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2022 Contribution to journal Open Access OPEN
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 2 (2022): 1296–1300. doi:10.1162/qss_e_00160
DOI: 10.1162/qss_e_00160
Metrics:


See at: direct.mit.edu Open Access | Quantitative Science Studies Open Access | ISTI Repository Open Access | CORE (RIOXX-UK Aggregator) Open Access | Quantitative Science Studies Open Access | CNR ExploRA Open Access


2022 Conference article Open Access OPEN
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: IRCDL 2022 - 18th Italian Research Conference on Digital Libraries, Padua, Italy, 24-25/02/2022
Project(s): OpenAIRE Nexus via OpenAIRE

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


2022 Report Open Access OPEN
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 via OpenAIRE, Blue Cloud via OpenAIRE, PerformFISH via OpenAIRE, EOSC-Pillar via OpenAIRE, DESIRA via OpenAIRE, EOSC Future via OpenAIRE, EOSCsecretariat.eu via OpenAIRE, EcoScope via OpenAIRE, RISIS 2 via OpenAIRE, OpenAIRE-Advance via OpenAIRE, OpenAIRE Nexus via OpenAIRE, SoBigData-PlusPlus via OpenAIRE
Metrics:


See at: ISTI Repository Open Access | CNR ExploRA Open Access


2022 Conference article Open Access OPEN
BIP! scholar: a service to facilitate fair researcher assessment
Vergoulis T., Chatzopoulos S., Vichos K., Kanellos I., Mannocci A., Manola N., Manghi P.
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.Source: JCDL'22 - 22nd ACM/IEEE Joint Conference on Digital Libraries, Cologne, Germany, 20-24/06/2022
DOI: 10.1145/3529372.3533296
DOI: 10.48550/arxiv.2205.03152
Project(s): OpenAIRE Nexus via OpenAIRE
Metrics:


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


2022 Conference article Closed Access
Sci-K 2022 - International Workshop on Scientific Knowledge: Representation, Discovery, and Assessment
Manghi P., Mannocci A., Osborne F., Sacharidis D., Salatino A., Vergoulis T.
In this paper we present the 2nd edition of the Scientific Knowledge: Representation, Discovery, and Assessment (Sci-K 2022) workshop. Sci-K aims to explore innovative solutions and ideas for the generation of approaches, data models, and infrastructures (e.g., knowledge graphs) for supporting, directing, monitoring and assessing the scientific knowledge and progress. This edition is also a reflection point as the community is seeking alternative solutions to the now-defunct Microsoft Academic Graph (MAG).Source: WWW 2022 - The ACM Web Conference 2022, pp. 735–738, Lyon, France (Online), 25-29/04/2022
DOI: 10.1145/3487553.3524883
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See at: dl.acm.org Restricted | CNR ExploRA Restricted


2022 Conference article Open Access OPEN
"Knock Knock! Who's There?" A study on scholarly repositories' availability
Mannocci A., Baglioni M., Manghi P.
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.Source: TPDL 2022 - 26th International Conference on Theory and Practice of Digital Libraries, pp. 306–312, Padua, Italy, 20-23/09/2022
DOI: 10.1007/978-3-031-16802-4_26
Project(s): OpenAIRE Nexus via OpenAIRE
Metrics:


See at: ISTI Repository Open Access | link.springer.com Restricted | CNR ExploRA Restricted


2022 Conference article Open Access OPEN
Open Science and authorship of supplementary material. Evidence from a research community
Mannocci A., Irrera O., Manghi P.
While, in early science, most of the papers were authored by a handful of scientists, modern science is characterised by more extensive collaborations, and the average number of authors per article has increased across many disciplines (Baethge, 2008; Cronin, 2001; Fernandes & Monteiro, 2017; Frandsen & Nicolaisen, 2010; Wren et al., 2007). Indeed, in some fields of science (e.g., High Energy Physics), it is not infrequent to encounter hundreds or thousands of authors co-participating in the same piece of research. Such intricate collaboration patterns make it difficult to establish a correct relationship between contributor and scientific contribution and hence get an accurate and fair reward during research evaluation (Brand, Allen, Altman, Hlava, & Scott, 2015; Vasilevsky et al., 2021; Vergoulis et al., 2022). Thus, as widely known, scientific authorship tends to be a rather hot-button topic in academia, as roughly one-fifth of academic disputes among authors stem from this (Dance, 2012). Open Science, however, has the potential to disrupt such traditional mechanisms by injecting into the "academic market" new kinds of "currency" for credit attribution, merit and impact assessment (Mooney & Newton, 2012; Silvello, 2018). To this end, the new practices of supplementary research data (and software) deposition and citation could be perceived as an opportunity to diversify the attribution portfolio and eventually give credit to the different contributors involved in the diverse phases of the lifecycle within the same research endeavour (Bierer, Crosas, & Pierce, 2017; Brand et al., 2015). While, on the one hand, it is known that authors' ordering tells little or nothing about authors' roles and contributions (Kosmulski, 2012), on the other hand, we argue that variations of any kind in author sets of paired publications and supplementary material can be indicative. Despite being unclear the actual reason behind such a variation, the presence of a fracture between the publication and research data realms might suggest once more that current practices for research assessment and reward should be revised and updated to capture such peculiarities as well. In (Mannocci, Irrera, & Manghi, 2022), we argue that modern Open Science Graphs (OSGs) can be used to analyse whether this is the case or not and understand if the opportunity has been seized already. By offering extensive metadata descriptions of both literature, research data, software, and their semantic relations, OSGs constitute a fertile ground to analyse this phenomenon computationally and thus analyse the emergence of significant patterns. As a preliminary study, in this paper, we conduct a focused analysis on a subset of publications with supplementary material drawn from the European Marine Science3 (MES) research community. The results are promising and suggest our hypothesis is worth exploring further. Indeed, in 702 cases out of 3,075 (22.83%), there are 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.Source: STI 2022 - 26th International Conference on Science, Technology and Innovation Indicators, Granada, Spain, 7-9/09/2022
DOI: 10.5281/zenodo.6975411
Project(s): OpenAIRE Nexus via OpenAIRE
Metrics:


See at: ISTI Repository Open Access | CNR ExploRA Open Access | zenodo.org Open Access


2022 Conference article Open Access OPEN
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.Source: MTSR 2022 - International Conference on Metadata and Semantics Research, Londra, UK, 07-11/11/2022
Project(s): OpenAIRE Nexus via OpenAIRE

See at: ISTI Repository Open Access | CNR ExploRA Open Access | www.mtsr-conf.org Open Access


2021 Conference article Open Access OPEN
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 via OpenAIRE

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


2021 Conference article Open Access OPEN
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 via OpenAIRE, OpenAIRE Nexus via OpenAIRE
Metrics:


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


2021 Dataset Unknown
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 via OpenAIRE, BE OPEN via OpenAIRE, OpenAIRE-Advance via OpenAIRE
Metrics:


See at: CNR ExploRA


2021 Report Open Access OPEN
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 via OpenAIRE, Blue Cloud via OpenAIRE, PerformFISH via OpenAIRE, EOSC-Pillar via OpenAIRE, DESIRA via OpenAIRE, EOSCsecretariat.eu via OpenAIRE, RISIS 2 via OpenAIRE, TAILOR via OpenAIRE, I-GENE via OpenAIRE, MOVING via OpenAIRE, OpenAIRE-Advance via OpenAIRE, SoBigData-PlusPlus via OpenAIRE
Metrics:


See at: ISTI Repository Open Access | CNR ExploRA Open Access


2021 Journal article Open Access OPEN
We can make a better use of ORCID: five observed misapplications
Baglioni M., Manghi P., Mannocci A., Bardi A.
Since 2012, the "Open Researcher and Contributor ID" organisation (ORCID) has been successfully running a worldwide registry, with the aim of "providing a unique, persistent identifier for individuals to use as they engage in research, scholarship, and innovation activities". Any service in the scholarly communication ecosystem (e.g., publishers, repositories, CRIS systems, etc.) can contribute to a non-ambiguous scholarly record by including, during metadata deposition, referrals to iDs in the ORCID registry. The OpenAIRE Research Graph is a scholarly knowledge graph that aggregates both records from the ORCID registry and publication records with ORCID referrals from publishers and repositories worldwide to yield research impact monitoring and Open Science statistics. Graph data analytics revealed "anomalies" due to ORCID registry "misapplications", caused by wrong ORCID referrals and misexploitation of the ORCID registry. Albeit these affect just a minority of ORCID records, they inevitably affect the quality of the ORCID infrastructure and may fuel the rise of detractors and scepticism about the service. In this paper, we classify and qualitatively document such misapplications, identifying five ORCID registrant-related and ORCID referral-related anomalies to raise awareness among ORCID users. We describe the current countermeasures taken by ORCID and, where applicable, provide recommendations. Finally, we elaborate on the importance of a community-steered Open Science infrastructure and the benefits this approach has brought and may bring to ORCID.Source: Data science journal 20 (2021): 1–12. doi:10.5334/dsj- 2021-038
DOI: 10.5334/dsj-2021-038
Project(s): OpenAIRE-Connect via OpenAIRE
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See at: datascience.codata.org Open Access | ISTI Repository Open Access | CNR ExploRA Open Access


2021 Contribution to book Open Access OPEN
Detection, analysis, and prediction of research topics with scientific knowledge graphs
Salatino A., Mannocci A., Osborne F.
Analysing research trends and predicting their impact on academia and industry is crucial to gain a deeper understanding of the advances in a research field and to inform critical decisions about research funding and technology adoption. In the last years, we saw the emergence of several publicly-available and large-scale Scientific Knowledge Graphs fostering the development of many data-driven approaches for performing quantitative analyses of research trends. This chapter presents an innovative framework for detecting, analysing, and forecasting research topics based on a large-scale knowledge graph characterising research articles according to the research topics from the Computer Science Ontology. We discuss the advantages of a solution based on a formal representation of topics and describe how it was applied to produce bibliometric studies and innovative tools for analysing and predicting research dynamics.Source: Predicting the Dynamics of Research Impact, edited by Manolopoulos Y., Vergoulis T., pp. 225–252, 2021
DOI: 10.1007/978-3-030-86668-6_11
Metrics:


See at: arxiv.org Open Access | doi.org Restricted | CNR ExploRA Restricted


2020 Conference article Open Access OPEN
Context-Driven Discoverability of Research Data
Baglioni M., Manghi P., Mannocci A.
Research data sharing has been proved to be key for accelerating scientific progress and fostering interdisciplinary research; hence, the ability to search, discover and reuse data items is nowadays vital in doing science. However, research data discovery is yet an open challenge. In many cases, descriptive metadata exhibit poor quality, and the ability to automatically enrich metadata with semantic information is limited by the data files format, which is typically not textual and hard to mine. More generally, however, researchers would like to find data used across different research experiments or even disciplines. Such needs are not met by traditional metadata description schemata, which are designed to freeze research data features at deposition time. In this paper, we propose a methodology that enables "context-driven discovery" for research data thanks to their proven usage across research activities that might differ from the original one, potentially across diverse disciplines. The methodology exploits the collection of publication-dataset and dataset-dataset links provided by OpenAIRE Scholexplorer data citation index so to propagate articles metadata into related research datasets by leveraging semantic relatedness. Such "context propagation" process enables the construction of "context-enriched" metadata of datasets, which enables "context-driven" discoverability of research data. To this end, we provide a real-case evaluation of this technique applied to Scholexplorer. Due to the broad coverage of Scholexplorer, the evaluation documents the effectiveness of this technique at improving data discovery on a variety of research data repositories and databases.Source: 24th International Conference on Theory and Practice of Digital Libraries, TPDL 2020, pp. 197–211, Lyon, France, August 25-27, 2020
DOI: 10.1007/978-3-030-54956-5_15
Project(s): OpenAIRE-Advance via OpenAIRE
Metrics:


See at: ZENODO Open Access | zenodo.org Open Access | Lecture Notes in Computer Science Restricted | link.springer.com Restricted | CNR ExploRA Restricted


2019 Conference article Open Access OPEN
OpenAIRE's DOIBoost - Boosting Crossref for Research
La Bruzzo S., Manghi P., Mannocci A.
Research in information science and scholarly communication strongly relies on the availability of openly accessible datasets of scholarly entities metadata and, where possible, their relative payloads. Since such metadata information is scattered across diverse, freely accessible, online resources (e.g. Crossref, ORCID), researchers in this domain are doomed to struggle with (meta)data integration problems, in order to produce custom datasets of often undocumented and rather obscure provenance. This practice leads to waste of time, duplication of efforts, and typically infringes open science best practices of transparency and reproducibility of science. In this article, we describe how to generate DOIBoost, a metadata collection that enriches Crossref with inputs from Microsoft Academic Graph, ORCID, and Unpaywall for the purpose of supporting high-quality and robust research experiments, saving times to researchers and enabling their comparison. To this end, we describe the dataset value and its schema, analyse its actual content, and share the software Toolkit and experimental workflow required to reproduce it. The DOIBoost dataset and Software Toolkit are made openly available via Zenodo.org. DOIBoost will become an input source to the OpenAIRE information graph.Source: IRCDL 2019 - Italian Research Conference on Digital Libraries, pp. 133–143, Pisa, Italy, 31/01/2019, 01/2/2019
DOI: 10.1007/978-3-030-11226-4_11
Project(s): OpenAIRE-Advance via OpenAIRE
Metrics:


See at: ISTI Repository Open Access | oro.open.ac.uk Open Access | link.springer.com Restricted | link.springer.com Restricted | CNR ExploRA Restricted


2019 Report Open Access OPEN
The OpenAIRE research graph: third-party publishing APIs
Atzori C., Baglioni M., Bardi A., Manghi P., La Bruzzo S., De Bonis M., Dell'Amico A., Artini M., Mannocci A., Ottonello E.
This work describes the specification of the OpenAIRE publishing APIs that support third-party services at publishing metadata about interlinked and packaged research products into the OpenAIRE Research Graph, in respect of the OpenAIRE interoperability guidelines (https://guidelines.openaire.eu). Research products generated by researchers using services of research infrastructures are today manually published by researchers in a repository external to their research infrastructure. This phase is often considered an extra burden, because researchers have to fill in metadata forms with information that is already available in the scope of the services they used. By using the OpenAIRE publishing APIs, services of research infrastructures can implement an on-demand publishing workflow for any type of research products to support their researchers at improving the FAIRness of their research products and relief them from the tedious step of finding a suitable repository and manually depositing the products in it.Source: ISTI Technical reports, 2019

See at: ISTI Repository Open Access | CNR ExploRA Open Access


2019 Dataset Unknown
OpenAIRE Research Graph Dump
Manghi P., Atzori C., Bardi A., Schirrwagen J., Dimitropoulos H., La Bruzzo S., Foufoulas I., Loehden A., Baecker A., Mannocci A., Horst M., Baglioni M., Czerniak A., Kiatropoulou K., Kokogiannaki A., De Bonis M., Artini M., Ottonello E., Lempesis A., Nielsen L. H., Ioannidis A., Bigarella C., Summan F.
The OpenAIRE Research Graph is one of the largest open scholarly record collections worldwide, key in fostering Open Science and establishing its practices in the 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 in the hands of the scientific community. Imagine a vast collection of research products all linked together, contextualised and openly available. For the past ten years OpenAIRE has been working to gather this valuable record. OpenAIRE is pleased to announce the beta release of its Research Graph, a massive collection of metadata and links between scientific products such as articles, datasets, software, and other research products, entities like organisations, funders, funding streams, projects, communities, and data sources. As of today, the OpenAIRE Research Graph aggregates around 450Mi metadata records with links collecting from 10,000 data sources trusted by scientists, including repositories registered in OpenDOAR, Open Access journals registered in DOAJ, Crossref, Unpaywall, ORCID and Microsoft Academic Graph. After cleaning, deduplication, and fine-grained classification processes, they narrow down to ~100Mi publications, ~8Mi datasets, ~200K software research products, 8Mi other products linked together with semantic relations. More than 10Mi full-texts of Open Access publications are mined by algorithms to enrich metadata records with additional properties and links among research products, funders, projects, communities, and organizations. Thanks to the mining algorithm, the graph is completed with 480Mi semantic relations. The OpenAIRE Research graph is available via our BETA Explore Portal and you can download it from Zenodo.DOI: 10.5281/zenodo.3516918
Project(s): OpenAIRE-Advance via OpenAIRE
Metrics:


See at: CNR ExploRA


2018 Dataset Unknown
DOIBoost Dataset Dump
La Bruzzo S., Manghi P., Mannocci A.
Research in information science and scholarly communication strongly relies on the availability of openly accessible datasets of metadata and, where possible, their relative payloads. To this end, CrossRef plays a pivotal role by providing free access to its entire metadata collection, and allowing other initiatives to link and enrich its information. Therefore, a number of key pieces of information result scattered across diverse datasets and resources freely available online. As a result of this fragmentation, researchers in this domain end up struggling with daily integration problems producing a plethora of ad-hoc datasets, therefore incurring in a waste of time, resources, and infringing open science best practices. DOIBoost is a metadata collection that enriches CrossRef with inputs from Microsoft Academic Graph, ORCID, and Unpaywall for the purpose of supporting high-quality and robust research experiments, saving times to researchers and enabling their comparison.Project(s): OpenAIRE-Advance via OpenAIRE

See at: CNR ExploRA | zenodo.org


2017 Conference article Open Access OPEN
Coping with interoperability in cultural heritage data infrastructures: the Europeana network of Ancient Greek and Latin Epigraphy
Amato G., Mannocci A., Vadicamo L., Zoppi F.
One of the main motivations of the project EAGLE (Europeana network of Ancient Greek and Latin Epigraphy, a Best Practice Network partially funded by the European Commission) is to restore some unity of our past by collecting in a single repository information about the thousands of inscriptions now scattered across all Europe. The collected information is ingested in Europeana and it is made available to the scholarly community and to the general public, for research and cultural dissemination, through a user-friendly portal supporting advanced query and search capabilities. In addition to the traditional search options (full-text search a la Google, fielded search, faceted search and filtering), the EAGLE portal supports two applications intended to make the fruition of the epigraphic material easier and more useful: the EAGLE Flagship Mobile Application and the Story Telling Application. Along the same lines, in order to make the epigraphic material more interesting and usable also by non-epigraphists, EAGLE, in collaboration with the Italian chapter of the Wikimedia Foundation, is leading an effort for the enrichment of the epigraphic images and text with additional information and translations into modern languages. During the whole project life frame, the maintainability and sustainability issues have been constantly considered from both the technical and the scientific point of view. This poster gives some insights of the overall infrastructure.Source: AIUCD 2017- Il telescopio inverso: big data e distant reading nelle discipline umanistiche, pp. 211–215, Rome, Italy, 24-28 January 2017
Project(s): EAGLE

See at: aiucd2017.aiucd.it Open Access | CNR ExploRA Open Access