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  1. Artikel ; Online: Graph-based methods for Author Name Disambiguation: a survey.

    De Bonis, Michele / Falchi, Fabrizio / Manghi, Paolo

    PeerJ. Computer science

    2023  Band 9, Seite(n) e1536

    Abstract: Scholarly knowledge graphs (SKG) are knowledge graphs representing research-related information, powering discovery and statistics about research impact and trends. Author name disambiguation (AND) is required to produce high-quality SKGs, as a ... ...

    Abstract Scholarly knowledge graphs (SKG) are knowledge graphs representing research-related information, powering discovery and statistics about research impact and trends. Author name disambiguation (AND) is required to produce high-quality SKGs, as a disambiguated set of authors is fundamental to ensure a coherent view of researchers' activity. Various issues, such as homonymy, scarcity of contextual information, and cardinality of the SKG, make simple name string matching insufficient or computationally complex. Many AND deep learning methods have been developed, and interesting surveys exist in the literature, comparing the approaches in terms of techniques, complexity, performance,
    Sprache Englisch
    Erscheinungsdatum 2023-09-11
    Erscheinungsland United States
    Dokumenttyp Journal Article
    ISSN 2376-5992
    ISSN (online) 2376-5992
    DOI 10.7717/peerj-cs.1536
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  2. Artikel ; Online: FDup: a framework for general-purpose and efficient entity deduplication of record collections.

    De Bonis, Michele / Manghi, Paolo / Atzori, Claudio

    PeerJ. Computer science

    2022  Band 8, Seite(n) e1058

    Abstract: 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 ... ...

    Abstract 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.
    Sprache Englisch
    Erscheinungsdatum 2022-09-06
    Erscheinungsland United States
    Dokumenttyp Journal Article
    ISSN 2376-5992
    ISSN (online) 2376-5992
    DOI 10.7717/peerj-cs.1058
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  3. Artikel ; Online: Data management plans as linked open data: exploiting ARGOS FAIR and machine actionable outputs in the OpenAIRE research graph.

    Papadopoulou, Elli / Bardi, Alessia / Kakaletris, George / Tziotzios, Diamadis / Manghi, Paolo / Manola, Natalia

    Journal of biomedical semantics

    2023  Band 14, Heft 1, Seite(n) 17

    Abstract: Background: Open Science Graphs (OSGs) are scientific knowledge graphs representing different entities of the research lifecycle (e.g. projects, people, research outcomes, institutions) and the relationships among them. They present a contextualized ... ...

    Abstract Background: Open Science Graphs (OSGs) are scientific knowledge graphs representing different entities of the research lifecycle (e.g. projects, people, research outcomes, institutions) and the relationships among them. They present a contextualized view of current research that supports discovery, re-use, reproducibility, monitoring, transparency and omni-comprehensive assessment. A Data Management Plan (DMP) contains information concerning both the research processes and the data collected, generated and/or re-used during a project's lifetime. Automated solutions and workflows that connect DMPs with the actual data and other contextual information (e.g., publications, fundings) are missing from the landscape. DMPs being submitted as deliverables also limit their findability. In an open and FAIR-enabling research ecosystem information linking between research processes and research outputs is essential. ARGOS tool for FAIR data management contributes to the OpenAIRE Research Graph (RG) and utilises its underlying services and trusted sources to progressively automate validation and automations of Research Data Management (RDM) practices.
    Results: A comparative analysis was conducted between the data models of ARGOS and OpenAIRE Research Graph against the DMP Common Standard. Following this, we extended ARGOS with export format converters and semantic tagging, and the OpenAIRE RG with a DMP entity and semantics between existing entities and relationships. This enabled the integration of ARGOS machine actionable DMPs (ma-DMPs) to the OpenAIRE OSG, enriching and exposing DMPs as FAIR outputs.
    Conclusions: This paper, to our knowledge, is the first to introduce exposing ma-DMPs in OSGs and making the link between OSGs and DMPs, introducing the latter as entities in the research lifecycle. Further, it provides insight to ARGOS DMP service interoperability practices and integrations to populate the OpenAIRE Research Graph with DMP entities and relationships and strengthen both FAIRness of outputs as well as information exchange in a standard way.
    Mesh-Begriff(e) Humans ; Data Management ; Reproducibility of Results
    Sprache Englisch
    Erscheinungsdatum 2023-11-02
    Erscheinungsland England
    Dokumenttyp Journal Article
    ZDB-ID 2548651-2
    ISSN 2041-1480 ; 2041-1480
    ISSN (online) 2041-1480
    ISSN 2041-1480
    DOI 10.1186/s13326-023-00297-5
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  4. Artikel ; Online: Translating the Microbiome: What's the Target?

    O'Toole, Paul W / Ghosh, Tarini Shankar / Goswami, Sourav / Manghi, Paolo / Segata, Nicola / Shanahan, Fergus

    Gastroenterology

    2023  Band 165, Heft 2, Seite(n) 317–319

    Mesh-Begriff(e) Humans ; Microbiota
    Sprache Englisch
    Erscheinungsdatum 2023-04-23
    Erscheinungsland United States
    Dokumenttyp Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
    ZDB-ID 80112-4
    ISSN 1528-0012 ; 0016-5085
    ISSN (online) 1528-0012
    ISSN 0016-5085
    DOI 10.1053/j.gastro.2023.04.008
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  5. Buch ; Online: Open Science and Authorship of Supplementary Material. Evidence from a Research Community

    Mannocci, Andrea / Irrera, Ornella / Manghi, Paolo

    2022  

    Abstract: Authorship of scientific articles has profoundly changed from early science until now. While 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) ...

    Abstract Authorship of scientific articles has profoundly changed from early science until now. While 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 out 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. As a preliminary study, in this paper, we leverage the wealth of information contained in Open Science Graphs, such as OpenAIRE, and conduct a focused analysis on a subset of publications with supplementary material drawn from the European Marine Science (MES) research community. The results are promising and suggest our hypothesis is worth exploring further as we registered in 22% of the cases substantial variations between the authors participating in the publication and the authors participating in the supplementary dataset (or software), thus posing the premises for a longitudinal, large-scale analysis of the phenomenon.

    Comment: 8 pages, 2 figures; accepted to the 26th International Conference on Science, Technology and Innovation Indicators (STI 2022)
    Schlagwörter Computer Science - Digital Libraries
    Thema/Rubrik (Code) 001
    Erscheinungsdatum 2022-07-06
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    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  6. Buch ; Online: "Knock knock! Who's there?" A study on scholarly repositories' availability

    Mannocci, Andrea / Baglioni, Miriam / Manghi, Paolo

    2022  

    Abstract: Scholarly repositories are the cornerstone of modern open science, and their availability is vital for enacting its practices. To this end, scholarly registries such as FAIRsharing, re3data, OpenDOAR and ROAR give them presence and visibility across ... ...

    Abstract Scholarly repositories are the cornerstone of modern open science, and their availability is vital for enacting its practices. To this end, scholarly registries such as FAIRsharing, re3data, OpenDOAR and ROAR give them presence and visibility across different research communities, disciplines, and applications by assigning an identifier and persisting their profiles with summary metadata. Alas, like any other resource available on the Web, scholarly repositories, be they tailored for literature, software or data, are quite dynamic and can be frequently changed, moved, merged or discontinued. Therefore, their references are prone to link rot over time, and their availability often boils down to whether the homepage URLs indicated in authoritative repository profiles within scholarly registries respond or not. For this study, we harvested the content of four prominent scholarly registries and resolved over 13 thousand unique repository URLs. By performing a quantitative analysis on such an extensive collection of repositories, this paper aims to provide a global snapshot of their availability, which bewilderingly is far from granted.

    Comment: 7 pages, no figures. Accepted at the 26th International Conference on Theory and Practice of Digital Libraries, Padua, Italy
    Schlagwörter Computer Science - Digital Libraries ; Computer Science - Networking and Internet Architecture
    Erscheinungsdatum 2022-07-26
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    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  7. Buch ; Online: Will open science change authorship for good? Towards a quantitative analysis

    Mannocci, Andrea / Irrera, Ornella / Manghi, Paolo

    2022  

    Abstract: 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) ... ...

    Abstract 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.

    Comment: 6 pages, in Proceedings of the 18th Italian Research Conference on Digital Libraries (IRCDL 2022), http://ceur-ws.org/Vol-3160/short15.pdf. arXiv admin note: text overlap with arXiv:2207.02775
    Schlagwörter Computer Science - Digital Libraries
    Thema/Rubrik (Code) 001
    Erscheinungsdatum 2022-07-07
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    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  8. Buch ; Online: (Semi)automated disambiguation of scholarly repositories

    Baglioni, Miriam / Mannocci, Andrea / Pavone, Gina / De Bonis, Michele / Manghi, Paolo

    2023  

    Abstract: 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 ...

    Abstract 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.

    Comment: 13 pages, 3 figures, 1 table
    Schlagwörter Computer Science - Digital Libraries
    Thema/Rubrik (Code) 020
    Erscheinungsdatum 2023-07-05
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    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  9. Buch ; Online: Scholarly outputs of EU Research Funding Programs

    Mugabushaka, Alexis-Michel / Baglioni, Miriam / Bardi, Alessia / Manghi, Paolo

    Understanding differences between datasets of publications reported by grant holders and OpenAIRE Research Graph in H2020

    2021  

    Abstract: Linking research results to grants is an essential prerequisite for an effective monitoring and evaluation of funding programs. For the EU research funding programs, there are multiple datasets linking scholarly publications to the individual grants, ... ...

    Abstract Linking research results to grants is an essential prerequisite for an effective monitoring and evaluation of funding programs. For the EU research funding programs, there are multiple datasets linking scholarly publications to the individual grants, including both open data and those from commercial bibliometric databases. In this paper, we systematically compare openly available data from two data sources: on one hand those reported by the Grant holders (and subsequently published by the European Commission on open data portal) and those from the OpenAIRE Research Graph which collect data from multiple sources. We describe the dataflow leading to their creation and assess the quality of data by validating, on sample basis, the link . We report that, by and large, OpenAIRE Research Graph offers a more complete dataset of scholarly outputs of from EU Research funding programs. We identify also possible improvements and make recommendations on how they can be addressed.
    Schlagwörter Computer Science - Digital Libraries
    Thema/Rubrik (Code) 306
    Erscheinungsdatum 2021-09-22
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    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  10. Buch ; Online: BIP! Scholar

    Vergoulis, Thanasis / Chatzopoulos, Serafeim / Vichos, Kleanthis / Kanellos, Ilias / Mannocci, Andrea / Manola, Natalia / Manghi, Paolo

    A Service to Facilitate Fair Researcher Assessment

    2022  

    Abstract: In recent years, assessing the performance of researchers has become a burden due to the extensive volume of the existing research output. As a result, evaluators often end up relying heavily on a selection of performance indicators like the h-index. ... ...

    Abstract In recent years, assessing the performance of researchers has become a burden due to the extensive volume of the existing research output. As a result, evaluators often end up relying heavily on a selection of performance indicators like the h-index. However, over-reliance on such indicators may result in reinforcing dubious research practices, while overlooking important aspects of a researcher's career, such as their exact role in the production of particular research works or their contribution to other important types of academic or research activities (e.g., production of datasets, peer reviewing). In response, a number of initiatives that attempt to provide guidelines towards fairer research assessment frameworks have been established. In this work, we present BIP! Scholar, a Web-based service that offers researchers the opportunity to set up profiles that summarise their research careers taking into consideration well-established guidelines for fair research assessment, facilitating the work of evaluators who want to be more compliant with the respective practices.
    Schlagwörter Computer Science - Digital Libraries ; Computer Science - Information Retrieval
    Thema/Rubrik (Code) 001
    Erscheinungsdatum 2022-05-06
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    Dokumenttyp Buch ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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