OpenAIRE's DOIBoost - Boosting CrossRef for Research

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 aim, 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

Realizzazione di un'estensione del digital library management system DORoTy per l'esportazione di compound object mediante protocolli OAI.

DORoTy è un digital library management system che offre il supporto alla gestione di collezioni di compound object in un ambiente fortemente tipato. In questa tesi si intende progettare e sviluppare un’estensione del linguaggio di definizione dei dati di DORoTy che permetta ai progettisti di specializzare le modalità di esportazione dei compound object a partire dai rispettivi tipi e in base agli standard Protocol for Metadata Harvesting e Object Resource Exchange definiti dalla Open Archive Initiative

The OpenAIRE Research Community Dashboard: On blending scientific workflows and scientific publishing

First Online 30 August 2019Despite 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.This work is partly funded by the OpenAIRE-Advance H2020 project (grant number: 777541; call: H2020-EINFRA-2017) and the OpenAIREConnect H2020 project (grant number: 731011; call: H2020-EINFRA-2016-1). Moreover, we would like to thank our colleagues Michele Manunta, Francesco Casu, and Claudio De Luca (Institute for the Electromagnetic Sensing of the Environment, CNR, Italy) for their work on the EPOS infrastructure RCD; and Stephane Pesant (University of Bremen, Germany) his work on the European Marine Science RCD

High-Performance Annotation Tagging over Solr Full-text Indexes

In this work, we focus on the problem of “annotation tagging” over Information Spaces of objects stored in a full-text index. In such a scenario, tags are assigned to objects by “data curator” users with the purpose of classification, while generic end-users will perceive tags as searchable and browsable object properties. To carry out their activities, data curators need “annotation tagging tools” which allow them to “bulk” tag or untag large sets of objects in temporary work sessions, where they can “virtually” and in “real-time” experiment the effect of their actions before making the changes visible to end-users. The implementation of these tools over full-text indexes is a challenge, since bulk object updates in this context are far from being real-time and in critical cases may slow down index performance. We devised TagTick, a tool which offers to data curators a fully functional annotation tagging environment over the full-text index Apache Solr, regarded as a “de-facto standard” in this area. TagTick consists of a TagTick Virtualizer module, which extends the APIs of Solr to support real-time, virtual, bulk-tagging operations, and a TagTick User Interface module, which offers end-user functionalities for annotation tagging. The tool scales optimally with the number and size of bulk tag operations, without compromising index performance

Customized OAI-ORE and OAI-PMH Exports of Compound Objects for the Fedora Repository

Modern Digital Library Systems (DLSs) are based on document models which surpass the traditional payload-metadata document model to incorporate further entities involved in the research life-cycle. Such DLSs manage graphs of interconnected objects, hence offer tools for the creation, visualization and exports of such graphs. In particular, objects in the graph are exported via standard OAI-ORE and OAI-PMH protocols, encoded as (XML) packages of interlinked information objects", also known as compound objects. Fedora is a well-known repository platform, designed to support the realization of DLSs implementing modern document models. To date, Fedora does not provide tools to customize compound object exports from DLS object graphs. This paper presents Fedora-OAIzer, an extension of Fedora which allows DLS developers to customize the structure of compound objects to be exported from a given DLS document model { expressed in terms of Fedora Content Models {and to select the OAI protocol of preference. In order to prove the completeness of the approach, Fedora-OAIzer is compared to other solutions for exporting compound objects from Fedora repositories.Includes: Conference preprint, Powerpoint presentation, Abstract and Biographical notesXAInternationa

OpenAIRE: Advancing open science

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.This research was supported by EU funded project OpenAIRE-Connect (grant agreement: 731011; Call: H2020-EINFRA-2016-1). We thank our colleague Stefania Biagioni for her help during the writing of this paper

OpenAIRE Research Graph: Dumps for research communities and initiatives

Manghi P, Atzori C, Bardi A, et al. OpenAIRE Research Graph: Dumps for research communities and initiatives. Bielefeld University; 2022.This dataset contains dumps of the OpenAIRE Research Graph containing metadata records relevant for the research communities and initiatives collaborating with OpenAIRE and&nbsp;with a public Open Research Gateway on OpenAIRE CONNECT&nbsp;&nbsp;as of May 2022. Each dump is a tar file containing gzip files with one json per line. Each json is compliant to the schema available at&nbsp;https://doi.org/10.5281/zenodo.6372977</p

OpenAIRE Research Graph Dump

Manghi P, Atzori C, Bardi A, et al. OpenAIRE Research Graph Dump. Bielefeld University; 2022.The OpenAIRE Research Graph is exported as several dumps, so you can download the parts you are interested into. publication_[part].tar: metadata records about research literature (includes types of publications listed here) dataset.tar: metadata records about research data (includes the subtypes listed here)&nbsp; software.tar: metadata records about research software (includes the subtypes listed here) otherresearchproduct.tar: metadata records about research products that cannot be classified as research literature, data or software (includes types of products listed here) organization.tar: metadata records about organizations involved in the research life-cycle, such as universities, research organizations, funders., datasource.tar: metadata records about providers whose content is available in the OpenAIRE Research Graph. They includes institutional and thematic repositories, journals, aggregators, funders&#39; databases. project.tar: metadata records about projects funded by a given funder. relation_[part].tar: metadata records about relations between entities in the graph. communities_infrastructures.tar: metadata records about research communities and research infrastructures Each file is a tar archive containing gz files, each with one json per line. Each json is compliant to the schema available at http://doi.org/10.5281/zenodo.5799514. Learn more about the OpenAIRE Research Graph at https://graph.openaire.eu. Discover the content of the graph on OpenAIRE EXPLORE&nbsp;and our API for developers.</p

OpenAIRE Graph Beginner's Kit

Baglioni M, Atzori C, Bardi A, et al. OpenAIRE Graph Beginner's Kit. OpenAIRE Nexus; 2022.The OpenAIRE Graph is an Open Access dataset containing metadata about research products (literature, datasets, software, etc.) linked to other entities of the research ecosystem like organisations, project grants, and data sources.&nbsp; The large size of the OpenAIRE Graph is a major impediment for beginners to familiarise with the underlying data model and explore its contents. Working with the Graph in its full size typically requires access to a huge distributed computing infrastructure which cannot be easily accessible to everyone.&nbsp;&nbsp; The OpenAIRE Beginner&rsquo;s Kit aims to address this issue. It consists of two components: A subset of the OpenAIRE Graph composed of the research products published between 2022-06-29 and 2022-12-29, all the entities connected to them and the respective relationships. The subset is composed of the following parts: publication.tar: metadata records about research literature (includes types of publications listed here) dataset.tar: metadata records about research data (includes the subtypes listed here) software.tar: metadata records about research software (includes the subtypes listed here) otherresearchproduct.tar: metadata records about research products that cannot be classified as research literature, data or software (includes types of products listed here) organization.tar: metadata records about organizations involved in the research life-cycle, such as universities, research organizations, funders. datasource.tar: metadata records about data sources&nbsp;whose content is available in the OpenAIRE Graph. They include&nbsp;institutional and thematic repositories, journals, aggregators, funders&#39; databases. project.tar: metadata records about project grants. relation.tar: metadata records about relations between entities in the graph. communities_infrastructures.tar: metadata records about research communities and research infrastructures Each file is a tar archive containing gz files, each with one json per line. Each json is compliant to the schema available at http://doi.org/10.5281/zenodo.7492151. A Zeppelin notebook that demonstrates how you can use PySpark to analyse the Graph and get answers to some interesting research questions:&nbsp;beginners_kit_zeppelin_notebook.json. Here&nbsp;a guide to Apache Zeppelin. </ul