2023 Contribution to conference Open Access

See at: ISTI Repository | CNR ExploRA

2023 Contribution to conference Open Access

See at: ISTI Repository | CNR ExploRA

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.Source: ISTI Annual Reports, 2023
DOI: 10.32079/isti-ar-2023/002
Project(s): Blue Cloud , EOSC Future , TAILOR
Metrics:

See at: CNR ExploRA

2022 Conference article Open Access

A preliminary assessment of the article deduplication algorithm used for the OpenAIRE Research Graph
Vichos K., De Bonis M., Kanellos I., Chatzopoulos S., Atzori C., Manola N., Manghi P., Vergoulis T.
In recent years, a large number of Scholarly Knowledge Graphs (SKGs) have been introduced in the literature. The communities behind these graphs strive to gather, clean, and integrate scholarly metadata from various sources to produce clean and easy-to-process knowledge graphs. In this context, a very important task of the respective cleaning and integration workflows is deduplication. In this paper, we briefly describe and evaluate the accuracy of the deduplication algorithm used for the OpenAIRE Research Graph. Our experiments show that the algorithm has an adequate performance producing a small number of false positives and an even smaller number of false negatives.Source: IRCDL 2022 - 18th Italian Research Conference on Digital Libraries, Padua, Italy, 24-25/02/2022
Project(s): OpenAIRE Nexus

See at: ceur-ws.org | ISTI Repository | CNR ExploRA

2022 Report 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.Source: ISTI Annual report, 2022
DOI: 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: ISTI Repository | CNR ExploRA

2022 Journal article Open Access

FDup: a framework for general-purpose and efficient entity deduplication of record collections
De Bonis M., Manghi P., Atzori C.
Deduplication is a technique aiming at identifying and resolving duplicate metadata records in a collection. This article describes FDup (Flat Collections Deduper), a general-purpose software framework supporting a complete deduplication workflow to manage big data record collections: metadata record data model definition, identification of candidate duplicates, identification of duplicates. FDup brings two main innovations: first, it delivers a full deduplication framework in a single easy-to-use software package based on Apache Spark Hadoop framework, where developers can customize the optimal and parallel workflow steps of blocking, sliding windows, and similarity matching function via an intuitive configuration file; second, it introduces a novel approach to improve performance, beyond the known techniques of "blocking" and "sliding window", by introducing a smart similarity matching function T-match. T-match is engineered as a decision tree that drives the comparisons of the fields of two records as branches of predicates and allows for successful or unsuccessful early-exit strategies. The efficacy of the approach is proved by experiments performed over big data collections of metadata records in the OpenAIRE Research Graph, a known open access knowledge base in Scholarly communication.Source: PeerJ Computer Science 8 (2022). doi:10.7717/PEERJ-CS.1058
DOI: 10.7717/peerj-cs.1058
Project(s): OpenAIRE Nexus
Metrics:

See at: OpenAIRE | ISTI Repository | peerj.com | CNR ExploRA

dnet-dedup framework
Artini M., Atzori C., Bardi A., Baglioni M., De Bonis M., Dell'Amico A., La Bruzzo S. F., Mannocci A., Manghi P.
The GDup Software enables an integrated, scalable, general-purpose system for entity deduplication over big information graphs. GDup supports practitioners with the functionalities needed to realize a fully-fledged entity deduplication workflow over a generic input graph, including Ground Truth support, end-user feedback, and strategies for identifying and merging duplicates to obtain an output disambiguated graph. GDup is today one of the core components of the OpenAIRE infrastructure production system, monitoring Open Science trends on behalf of the European Commission.Project(s): OpenAIRE-Advance , OpenAIRE Nexus

See at: github.com | CNR ExploRA

2022 Report Open Access

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2022 Report Open Access

OpenAIRE Research Graph: aggregation workflow
La Bruzzo S. F., Artini M., Atzori C., Bardi A., Baglioni M., De Bonis M., Dell'Amico A., Mannocci A., Manghi P., Pavone G.
The OpenAIRE Graph (formerly the OpenAIRE Research Graph) is one of the largest open scholarly record collections worldwide. It is key in fostering Open Science and establishing its practices in daily research activities. Conceived as a public and transparent good, populated out of data sources trusted by scientists, the Graph aims at bringing discovery, monitoring, and assessment of science back into the hands of the scientific community. OpenAIRE collects metadata records from more than 70K scholarly communication sources worldwide, including Open Access institutional repositories, data archives, and journals. All the metadata records (i.e., descriptions of research products) are put together in a data lake with records from Crossref, Unpaywall, ORCID, ROR, and information about projects provided by national and international funders. This technical Report describes the main Aggregation Workflow to orchestrate the data aggregation and the implemented mapping from some of the main datasources into the OpenAIRE research graph data model.Source: ISTI Technical Report, ISTI-2022-TR/033, 2022
DOI: 10.32079/isti-tr-2022/033
Project(s): OpenAIRE-Advance , OpenAIRE Nexus
Metrics:

See at: ISTI Repository | CNR ExploRA

2022 Report Open Access

OpenAIRE Research Graph deduplication workflow
La Bruzzo S. F., Artini M., Atzori C., Bardi A., Baglioni M., De Bonis M., Mannocci A., Manghi P., Pavone G.
The OpenAIRE aggregation workflow can collect metadata records from different providers about the same scholarly work. Each metadata record can carry different information because, for example, some providers are not aware of links to projects, keywords, or other details. Another typical case is when OpenAIRE collects one metadata record from a repository about a pre-print and another from a journal about the published article. To provide correct statistics, OpenAIRE must identify those cases and "merge" the two metadata records so that the scholarly work is counted only once in the statistics OpenAIRE produces. This technical Report describes the Deduplication workflow and technique adopted to deduplicate the OpenAIRE Graph.Source: ISTI Technical Report, ISTI-2022-TR/032, 2022
DOI: 10.32079/isti-tr-2022/032
Project(s): OpenAIRE-Connect , OpenAIRE Nexus
Metrics:

See at: ISTI Repository | CNR ExploRA

2022 Report Open Access

InfraScience research activity report 2022
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., Lelii L., Manghi P., Mangiacrapa F., Mangione D., Mannocci A., Ottonello E., Pagano P., Panichi G., Pavone G., Piccioli T., Sinibaldi F., Straccia U., Zoppi F.
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 2022 to highlight the major results. In particular, the InfraScience group confronted with 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 2022 InfraScience members contributed to the publishing of several 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.Source: ISTI Annual reports, 2022
DOI: 10.32079/isti-ar-2022/004
Project(s): ARIADNEplus , Blue Cloud , EOSC-Pillar , DESIRA , EOSC Future , RISIS 2 , TAILOR , SoBigData-PlusPlus
Metrics:

See at: ISTI Repository | CNR ExploRA

2022 Other Open Access

RISIS tool demonstration event - The OpenAIRE Research Graph: an Open Access resource for research on research
Bardi A., Baglioni M., Atzori C.
RISIS embraces the International Open Access Week 2022 with a session on the OpenAIRE Research Graph: an Open Access dataset with metadata about research products (literature, datasets, software, etc.) linked to other entities of the research ecosystem like organisations, project grants, data sources, and services. The session included a presentation of the graph and a guided practical session where participants can learn how to use the OpenAIRE Research Graph for research and policy-related activities. More information about the event is available on the RISIS2 project web site. The practical part has been conducted on the RISIS Lab Virtual Research Environment of the D4Science infrastructure operated by CNR - ISTI. The Jupyter notebooks can be run on the JupyterHub integrated in the RISIS Lab or in other JupyterHub instances supporting PySpark. The data analysis was performed on a subset of the OpenAIRE Research Graph composed of 848 H2020 projects related to the Sustainable Development Goal Climate Action (SDG13), their funded research products, and their related organizations (risis_dataset.zip). Details on the subset, the model, and other useful documentation is available in the slides.Project(s): RISIS 2 , OpenAIRE Nexus

See at: ISTI Repository | ISTI Repository | CNR ExploRA

2021 Conference article Open Access

Reflections on the misuses of ORCID iDs
Baglioni M., Mannocci A., Manghi P., Atzori C., Bardi A., La Bruzzo S.
Since 2012, the "Open Researcher and Contributor Identification Initiative" (ORCID) has been successfully running a worldwide registry, with the aim of unequivocally pinpoint researchers and the body of knowledge they contributed to. In practice, ORCID clients, e.g., publishers, repositories, and CRIS systems, make sure their metadata can refer to iDs in the ORCID registry to associate authors and their work unambiguously. However, the ORCID infrastructure still suffers from several "service misuses", which put at risk its very mission and should be therefore identified and tackled. In this paper, we classify and qualitatively document such misuses, occurring from both users (researchers and organisations) of the ORCID registry and the ORCID clients. We conclude providing an outlook and a few recommendations aiming at improving the exploitation of the ORCID infrastructure.Source: IRCDL 2021 - 17th Italian Research Conference on Digital Libraries, pp. 117–125, Online conference, 18-19/02/2021
Project(s): OpenAIRE-Advance

See at: ceur-ws.org | ISTI Repository | CNR ExploRA

2021 Conference article Open Access

BIP! DB: a dataset of impact measures for scientific publications
Vergoulis T., Kanellos I., Atzori C., Mannocci A., Chatzopoulos S., La Bruzzo S., Manola N., Manghi P.
The growth rate of the number of scientific publications is constantly increasing, creating important challenges in the identification of valuable research and in various scholarly data management applications, in general. In this context, measures which can effectively quantify the scientific impact could be invaluable. In this work, we present BIP! DB, an open dataset that contains a variety of impact measures calculated for a large collection of more than 100 million scientific publications from various disciplines.Source: WWW 2021 - Companion of the World Wide Web Conference, pp. 456–460, Online conference, 13/04/2021
DOI: 10.1145/3442442.3451369
DOI: 10.48550/arxiv.2101.12001
Project(s): OpenAIRE-Advance , OpenAIRE Nexus
Metrics:

See at: arXiv.org e-Print Archive | arxiv.org | ISTI Repository | dl.acm.org | doi.org | doi.org | CNR ExploRA

OpenAIRE research graph: dumps for research communities and initiatives
Manghi P., Atzori C., Bardi A., Baglioni M., Schirrwagen J., Dimitropoulos H., La Bruzzo S., Foufoulas I., Lohden A., Backer A., Mannocci A., Horst M., Czerniak A., Kiatropoulou K., Kokogiannaki A., De Bonis M., Artini M., Ottonello E., Lempesis A., Ioannidis A., Summan F.
This dataset contains dumps of the OpenAIRE Research Graph containing metadata records relevant for the research communities and initiatives collaborating with OpenAIRE. Each dataset is a tar file containing gzip files with one json per line. Each json is compliant to the schema available at DOI: 10.5281/zenodo.3974226DOI: 10.5281/zenodo.3974604
Project(s): RISIS 2 , BE OPEN , OpenAIRE-Advance
Metrics:

See at: CNR ExploRA

OpenAIRE Covid-19 publications, datasets, software and projects metadata
Bardi A., Kuchma I., Pavone G., Artini M., Atzori C., Backer A., Baglioni M., Czerniak A., De Bonis M., Dimitropoulos H., Foufoulas I., Horst M., Iatropoulou K., Jacewicz P., Kokogiannaki A., La Bruzzo S., Lazzeri E., Lohden A., Manghi P., Mannocci A., Manola N., Ottonello E., Schirrwagen J.
This dump provides access to the metadata records of publications, research data, software and projects that may be relevant to the Corona Virus Disease (COVID-19) fight. The dump contains records of the OpenAIRE COVID-19 Gateway (https://covid-19.openaire.eu/), identified via full-text mining and inference techniques applied to the OpenAIRE Research Graph (https://explore.openaire.eu/). The Graph is one of the largest Open Access collections of metadata records and links between publications, datasets, software, projects, funders, and organizations, aggregating 12,000+ scientific data sources world-wide, among which the Covid-19 data sources Zenodo COVID-19 Community, WHO (World Health Organization), BIP! FInder for COVID-19, Protein Data Bank, Dimensions, scienceOpen, and RSNA. The dump consists of a gzip file containing one json per line. Each json is compliant to the schema available at https://doi.org/10.5281/zenodo.3974226DOI: 10.5281/zenodo.3980490
Project(s): OpenAIRE-Advance
Metrics:

See at: CNR ExploRA

2021 Report Open Access

InfraScience Research Activity Report 2020
Artini M., Assante M., Atzori C., Baglioni M., Bardi A., Candela L., Casini G., Castelli D., Cirillo R., Coro G., Debole F., Dell'Amico A., Frosini L., La Bruzzo S., Lazzeri E., Lelii L., Manghi P., Mangiacrapa F., Mannocci A., Pagano P., Panichi 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 2020 to highlight the major results. In particular, the InfraScience group confronted with research challenges characterising Data Infrastructures, e\-Sci\-ence, 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, \ie D4Science and OpenAIRE. During 2020 InfraScience members contributed to the publishing of 30 papers, to the research and development activities of 12 research projects (11 funded by EU), to the organization of conferences and training events, to several working groups and task forces.Source: ISTI Annual Report, ISTI-2021-AR/002, pp.1–20, 2021
DOI: 10.32079/isti-ar-2021/002
Project(s): ARIADNEplus , Blue Cloud , PerformFISH , EOSC-Pillar , DESIRA , EOSCsecretariat.eu , RISIS 2 , TAILOR , I-GENE , MOVING , OpenAIRE-Advance , SoBigData-PlusPlus
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See at: ISTI Repository | CNR ExploRA

2021 Contribution to conference Open Access

OpenOrgs: bridging registries of research organizations. Supporting disambiguation and improving the quality of data
Pavone G., Atzori C.
This presentation was given for OpenAIRE Tech Clinic webinar on 21 June 2021, focusing on the OpenOrgs tool. Unambiguously identifying organizations involved in the research work may not be a trivial task. Their names can be derived from various data sources, each of which often contains a different version of the organization's name (full legal name, short or alternative names, acronym, and so on) and different metadata fields. In OpenOrgs, data curators can enrich the metadata description of organizations and resolve the ambiguity of duplicates detected with an automated process by stating whether two or more entities correspond or not to the same organization. With these tasks, OpenOrgs users can compensate for the lack of information available and improve the organizations' discoverability.Source: OpenAIRE Tech Clinic webinar, Online event, 21 June 2021
DOI: 10.5281/zenodo.5101096
Project(s): OpenAIRE Nexus
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See at: ISTI Repository | zenodo.org | CNR ExploRA

2020 Journal article Open Access

Entity deduplication in big data graphs for scholarly communication
Manghi P., Atzori C., De Bonis M., Bardi A.
Purpose: Several online services offer functionalities to access information from "big research graphs" (e.g. Google Scholar, OpenAIRE, Microsoft Academic Graph), which correlate scholarly/scientific communication entities such as publications, authors, datasets, organizations, projects, funders, etc. Depending on the target users, access can vary from search and browse content to the consumption of statistics for monitoring and provision of feedback. Such graphs are populated over time as aggregations of multiple sources and therefore suffer from major entity-duplication problems. Although deduplication of graphs is a known and actual problem, existing solutions are dedicated to specific scenarios, operate on flat collections, local topology-drive challenges and cannot therefore be re-used in other contexts. Design/methodology/approach: This work presents GDup, an integrated, scalable, general-purpose system that can be customized to address deduplication over arbitrary large information graphs. The paper presents its high-level architecture, its implementation as a service used within the OpenAIRE infrastructure system and reports numbers of real-case experiments. Findings: GDup provides the functionalities required to deliver a fully-fledged entity deduplication workflow over a generic input graph. The system offers out-of-the-box Ground Truth management, acquisition of feedback from data curators and algorithms for identifying and merging duplicates, to obtain an output disambiguated graph. Originality/value: To our knowledge GDup is the only system in the literature that offers an integrated and general-purpose solution for the deduplication graphs, while targeting big data scalability issues. GDup is today one of the key modules of the OpenAIRE infrastructure production system, which monitors Open Science trends on behalf of the European Commission, National funders and institutions.Source: Data technologies and applications 54 (2020): 409–435. doi:10.1108/DTA-09-2019-0163
DOI: 10.1108/dta-09-2019-0163
Project(s): OpenAIRE2020 , OpenAIRE-Advance
Metrics:

See at: Data Technologies and Applications | ISTI Repository | www.emerald.com | Data Technologies and Applications | CNR ExploRA

2019 Report Open Access

See at: ISTI Repository | CNR ExploRA