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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

See at: CNR ExploRA


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

See at: ZENODO Open Access | zenodo.org Open Access | academic.microsoft.com Restricted | link.springer.com Restricted | link.springer.com 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

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

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


2017 Contribution to book Open Access OPEN

The OpenAIRE workflows for data management
Atzori C., Bardi A., Manghi P., Mannocci A.
The OpenAIRE initiative is the point of reference for Open Access in Europe and aims at the creation of an e-Infrastructure for the free flow, access, sharing, and re-use of research outcomes, services and processes for the advancement of research and the dissemination of scientific knowledge. OpenAIRE makes openly accessible a rich Information Space Graph (ISG) where products of the research life-cycle (e.g. publications, datasets, projects) are semantically linked to each other. Such an information space graph is constructed by a set of autonomic (orchestrated) workflows operating in a regimen of continuous data integration. This paper discusses the principal workflows operated by the OpenAIRE technical infrastructure in its different functional areas and provides the reader with the extent of the several challenges faced and the solutions realized.Source: Digital Libraries and Archives, edited by Costantino Grana, Lorenzo Baraldi, pp. 95–107, 2017
DOI: 10.1007/978-3-319-68130-6_8
DOI: 10.5281/zenodo.996006
DOI: 10.5281/zenodo.996005
Project(s): OpenAIRE2020 via OpenAIRE

See at: ZENODO Open Access | zenodo.org Open Access | academic.microsoft.com Restricted | core.ac.uk Restricted | dblp.uni-trier.de Restricted | link.springer.com Restricted | link.springer.com Restricted | CNR ExploRA Restricted | rd.springer.com Restricted


2017 Doctoral thesis Open Access OPEN

Data Flow Quality Monitoring in Data Infrastructures
Mannocci A.
In the last decade, a lot of attention worldwide has been brought by researchers, organizations, and funders on the realization ofData Infrastructures (DIs), namely systems supporting researchers with the broad spectrum of resources they need to perform science. DIs are here intended as ICT (eco)systems offering data and processing components which can be combined into data flows so as to enable arbitrarily complex data manipulation actions serving the consumption needs of DI customers, be them humans or machines.Data resulting from the execution of data flows, represent an important asset both for the DI users, typically craving for the information they need, and for the organization (or community) operating the DI, whose existence and cost sustainability depends on the adoption and usefulness of the DI. On the other hand, when operating several data processing data flows over time, several issues, well-known to practitioners, may arise and compromise the behaviour of the DI, and therefore undermine its reliability and generate stakeholders dissatisfaction. Such issues span a plethora of causes, such as(i) the lack of any kind of guarantees (e.g. quality, stability, findability, etc.) from integrated external data sources, typically not under the jurisdiction of the DI; (ii) the occurrence at any abstraction level of subtle, unexpected errors in the data flows; and(iii) the nature in ever changing evolution of the DI, in terms of data flow composition and algorithms/configurations in use.The autonomy of DI components, their use across several data flows, the evolution of end-user requirements over time, make the one of DI data flows a critical environment, subject to the most subtle inconsistencies. Accordingly, DI users demand guarantees, while quality managers are called to provide them, on the "correctness" of the DI data flows behaviour over time, to be somehow quantified in terms of "data quality" and in terms of "processing quality". Monitoring the quality of data flows is therefore a key activity of paramount importance to ensure the up-taking and long term existence of a DI. Indeed, monitoring can detect or anticipate misbehaviours of DI's data flows, in order to prevent and adjust the errors, or at least "formally" justify to the stakeholders the underlying reasons, possibly not due to the DI, of such errors. Not only, monitoring can also be vital for DIs operation, as having hardware and software resources actively employed in processing low quality data can yield inefficient resource allocation and waste of time.However, data flow quality monitoring is further hindered by the "hybrid" nature of such infrastructures, which typically consist of a patchwork of individual components("system of systems") possibly developed by distinct stakeholders with possibly distinct life-cycles, evolving over time, whose interactions are regulated mainly by shared policies agreed at infrastructural level. Due to such heterogeneity, generally DIs are not equipped with built-in monitoring systems in this sense and to date DI quality managers are therefore bound to use combinations of existing tools - with non trivial integration efforts - or to develop and integrate ex-post their own ad-hoc solutions, at high cost of realization and maintenance.In this thesis, we introduce MoniQ, a general-purpose Data Flow Quality Monitoring system enabling the monitoring of critical data flow components, which are routinely checked during and after every run of the data flow against a set of user-defined quality control rules to make sure the data flow meets the expected behaviour and quality criteria over time, as established upfront by the quality manager. MoniQ introduces a monitoring description language capable of (i) describing the semantic and the time ordering of the observational intents and capture the essence of the DI data flows to be monitored; and (ii) describing monitoring intents over the monitoring flows in terms of metrics to be extracted and controls to be ensured. The novelty of the language is that it incorporates the essence of existing data quality monitoring approaches, identifies and captures process monitoring scenarios, and, above all, provides abstractions to represent monitoring scenarios that combine data and process quality monitoring within the scope of a data flow. The study is provided with an extensive analysis of two real-world use cases used as support and validation of the proposed approach, and discusses an implementation of MoniQ providing quality managers with high-level tools to integrate the solution in a DI in an easy, technology transparent and cost efficient way in order to start to get insight out data flows by visualizing the trends of the metrics defined and the outcome of the controls declared against them.Project(s): OPENAIRE via OpenAIRE

See at: etd.adm.unipi.it Open Access | ISTI Repository Open Access | CNR ExploRA Open Access


2016 Journal article Open Access OPEN

EAGLE - L'infrastruttura di aggregazione dei dati e i servizi a supporto del portale e delle applicazioni
Mannocci A., Casarosa V., Manghi P., Zoppi F.
La lunga tradizione epigrafica, risalente al secolo XVI, epoca ben lontana dai concetti di globalizzazione, standardizzazione e interoperabilità, ha fatto sì che nel tempo si sedimentassero, nelle varie comunità di studiosi, modus operandi spesso contrastanti. All'inizio degli anni '30 il Sistema di Leida (B. a. Van GroninGen, "Projet d'unification des systèmes de signes critiques", in Chronique d'Égypte 7, 1932, pp. 262-269) ha contribuito a ridurre notevolmente la frammentazione presente nei testi, ma una nuova deriva si è verificata dagli anni 90 in poi quando, con l'arrivo di Internet e del Web, gli archivi epigrafici hanno iniziato la loro conversione al digitale. Nonostante la definizione di uno standard per l'annotazione di documenti a carattere epigrafico (EpiDoc: http://sourceforge.net/p/epidoc/wiki/Home/) le comunità hanno per lo più operato in modo indipendente e senza nessuna linea guida condivisa, lasciando di fatto il panorama altamente frammentario. Il progetto EAGLE mira proprio a riconciliare e riunificare sotto un'unica egida le varie comunità epigrafiche e rendere i loro contenuti ricercabili da un unico punto di accesso, e a questo scopo ha sviluppato un'infrastruttura che consente l'aggregazione di tali contenuti e la loro armonizzazione secondo un modello di dati condiviso, e permette infine di interrogare i dati sia attraverso il proprio portale che attraverso Europeana.Source: Forma urbis XXI (2016): 18–21.
Project(s): EAGLE

See at: CNR ExploRA Open Access | www.formavrbis.com Open Access


2016 Conference article Restricted

DataQ: a data flow quality monitoring system for aggregative data infrastructures
Mannocci A., Manghi P.
Aggregative Data Infrastructures (ADIs) are information systems offering services to integrate content collected from data sources so as to form uniform and richer information spaces and support communities of users with enhanced access services to such content. The resulting information spaces are an important asset for the target communities, whose services demand for guarantees on their "correctness" and "quality" over time, in terms of the expected content (structure and semantics) and of the processes generating such content. Application-level continuous monitoring of ADIs becomes therefore crucial to ensure validation of quality. However, ADIs are in most of the cases the result of patchworks of software components and services, in some cases developed independently, built over time to address evolving requirements. As such they are not generally equipped with embedded monitoring components and ADI admins must rely on third-party monitoring systems. In this paper we describe DataQ, a general-purpose system for exible and cost-effective data fow quality monitoring in ADIs. DataQ supports ADI admins with a framework where they can (i) represent ADIs data fows and the relative monitoring specification, and (ii) be instructed on how to meet such specification on the ADI side to implement their monitoring functionality.Source: TPDL 2016 - Theory and Practice of Digital Libraries. 20th International Conference, pp. 357–369, Hannover, Germany, September 5-9, 2016
DOI: 10.1007/978-3-319-43997-6_28
Project(s): OpenAIRE2020 via OpenAIRE

See at: academic.microsoft.com Restricted | dblp.uni-trier.de Restricted | link.springer.com Restricted | link.springer.com Restricted | CNR ExploRA Restricted | rd.springer.com Restricted


2015 Report Open Access OPEN

EAGLE - Second Release of AIM Infrastructure (version 1.0)
Zoppi F., Amato G., Bolettieri P., Falchi F., Manghi P., Mannocci A., Casarosa V.
This document describes the final implementation (Release 2) of the EAGLE Aggregation and Image Retrieval system (AIM) Infrastructure in terms of: . Current implementation against the specification given in "D4.1 AIM Infrastructure Specification" (Section 1). . Details about the Metadata Aggregation System (Section 2). . Details about the Image Retrieval System (Section 3). . HW & SW requirements of the AIM (Appendix A). . Sample of the Content Checker Curation Tool (Appendix B). . Image Recognition and Similarity Search API (Appendix C). This document being just a Release Note produced as accompanying document of the AIM infrastructure software (D4.2.2, deliverable of type "Product"), please refer to the released document "D4.1 AIM Infrastructure Specification" for details about the full featured AIM Infrastructure.Source: Project report, EAGLE, Deliverable D4.2.2, pp.1–29, 2015
Project(s): EAGLE

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


2015 Journal article Open Access OPEN

The OpenAIRE literature broker service for institutional repositories
Artini M., Atzori C., Bardi A., La Bruzzo S., Manghi P., Mannocci A.
OpenAIRE is the European infrastructure for Open Access scholarly communication. It populates and provides access to a graph of objects relative to publications, datasets, people, organizations, projects, and funders aggregated from a variety of data sources, such as institutional repositories, data archives, journals, and CRIS systems. Thanks to infrastructure services, objects in the graph are harmonized to achieve semantic homogeneity, de-duplicated to avoid ambiguities, and enriched with missing properties and/or relationships. OpenAIRE data sources interested in enhancing or incrementing their content may benefit in a number of ways from this graph. This paper presents the high-level architecture behind the realization of an institutional repository Literature Broker Service for OpenAIRE. The Service implements a subscription and notification paradigm supporting institutional repositories willing to: (i) learn about publication objects in OpenAIRE that do not appear in their collection but may be pertinent to it, and (ii) learn about extra properties or relationships relative to publication objects in their collection.Source: D-Lib magazine 21 (2015): 2–10. doi:10.1045/november2015-artini
DOI: 10.1045/november2015-artini
Project(s): OpenAIRE2020 via OpenAIRE

See at: D-Lib Magazine Open Access | CNR ExploRA Open Access | D-Lib Magazine Open Access


2015 Software Unknown

dnet-basic-aggregator: release 1.0
Artini M., Atzori C., Bardi A., Castelli D., Dell'Amico A., La Bruzzo S., Manghi P., Mannocci
This is a minimal instance of the D-Net software toolkit, a software framework for the realization of aggregative data infrastructures.DOI: 10.5281/zenodo.31693
Project(s): OPENAIREPLUS via OpenAIRE

See at: CNR ExploRA


2015 Contribution to book Open Access OPEN

The EAGLE Europeana network of Ancient Greek and Latin Epigraphy: a technical perspective
Mannocci A., Casarosa V., Manghi P., Zoppi F.
The project EAGLE (Europeana network of Ancient Greek and Latin Epigraphy, a Best Practice Network partially funded by the European Commission) aims at aggregating epigraphic material provided by some 15 different epigraphic archives (about 80% of the classified epigraphic material from the Mediterranean area) for ingestion to Europeana. The collected material will be made available also to the scholarly community and to the general public, for research and cultural dissemination. This paper briefly presents the main services provided by EAGLE and the challenges encountered for the aggregation of material coming from heterogeneous archives (different data models and metadata schemas, and exchange formats). EAGLE has defined a common data model for epigraphic information, into which data models from different archives can be optimally mapped. The data infrastructure is based on the D-NET software toolkit, capable of dealing with data collection, mapping, cleaning, indexing, and access provisioning through web portals or standard access protocols.Source: Digital Libraries on the Move 11th Italian Research Conference on Digital Libraries, IRCDL 2015, Bolzano, Italy, January 29-30, 2015, Revised Selected Papers, edited by Diego Calvanese, Dario De Nart, Carlo Tasso, pp. 75–78, 2015
DOI: 10.1007/978-3-319-41938-1_8
Project(s): EAGLE

See at: link.springer.com Open Access | CNR ExploRA Open Access | academic.microsoft.com Restricted | dblp.uni-trier.de Restricted | ircdl2015.unibz.it Restricted | link.springer.com Restricted | link.springer.com Restricted | rd.springer.com Restricted


2015 Conference article Open Access OPEN

The EAGLE data aggregator: data quality monitoring
Mannocci A., Casarosa V., Manghi P., Zoppi F.
The EAGLE project aggregates epigraphy related content from about 20 different data providers, and makes its content available to both Europeana and to scholars. Data Quality monitoring is a key issue in Aggregative Data Infrastructures, where content is collected from a number of different sources with different data models and quality standards. This paper presents a Monitoring Framework for enabling the observation and monitoring of an aggregative infrastructure focusing on the description of the Data Flow and Dynamics Service, and exemplifying these concepts with a use case tailored to the characteristics of the EAGLE aggregation data flow. An Infrastructure Quality Manager (IQM) is provided with a Web user interface (WebUI), allowing her to describe the data flows taking place in the infrastructure and to define monitoring scenarios. The scenarios will include the definition of sensors (pieces of software plugged into the data flow), which will provide observations of measured objects. The scenarios include also the definition of controls and analysers, which will store and process the observations received from the sensors and will verify if the values of the measured features comply with some expected behaviour over time. A monitoring scenario for EAGLE has been defined and tested on simulated data (the monitoring framework is still under development) in order to monitor the "health" of different data collections involved in the EAGLE collection and transformation workflows.Source: 7th EAGLE International Conference, Roma, Italy, 27-29 Gennaio 2016
Project(s): EAGLE

See at: CNR ExploRA Open Access


2014 Report Open Access OPEN

EAGLE - First Release of AIM Infrastructure (version 1.0)
Amato G., Bolettieri P., Falchi F., Manghi P., Mannocci A., Zoppi F.
This document describes the current implementation (Release 1) of the EAGLE Aggregation and Image Retrieval system (AIM) Infrastructure in terms of: . Current implementation against the specification given in "D4.1 AIM Infrastructure Specification" (Section 1). . Details about the Metadata Aggregation System (Section 2). . Details about the Image Retrieval System (Section 3). . HW & SW requirements of the AIM (Section 4). For details about the full featured AIM Infrastructure, please refer to the released document "D4.1 AIM Infrastructure Specification".Source: Project report, EAGLE, Deliverable D4.2.1, 2014
Project(s): EAGLE

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


2014 Report Open Access OPEN

EAGLE - EAGLE metadata model specification (version 1.0)
Sicilia M., Gomez-pantoja J., Fuentes M. J. R., Ruiz E. R., Mannocci A., Manghi P., Zoppi F.
The main goal of the the EAGLE project is to aggregate into the EAGLE portal data from the EAGLE partners who have epigraphic data bases (the so called Content Providers), and then ingest these data into Europeana. The purpose of this document is to define a common data model to which all the Content Providers can map their own data sets so that all the collected material can be managed in a uniform an coherent way, both for ingestion to Europeana and for supporting advanced search functionality over the aggregated data.Source: Project report, EAGLE, Deliverable D3.1, 2014
Project(s): EAGLE

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


2014 Journal article Open Access OPEN

The D-NET software toolkit A framework for the realization, maintenance, and operation of aggregative infrastructures
Manghi P., Artini M., Atzori C., Bardi A., Mannocci A., La Bruzzo S., Candela L., Castelli D., Pagano P.
Purpose This paper presents the architectural principles and the services of the D-NET Software Toolkit. D-NET is a framework where designers and developers find the tools for constructing and operating aggregative infrastructures (systems for aggregating data sources with heterogeneous data models and technologies) in a cost-effective way. Designers and developers can select from a variety of D-NET data management services, can configure them to handle data according to given data models, and can construct autonomic workflows to obtain personalized aggregative infrastructures. Design/methodology/approach The paper provides a definition of aggregative infrastructures, sketching architecture and components, as inspired by real-case examples. It then describes the limits of current solutions, which find their lacks in the realization and maintenance costs of such complex software. Finally, it proposes D-NET as an optimal solution for designers and developers willing to realize aggregative infrastructures. The D-NET architecture and services are presented, drawing a parallel with the ones of aggregative infrastructures. Finally, real-cases of D-NET are presented, to show-case the statement above. Findings The D-NET software toolkit is a general-purpose service-oriented framework where designers can construct customised, robust, scalable, autonomic aggregative infrastructures in a cost-effective way. D-NET is today adopted by several EC projects, national consortia and communities to create customised infrastructures under diverse application domains, and other organisations are enquiring for or are experimenting its adoption. Its customisability and extendibility make D-NET a suitable candidate for creating aggregative infrastructures mediating between different scientific domains and therefore supporting multi-disciplinary research. Originality/value D-NET is the first general-purpose framework of this kind. Other solutions are available in the literature but focus on specific use-cases and therefore suffer from the limited re-use in different contexts. Due to its maturity, D-NET can also be used by third-party organizations, not necessarily involved in the software design and maintenance.Source: Program (Lond., 1966) 48 (2014): 322–354. doi:10.1108/PROG-08-2013-0045
DOI: 10.1108/prog-08-2013-0045
Project(s): OPENAIREPLUS via OpenAIRE

See at: ISTI Repository Open Access | Program electronic library and information systems Open Access | Program electronic library and information systems Restricted | Program electronic library and information systems Restricted | Program electronic library and information systems Restricted | CNR ExploRA Restricted | Program electronic library and information systems Restricted | Program electronic library and information systems Restricted | www.emeraldinsight.com Restricted | Program electronic library and information systems Restricted | Program electronic library and information systems Restricted


2014 Contribution to book Restricted

Preliminary analysis of data sources interlinking
Mannocci A. K, Manghi P.
The novel e-Science's data-centric paradigm has proved that interlinking publications and research data objects coming from different realms and data sources (e.g. publication repositories, data repositories) makes dissemination, re-use, and validation of research activities more effective. Scholarly Communication Infrastructures (SCIs) are advocated for bridging such data sources by offering an overlay of services for identification, creation, and navigation of relationships among objects of different nature. Since realization and maintenance of such infrastructures is in general very cost-consuming, in this paper we propose a lightweight approach for "preliminary analysis of data source interlinking" to help practitioners at evaluating whether and to what extent realizing them can be effective. We present Data Searchery, a configurable tool delivering a service for relating objects across data sources, be them publications or research data, by identifying relationships between their metadata descriptions in real-time.Source: Theory and Practice of Digital Libraries -- TPDL 2013 Selected Workshops, edited by ?ukasz Bolikowski, Vittore Casarosa, Paula Goodale, Nikos Houssos, Paolo Manghi, Jochen Schirrwagen, pp. 53–64. Berlin: Springer, 2014
DOI: 10.1007/978-3-319-08425-1_6
DOI: 10.1007/978-3-319-14226-5_6

See at: academic.microsoft.com Restricted | biblioproxy.cnr.it Restricted | link.springer.com Restricted | link.springer.com Restricted | link.springer.com Restricted | link.springer.com Restricted | CNR ExploRA Restricted | rd.springer.com Restricted