed across scientific domains. Such diversity hampers the ability to consistently analyze, detect, and quantify data citations.We focus on the European Marine Science (MES) community to examine how data is cited in this specific context. We identify four types of data citations: formal, informal, complete, and incomplete. By analyzing the usage of these diverse data citation modalities, we investigate their impact on the widespread adoption of data citation practices.DOI: 10.1007/978-3-031-43849-3_7
Metrics:
See at:
CNR IRIS | link.springer.com | ISTI Repository | doi.org | CNR IRIS | CNR IRIS
2022
Journal article
Open Access
New trends in scientific knowledge graphs and research impact assessment
Manghi P, Mannocci A, Osborne F, Sacharidis D, Salatino A, Vergoulis T
Source: QUANTITATIVE SCIENCE STUDIES, vol. 2 (issue 4), pp. 1296-1300
DOI: 10.1162/qss_e_00160
Metrics:
Manghi P, Mannocci A, Osborne F, Sacharidis D, Salatino A, Vergoulis T
Source: QUANTITATIVE SCIENCE STUDIES, vol. 2 (issue 4), pp. 1296-1300
DOI: 10.1162/qss_e_00160
Metrics:
See at:
direct.mit.edu | Quantitative Science Studies | CNR IRIS | ISTI Repository | CORE (RIOXX-UK Aggregator) | Quantitative Science Studies | CNR IRIS
2022
Conference article
Open Access
Will open science change authorship for good? Towards a quantitative analysis
Mannocci A, Irrera O, Manghi P
Authorship of scientific articles has profoundly changed from early science until now. If once upon a time a paper was authored by a handful of authors, scientific collaborations are much more prominent on average nowadays. As authorship (and citation) is essentially the primary reward mechanism according to the traditional research evaluation frameworks, it turned to be a rather hot-button topic from which a significant portion of academic disputes stems. However, the novel Open Science practices could be an opportunity to disrupt such dynamics and diversify the credit of the different scientific contributors involved in the diverse phases of the lifecycle of the same research effort. In fact, a paper and research data (or software) contextually published could exhibit different authorship to give credit to the various contributors right where it feels most appropriate. We argue that this can be computationally analysed by taking advantage of the wealth of information in model Open Science Graphs. Such a study can pave the way to understand better the dynamics and patterns of authorship in linked literature, research data and software, and how they evolved over the years.Source: CEUR WORKSHOP PROCEEDINGS. Padua, Italy, 24-25/02/2022
Project(s): OpenAIRE Nexus
Mannocci A, Irrera O, Manghi P
Authorship of scientific articles has profoundly changed from early science until now. If once upon a time a paper was authored by a handful of authors, scientific collaborations are much more prominent on average nowadays. As authorship (and citation) is essentially the primary reward mechanism according to the traditional research evaluation frameworks, it turned to be a rather hot-button topic from which a significant portion of academic disputes stems. However, the novel Open Science practices could be an opportunity to disrupt such dynamics and diversify the credit of the different scientific contributors involved in the diverse phases of the lifecycle of the same research effort. In fact, a paper and research data (or software) contextually published could exhibit different authorship to give credit to the various contributors right where it feels most appropriate. We argue that this can be computationally analysed by taking advantage of the wealth of information in model Open Science Graphs. Such a study can pave the way to understand better the dynamics and patterns of authorship in linked literature, research data and software, and how they evolved over the years.Source: CEUR WORKSHOP PROCEEDINGS. Padua, Italy, 24-25/02/2022
Project(s): OpenAIRE Nexus
See at:
ceur-ws.org | CNR IRIS | ISTI Repository | CNR IRIS
2022
Other
Open Access
InfraScience research activity report 2021
Artini M, Assante M, Atzori C, Baglioni M, Bardi A, Bove P, Candela L, Casini G, Castelli D, Cirillo R, Coro G, De Bonis M, Debole F, Dell'Amico A, Frosini L, La Bruzzo S, Lazzeri E, Lelii L, Manghi P, Mangiacrapa F, Mangione D, Mannocci A, Ottonello E, Pagano P, Panichi G, Pavone G, Piccioli T, Sinibaldi F, Straccia U
InfraScience is a research group of the National Research Council of Italy - Institute of Information Science and Technologies (CNR - ISTI) based in Pisa, Italy. This report documents the research activity performed by this group in 2021 to highlight the major results. In particular, the InfraScience group confronted with research challenges characterising Data Infrastructures, eScience, and Intelligent Systems. The group activity is pursued by closely connecting research and development and by promoting and supporting open science. In fact, the group is leading the development of two large scale infrastructures for Open Science, i.e. D4Science and OpenAIRE. During 2021 InfraScience members contributed to the publishing of 25 papers, to the research and development activities of 18 research projects (15 funded by EU), to the organization of conferences and training events, to several working groups and task forces.DOI: 10.32079/isti-ar-2022/001
DOI: https://doi.org/10.32079/isti-ar-2022/001
Project(s): ARIADNEplus, Blue Cloud , PerformFISH , EOSC-Pillar , DESIRA , EOSC Future , EOSCsecretariat.eu , EcoScope , RISIS 2 , OpenAIRE-Advance , OpenAIRE Nexus , SoBigData-PlusPlus
Metrics:
Artini M, Assante M, Atzori C, Baglioni M, Bardi A, Bove P, Candela L, Casini G, Castelli D, Cirillo R, Coro G, De Bonis M, Debole F, Dell'Amico A, Frosini L, La Bruzzo S, Lazzeri E, Lelii L, Manghi P, Mangiacrapa F, Mangione D, Mannocci A, Ottonello E, Pagano P, Panichi G, Pavone G, Piccioli T, Sinibaldi F, Straccia U
InfraScience is a research group of the National Research Council of Italy - Institute of Information Science and Technologies (CNR - ISTI) based in Pisa, Italy. This report documents the research activity performed by this group in 2021 to highlight the major results. In particular, the InfraScience group confronted with research challenges characterising Data Infrastructures, eScience, and Intelligent Systems. The group activity is pursued by closely connecting research and development and by promoting and supporting open science. In fact, the group is leading the development of two large scale infrastructures for Open Science, i.e. D4Science and OpenAIRE. During 2021 InfraScience members contributed to the publishing of 25 papers, to the research and development activities of 18 research projects (15 funded by EU), to the organization of conferences and training events, to several working groups and task forces.DOI: 10.32079/isti-ar-2022/001
DOI: https://doi.org/10.32079/isti-ar-2022/001
Project(s): ARIADNEplus
, Blue Cloud , PerformFISH , EOSC-Pillar , DESIRA , EOSC Future , EOSCsecretariat.eu , EcoScope , RISIS 2 , OpenAIRE-Advance , OpenAIRE Nexus , SoBigData-PlusPlus Metrics:
See at:
CNR IRIS | ISTI Repository | CNR IRIS