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
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
See at: CNR ExploRA
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
See at:
ISTI Repository 
| CNR ExploRA | www.emerald.com | Data Technologies and Applications 
| Data Technologies and Applications | Data Technologies and Applications | Data Technologies and Applications
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 | CNR ExploRA
The OpenAIRE Research Community Dashboard: On Blending Scientific Workflows and Scientific Publishing
Baglioni M., Bardi A., Kokogiannaki A., Manghi P., Iatropoulou K., Principe P., Vieira A., Nielsen L. H., Dimitropoulos H., Foufoulas I., Manola N., Atzori C., La Bruzzo S., Lazzeri E., Artini M., De Bonis M., Dell'Amico A.
Despite the hype, the effective implementation of Open Science is hindered by several cultural and technical barriers. Researchers embraced digital science, use "digital laboratories" (e.g. research infrastructures, thematic services) to conduct their research and publish research data, but practices and tools are still far from achieving the expectations of transparency and reproducibility of Open Science. The places where science is performed and the places where science is published are still regarded as different realms. Publishing is still a post-experimental, tedious, manual process, too often limited to articles, in some contexts semantically linked to datasets, rarely to software, generally disregarding digital representations of experiments. In this work we present the OpenAIRE Research Community Dashboard (RCD), designed to overcome some of these barriers for a given research community, minimizing the technical efforts and without renouncing any of the community services or practices. The RCD flanks digital laboratories of research communities with scholarly communication tools for discovering and publishing interlinked scientific products such as literature, datasets, and software. The benefits of the RCD are show-cased by means of two real-case scenarios: the European Marine Science community and the European Plate Observing System (EPOS) research infrastructure.Source: 23rd International Conference on Theory and Practice of Digital Libraries, TPDL, pp. 56–69, Oslo, Norway, September 9-12, 2019
DOI: 10.1007/978-3-030-30760-8_5
DOI: 10.5281/zenodo.3467104
DOI: 10.5281/zenodo.3467103
Project(s): OpenAIRE-Connect , OpenAIRE-Advance
See at:
ISTI Repository | repositorium.sdum.uminho.pt | ZENODO | academic.microsoft.com | dblp.uni-trier.de | link.springer.com | link.springer.com | CNR ExploRA | rd.springer.com
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
See at: CNR ExploRA
OpenAIRE: Advancing open science
Manghi P., Artini M., Atzori C., Baglioni M., Bardi A., La Bruzzo S., De Bonis M., Dimitropoulos H., Foufoulas I., Iatropoulou K., Manola N., Martziou S., Principe P.
OpenAIRE, the point of reference for Open Access in Europe, is now addressing the problem of enabling the Open Science paradigm. To this aim it will provide services to: (i) overcome the limits of today's scientific communication landscape, by allowing research communities and the relative e-infrastructures to fully publish, interlink, package and reuse their research artefacts (e.g. literature, data, and software) and their funding grants within the European and global ecosystem as supported/promoted by OpenAIRE, (ii) enable end-users (e.g. researchers, funder officers) to search and consult a rich and up-to-date knowledge graph of research results and (iii) enable scientific and educational information repositories and publishers to subscribe and be notified of changes in the OpenAIRE knowledge graph. These combined actions will bring long-term and immediate benefits to research communities, research organisations, repository managers, and funders by affecting the way research results are disseminated and reused. On the one hand, publishing the interlinked and packaged research literature, data and software via OpenAIRE drives research communities to an Open Science transition in a consistent and interoperable fashion. On the other hand, the resulting infrastructure concretely enables the construction of Open Science oriented services, supporting practices such as machine-assisted research reproducibility and evaluation.Source: The Grey journal (Print) 15 (2019): 141–146.
Project(s): OpenAIRE-Connect
See at:
ISTI Repository | CNR ExploRA
Deep learning techniques for visual food recognition on a mobile app
De Bonis M., Amato G., Falchi F. ., Gennaro C., Manghi P.
The paper provides an efficient solution to implement a mobile application for food recognition using Convolutional Neural Networks (CNNs). Different CNNs architectures have been trained and tested on two datasets available in literature and the best one in terms of accuracy has been chosen. Since our CNN runs on a mobile phone, efficiency measurements have also taken into account both in terms of memory and computational requirements. The mobile application has been implemented relying on RenderScript and the weights of every layer have been serialized in different files stored in the mobile phone memory. Extensive experiments have been carried out to choose the optimal configuration and tuning parameters.Source: 11th International Conference on Multimedia and Network Information Systems, MISSI 2018, pp. 303–312, Wroclaw; Poland, 12-14 September 2018
DOI: 10.1007/978-3-319-98678-4_31
See at:
link.springer.com | ISTI Repository | CNR ExploRA | academic.microsoft.com | dblp.uni-trier.de | doi.org | link.springer.com | link.springer.com
OpenAIRE: Advancing open science
Manghi P., Artini M., Atzori C., Baglioni M., Bardi A., La Bruzzo S., De Bonis M., Dimitropoulos H., Foufoulas I., Iatropoulou K., Manola N., Martziou S., Principe P.
OpenAIRE, the point of reference for Open Access in Europe, is now addressing the problem of enabling the Open Science paradigm. To this aim it will provide services to: (i) overcome the limits of today's scientific communication landscape, by allowing research communities and the relative e-infrastructures to fully publish, interlink, package and reuse their research artefacts (e.g. literature, data, and software) and their funding grants within the European and global ecosystem as supported/promoted by OpenAIRE, (ii) enable end-users (e.g. researchers, funder officers) to search and consult a rich and up-to-date knowledge graph of research results and (iii) enable scientific and educational information repositories and publishers to subscribe and be notified of changes in the OpenAIRE knowledge graph. These combined actions will bring long-term and immediate benefits to research communities, research organisations, repository managers, and funders by affecting the way research results are disseminated and reused. On the one hand, publishing the interlinked and packaged research literature, data and software via OpenAIRE drives research communities to an Open Science transition in a consistent and interoperable fashion. On the other hand, the resulting infrastructure concretely enables the construction of Open Science oriented services, supporting practices such as machine-assisted research reproducibility and evaluation.Source: GL19 - Nineteenth International Conference on Grey Literature, pp. 107–112, Roma, Italy, 23-24 October 2017
DOI: 10.26069/greynet-2018-000.010-gg
Project(s): OpenAIRE-Connect
See at:
greyguide.isti.cnr.it | ISTI Repository | CNR ExploRA
OpenAIRE: The OpenScience European Infrastructure
Artini M., Atzori C., Baglioni M., Bardi A., Biagioni S., De Bonis M., Dell'Amico A., La Bruzzo S., Manghi P.
OpenAIRE , the point of reference for Open Access in Europe, is now addressing the problem of enabling the Open Science paradigm. To this aim it will provide services to: (i) overcome the limits of today's scientific communication landscape, by allowing research communities and the relative e-infrastructures to fully publish, interlink, package and reuse their research artefacts (e.g. literature, data, and software) and their funding grants within the European and global ecosystem as supported/promoted by OpenAIRE, (ii) enable end-users (e.g. researchers, funder officers) to search and consult a rich and up-to-date knowledge graph of research results and (iii) enable scientific and educational information repositories and publishers to subscribe and be notified of changes in the OpenAIRE knowledge graph. These combined actions will bring long-term and immediate benefits to research communities, research organisations, repository managers, and funders by affecting the way research results are disseminated and reused. On the one hand, publishing the interlinked and packaged research literature, data and software via OpenAIRE drives research communities to an Open Science transition in a consistent and interoperable fashion. On the other hand, the resulting infrastructure concretely enables the construction of Open Science oriented services, supporting practices such as machine-assisted research reproducibility and evaluation.Source: Nineteenth International Conference on Grey Literature - Public Awareness and Access to Grey Literature, pp. 13–13, Roma, CNR, 23-24 October 2017
Project(s): OpenAIRE-Advance
See at:
greyguide.isti.cnr.it | ISTI Repository | CNR ExploRA