2020
Other
Open Access
RISIS 2 - Opening of Open Data VRE
Assante M, Baglioni M, Bardi A, Mangiacrapa F, Pagano P
This report is a short document accompanying the Deliverable "D4.2 Opening of Open Data VRE", which is of type: "Websites, patents filling, etc.". It describes the design of the software components involved in the Open Data VRE, deployed to serve the current needs of the RISIS community.Project(s): RISIS 2
Assante M, Baglioni M, Bardi A, Mangiacrapa F, Pagano P
This report is a short document accompanying the Deliverable "D4.2 Opening of Open Data VRE", which is of type: "Websites, patents filling, etc.". It describes the design of the software components involved in the Open Data VRE, deployed to serve the current needs of the RISIS community.Project(s): RISIS 2
See at:
CNR IRIS 
| ISTI Repository | CNR IRIS 
2007
Contribution to book
Restricted
Querying and Reasoning for Spatiotemporal Data Mining
Manco G, Baglioni M, Giannotti F, Bart Kuijpers, Alessandra Raffaetà, Renso C
In the previous chapters, we studied movement data from several perspectives: the application opportunities, the type of analytical questions, the modeling requirements, and the challenges for mining. Moreover, the complexity of the overall analysis process was pointed out several times. The analytical questions posed by the end user need to be translated into several tasks such as choose analysismethods, prepare the data for application of these methods, apply the methods to the data, and interpret and evaluate the results obtained.
Manco G, Baglioni M, Giannotti F, Bart Kuijpers, Alessandra Raffaetà, Renso C
In the previous chapters, we studied movement data from several perspectives: the application opportunities, the type of analytical questions, the modeling requirements, and the challenges for mining. Moreover, the complexity of the overall analysis process was pointed out several times. The analytical questions posed by the end user need to be translated into several tasks such as choose analysismethods, prepare the data for application of these methods, apply the methods to the data, and interpret and evaluate the results obtained.
2016
Other
Restricted
Analysis of DataCite for paper - dataset context propagation
Baglioni M.
Scholarly communication graphs represent semantic relations between scientific products (papers, data, algorithms, etc), authors, organizations and research projects. In this context the aim is to find a way to measure the distance between papers and data (semantic correlation) to obtain a better data discovery. In fact, data metadata are poor, and the identification of a correlation distance between a paper (richer) and data allows to propagate the context (for example abstract) from the richer object to the other one
Baglioni M.
Scholarly communication graphs represent semantic relations between scientific products (papers, data, algorithms, etc), authors, organizations and research projects. In this context the aim is to find a way to measure the distance between papers and data (semantic correlation) to obtain a better data discovery. In fact, data metadata are poor, and the identification of a correlation distance between a paper (richer) and data allows to propagate the context (for example abstract) from the richer object to the other one
2024
Conference article
Metadata Only Access
Exploring Scientometrics with the OpenAIRE Graph: Introducing the OpenAIRE Beginner's Kit
Andrea Mannocci, Miriam Baglioni
The OpenAIRE Graph is an extensive resource housing diverse information onresearch products, including literature, datasets, and software, alongsideresearch projects and other scholarly outputs and context. It stands as acornerstone among contemporary research information databases, offeringinvaluable insights for scientometric investigations. Despite its wealth ofdata, its sheer size may initially appear daunting, potentially hindering itswidespread adoption. To address this challenge, this paper introduces theOpenAIRE Beginner's Kit, a user-friendly solution providing access to a subsetof the OpenAIRE Graph within a sandboxed environment coupled with a Jupyternotebook for analysis. The OpenAIRE Beginner's Kit is meticulously designed todemocratise research and data exploration, offering accessibility from standarddesktop and laptop setups. Within this paper, we provide a brief overview ofthe included dataset and offer guidance on leveraging the kit through aselection of illustrative queries tailored to address common scientometricinquiries.
Andrea Mannocci, Miriam Baglioni
The OpenAIRE Graph is an extensive resource housing diverse information onresearch products, including literature, datasets, and software, alongsideresearch projects and other scholarly outputs and context. It stands as acornerstone among contemporary research information databases, offeringinvaluable insights for scientometric investigations. Despite its wealth ofdata, its sheer size may initially appear daunting, potentially hindering itswidespread adoption. To address this challenge, this paper introduces theOpenAIRE Beginner's Kit, a user-friendly solution providing access to a subsetof the OpenAIRE Graph within a sandboxed environment coupled with a Jupyternotebook for analysis. The OpenAIRE Beginner's Kit is meticulously designed todemocratise research and data exploration, offering accessibility from standarddesktop and laptop setups. Within this paper, we provide a brief overview ofthe included dataset and offer guidance on leveraging the kit through aselection of illustrative queries tailored to address common scientometricinquiries.
2007
Journal article
Restricted
Building geospatial ontologies from geographical databases
Baglioni M, Masserotti M V, Renso C, Spinsanti L
The last few years have seen a growing interest in approaches that define methodologies to automatically extract semantics from databases by using ontologies. Geographic data are very rarely collected in a well organized way, quite often they lack both metadata and conceptual schema. Extracting semantic information from data stored in a geodatabase is complex and an extension of the existing methodologies is needed. We describe an approach to extract a geospatial ontology from geographical data stored in spatial databases. To provide geospatial semantics we introduce new relations which define geospatial ontology that can serve as a basis for an advanced user querying system. Some examples of use of the methodology in the urban domain are presented.
Baglioni M, Masserotti M V, Renso C, Spinsanti L
The last few years have seen a growing interest in approaches that define methodologies to automatically extract semantics from databases by using ontologies. Geographic data are very rarely collected in a well organized way, quite often they lack both metadata and conceptual schema. Extracting semantic information from data stored in a geodatabase is complex and an extension of the existing methodologies is needed. We describe an approach to extract a geospatial ontology from geographical data stored in spatial databases. To provide geospatial semantics we introduce new relations which define geospatial ontology that can serve as a basis for an advanced user querying system. Some examples of use of the methodology in the urban domain are presented.
See at:
CNR IRIS | CNR IRIS | www.springerlink.com
2008
Conference article
Restricted
An ontology-based approach for the semantic modelling and reasoning on trajectories
Baglioni M, Macedo J, Renso C, Wachowicz M
In this paper we present a methodology for the semantic enrichment of trajectories. The objective of this process is to provide a semantic interpretation of a trajectory in term of behaviour. This has been achieved by enhancing raw trajectories with semantic information about moves and stops and by exploiting some domain knowledge encoded in an ontology. Furthermore, the reasoning mechanisms provided by the OWL ontology formalism have been exploited to accomplish a further semantic enrichment step that puts together the different levels of knowledge of the domain. A final example application shows the added power of the enrichment process in characterizing people behaviour.
Baglioni M, Macedo J, Renso C, Wachowicz M
In this paper we present a methodology for the semantic enrichment of trajectories. The objective of this process is to provide a semantic interpretation of a trajectory in term of behaviour. This has been achieved by enhancing raw trajectories with semantic information about moves and stops and by exploiting some domain knowledge encoded in an ontology. Furthermore, the reasoning mechanisms provided by the OWL ontology formalism have been exploited to accomplish a further semantic enrichment step that puts together the different levels of knowledge of the domain. A final example application shows the added power of the enrichment process in characterizing people behaviour.
See at:
CNR IRIS | CNR IRIS | www.springerlink.com
2010
Other
Open Access
An algorithm to enhance queries over a geodatabase
Baglioni M, Masserotti M V, Renso C, Spinsanti L
Geospatial semantic querying to spatial databases has been recognized as a hot topic in GIS research, although no standardized approaches have been proposed so far. However, a common solution is to adopt an ontology as a knowledge representation structure on top of a spatial database to support user queries. In this context, we propose an approach to build an ontology which, not only represents the concepts stored in the database and their semantic abstractions, but it is also capable of managing the defined specializations of such concepts. The methodology introduced in this paper aims at building this richer ontology and the associated materialized views to handle the semantic query translation.
Baglioni M, Masserotti M V, Renso C, Spinsanti L
Geospatial semantic querying to spatial databases has been recognized as a hot topic in GIS research, although no standardized approaches have been proposed so far. However, a common solution is to adopt an ontology as a knowledge representation structure on top of a spatial database to support user queries. In this context, we propose an approach to build an ontology which, not only represents the concepts stored in the database and their semantic abstractions, but it is also capable of managing the defined specializations of such concepts. The methodology introduced in this paper aims at building this richer ontology and the associated materialized views to handle the semantic query translation.
See at:
CNR IRIS | ISTI Repository | CNR IRIS
2011
Conference article
Restricted
Improving geodatabase semantic querying exploiting ontologies
Baglioni M, Masserotti Mv, Renso C, Spinsanti L
Geospatial semantic querying to geographical databases has been recognized as an hot topic in GIS research. Most approaches propose to adopt an ontology as a knowledge representation structure on top of the database, representing the concepts the user can query. These concepts are typically directly mapped to database tables. In this paper we propose a methodology where the ontology is further exploited mapping axioms to spatial SQL queries. The main advantage of this approach is that semantic-rich geospatial queries can be abstractly represented in the ontology and can be automatically translated into spatial SQL queries.
Baglioni M, Masserotti Mv, Renso C, Spinsanti L
Geospatial semantic querying to geographical databases has been recognized as an hot topic in GIS research. Most approaches propose to adopt an ontology as a knowledge representation structure on top of the database, representing the concepts the user can query. These concepts are typically directly mapped to database tables. In this paper we propose a methodology where the ontology is further exploited mapping axioms to spatial SQL queries. The main advantage of this approach is that semantic-rich geospatial queries can be abstractly represented in the ontology and can be automatically translated into spatial SQL queries.
See at:
CNR IRIS | CNR IRIS | CNR IRIS | www.springerlink.com
2018
Journal article
Open Access
Navigating the unfolding open data landscape in ecology and evolution
Culina A, Baglioni M, Crowther Tw, Visser Me, Woutersenwindhouwer S, Manghi P
Open access to data is revolutionizing the sciences. To allow ecologists and evolutionary biologists to confidently find and use the existing data, we provide an overview of the landscape of online data infrastructures, and highlight the key points to consider when using open data. We introduce an online collaborative platform to keep a community-driven, updated list of the best sources that enable search for data in one interface. In doing so, our aim is to lower the barrier to accessing open data, and encourage its use by researchers hoping to increase the scope, reliability and value of their findings.Source: NATURE ECOLOGY & EVOLUTION, vol. 2 (issue 3), pp. 420-426
Culina A, Baglioni M, Crowther Tw, Visser Me, Woutersenwindhouwer S, Manghi P
Open access to data is revolutionizing the sciences. To allow ecologists and evolutionary biologists to confidently find and use the existing data, we provide an overview of the landscape of online data infrastructures, and highlight the key points to consider when using open data. We introduce an online collaborative platform to keep a community-driven, updated list of the best sources that enable search for data in one interface. In doing so, our aim is to lower the barrier to accessing open data, and encourage its use by researchers hoping to increase the scope, reliability and value of their findings.Source: NATURE ECOLOGY & EVOLUTION, vol. 2 (issue 3), pp. 420-426
See at:
CNR IRIS | ISTI Repository | www.nature.com | CNR IRIS
2019
Other
Open Access
The OpenAIRE Research Graph Data Model
Manghi P, Bardi A, Atzori C, Baglioni M, Manola N, Schirrwagen J, Principe P
The purpose of the European OpenAIRE infrastructure is to facilitate, foster, support, and monitor Open Science scholarly communication in Europe. The infrastructure has been operational for almost a decade and successful in linking people, ideas and resources in support of the free flow, access, sharing, and re-use of research outcomes. To this aim it offers dissemination and training on Open Access and Open Science, facilitates exchange of knowledge, and operates the technical services required to facilitate and monitor Open Science publishing trends and research impact across geographic and discipline boundaries. OpenAIRE services populate a research graph whose objects are scientific results, organizations, funders, communities, organizations, and data sources. In this article we describe the data model, inspired by several existing metadata standards.DOI: 10.5281/zenodo.2643199
DOI: 10.5281/zenodo.2643198
Project(s): OPENAIREPLUS, OPENAIRE , OpenAIRE2020 , OpenAIRE-Connect , OpenAIRE-Advance
Metrics:
Manghi P, Bardi A, Atzori C, Baglioni M, Manola N, Schirrwagen J, Principe P
The purpose of the European OpenAIRE infrastructure is to facilitate, foster, support, and monitor Open Science scholarly communication in Europe. The infrastructure has been operational for almost a decade and successful in linking people, ideas and resources in support of the free flow, access, sharing, and re-use of research outcomes. To this aim it offers dissemination and training on Open Access and Open Science, facilitates exchange of knowledge, and operates the technical services required to facilitate and monitor Open Science publishing trends and research impact across geographic and discipline boundaries. OpenAIRE services populate a research graph whose objects are scientific results, organizations, funders, communities, organizations, and data sources. In this article we describe the data model, inspired by several existing metadata standards.DOI: 10.5281/zenodo.2643199
DOI: 10.5281/zenodo.2643198
Project(s): OPENAIREPLUS
, OPENAIRE , OpenAIRE2020 , OpenAIRE-Connect , OpenAIRE-Advance Metrics:
See at:
CNR IRIS | ISTI Repository | ZENODO | CNR IRIS
2021
Dataset
Metadata Only Access
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
Metrics:
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 Metrics:
See at:
CNR IRIS
2022
Software
Metadata Only Access
dnet-dedup framework
Artini M., Atzori C., Bardi A., Baglioni M., De Bonis M., Dell'Amico A., La Bruzzo S. F., Mannocci A., Manghi P.
The GDup Software enables an integrated, scalable, general-purpose system for entity deduplication over big information graphs. GDup supports practitioners with the functionalities needed to realize a fully-fledged entity deduplication workflow over a generic input graph, including Ground Truth support, end-user feedback, and strategies for identifying and merging duplicates to obtain an output disambiguated graph. GDup is today one of the core components of the OpenAIRE infrastructure production system, monitoring Open Science trends on behalf of the European Commission.Project(s): OpenAIRE-Advance, OpenAIRE Nexus
Artini M., Atzori C., Bardi A., Baglioni M., De Bonis M., Dell'Amico A., La Bruzzo S. F., Mannocci A., Manghi P.
The GDup Software enables an integrated, scalable, general-purpose system for entity deduplication over big information graphs. GDup supports practitioners with the functionalities needed to realize a fully-fledged entity deduplication workflow over a generic input graph, including Ground Truth support, end-user feedback, and strategies for identifying and merging duplicates to obtain an output disambiguated graph. GDup is today one of the core components of the OpenAIRE infrastructure production system, monitoring Open Science trends on behalf of the European Commission.Project(s): OpenAIRE-Advance
, OpenAIRE Nexus
See at:
github.com | CNR IRIS
2022
Other
Open Access
OpenAIRE Research Graph deduplication workflow
La Bruzzo Sf, Artini M, Atzori C, Bardi A, Baglioni M, De Bonis M, Mannocci A, Manghi P, Pavone G
The OpenAIRE aggregation workflow can collect metadata records from different providers about the same scholarly work. Each metadata record can carry different information because, for example, some providers are not aware of links to projects, keywords, or other details. Another typical case is when OpenAIRE collects one metadata record from a repository about a pre-print and another from a journal about the published article. To provide correct statistics, OpenAIRE must identify those cases and "merge" the two metadata records so that the scholarly work is counted only once in the statistics OpenAIRE produces. This technical Report describes the Deduplication workflow and technique adopted to deduplicate the OpenAIRE Graph.DOI: 10.32079/isti-tr-2022/032
Project(s): OpenAIRE-Connect, OpenAIRE Nexus
Metrics:
La Bruzzo Sf, Artini M, Atzori C, Bardi A, Baglioni M, De Bonis M, Mannocci A, Manghi P, Pavone G
The OpenAIRE aggregation workflow can collect metadata records from different providers about the same scholarly work. Each metadata record can carry different information because, for example, some providers are not aware of links to projects, keywords, or other details. Another typical case is when OpenAIRE collects one metadata record from a repository about a pre-print and another from a journal about the published article. To provide correct statistics, OpenAIRE must identify those cases and "merge" the two metadata records so that the scholarly work is counted only once in the statistics OpenAIRE produces. This technical Report describes the Deduplication workflow and technique adopted to deduplicate the OpenAIRE Graph.DOI: 10.32079/isti-tr-2022/032
Project(s): OpenAIRE-Connect
, OpenAIRE Nexus Metrics:
See at:
CNR IRIS | ISTI Repository | CNR IRIS
2021
Other
Open Access
Be Open - D3.2: TOPOS development
Spanidis P, Giannakari O, Garcia C, Anagnostopoulou A, Bardi A, Dimitropoulos H, Foufoulas Y, Baglioni M
This deliverable describes the design and implementation of the TOPOS forum and observatory. More analytically, it describes the methodology selected for each particular tool together with the technologies that have been used for the implementation of these tools. D3.2 is organized in 8 chapters. The first one is an introductory chapter presenting the aim and objectives of the current deliverable, the second describes the interconnection between Task 3.1 and Task 3.2. Chapter 3 deals with the TOPOS Gateway while Chapters 4 and 5 present the actual tools that have been developed (Observatory and Forum). Deliverable's conclusions are hosted in the last chapter.DOI: 10.5281/zenodo.4585548
DOI: 10.5281/zenodo.4585547
Project(s): BE OPEN
Metrics:
Spanidis P, Giannakari O, Garcia C, Anagnostopoulou A, Bardi A, Dimitropoulos H, Foufoulas Y, Baglioni M
This deliverable describes the design and implementation of the TOPOS forum and observatory. More analytically, it describes the methodology selected for each particular tool together with the technologies that have been used for the implementation of these tools. D3.2 is organized in 8 chapters. The first one is an introductory chapter presenting the aim and objectives of the current deliverable, the second describes the interconnection between Task 3.1 and Task 3.2. Chapter 3 deals with the TOPOS Gateway while Chapters 4 and 5 present the actual tools that have been developed (Observatory and Forum). Deliverable's conclusions are hosted in the last chapter.DOI: 10.5281/zenodo.4585548
DOI: 10.5281/zenodo.4585547
Project(s): BE OPEN
Metrics:
See at:
ZENODO | ZENODO | CNR IRIS | ISTI Repository | CNR IRIS
2024
Conference article
Open Access
The ARIADNEplus Knowledge Base: a Linked Open Data set for archaeological research
Bardi A., Baglioni M., Artini M., Mannocci A., Pavone G.
The ARIADNE infrastructure provides tools and services for researchers to address archaeological grand challenges that require discovery and analysis of information scattered across different thematic and geographically distributed sources. The ARIADNEplus Knowledge Base (KB) is an archaeological Linked Open Data set modelled according to the ARIADNE ontology, based on CIDOC-CRM, and provided by an international network of organisations leaders in different domains of archaeological sciences. In February 2024, the ARIADNEplus KB features about 4 million archaeological resources. Thanks to the ARIADNE infrastructure, data providers increased the level of fairness of their resources and contributed to a unique asset for the archaeology research community, the European Open Science Cloud and society at large.Source: CEUR WORKSHOP PROCEEDINGS, vol. 3741, pp. 91-100. Viallasimius, Italy, 23-26/06/2024
Project(s): ARIADNEplus, ATRIUM
Bardi A., Baglioni M., Artini M., Mannocci A., Pavone G.
The ARIADNE infrastructure provides tools and services for researchers to address archaeological grand challenges that require discovery and analysis of information scattered across different thematic and geographically distributed sources. The ARIADNEplus Knowledge Base (KB) is an archaeological Linked Open Data set modelled according to the ARIADNE ontology, based on CIDOC-CRM, and provided by an international network of organisations leaders in different domains of archaeological sciences. In February 2024, the ARIADNEplus KB features about 4 million archaeological resources. Thanks to the ARIADNE infrastructure, data providers increased the level of fairness of their resources and contributed to a unique asset for the archaeology research community, the European Open Science Cloud and society at large.Source: CEUR WORKSHOP PROCEEDINGS, vol. 3741, pp. 91-100. Viallasimius, Italy, 23-26/06/2024
Project(s): ARIADNEplus
, ATRIUM
See at:
ceur-ws.org | CNR IRIS | CNR IRIS
2008
Journal article
Restricted
Ontology-supported Querying of Geographical Databases
Baglioni M, Giovannetti E, Masserotti M V, Renso C, Spinsanti L
Querying geographical information systems has been recognized as a difficult task for non-expert users. Furthermore, user queries are often characterized by semantic aspects not directly managed by traditional spatial databases or GIS. Examples of such semantic geospatial queries are the use of implicit spatial relations between objects, or the reference of domain concepts not explicitly represented in data. To handle such queries, we envisage a system that translates natural language queries into spatial SQL statements on a database, thus improving standard GIS with new semantic capabilities. Within this general objective, the contribution of this article is to introduce a methodology to handle semantic geospatial queries issued over a spatial database. This approach captures semantics from an ontology built upon the spatial database and enriched by domain concepts and properties specifically defined to represent the localization of objects. Some examples of the use of the methodology in the urban domain are presented.Source: TRANSACTIONS IN GIS (ONLINE), vol. 12 (suppl. 1), pp. 31-44
Baglioni M, Giovannetti E, Masserotti M V, Renso C, Spinsanti L
Querying geographical information systems has been recognized as a difficult task for non-expert users. Furthermore, user queries are often characterized by semantic aspects not directly managed by traditional spatial databases or GIS. Examples of such semantic geospatial queries are the use of implicit spatial relations between objects, or the reference of domain concepts not explicitly represented in data. To handle such queries, we envisage a system that translates natural language queries into spatial SQL statements on a database, thus improving standard GIS with new semantic capabilities. Within this general objective, the contribution of this article is to introduce a methodology to handle semantic geospatial queries issued over a spatial database. This approach captures semantics from an ontology built upon the spatial database and enriched by domain concepts and properties specifically defined to represent the localization of objects. Some examples of the use of the methodology in the urban domain are presented.Source: TRANSACTIONS IN GIS (ONLINE), vol. 12 (suppl. 1), pp. 31-44
2010
Journal article
Restricted
Improving the business plan evaluation process: the role of intangibles
Turini F, Baglioni M, Bellandi A, Furletti B, Pratesi C
One of the main objectives of the European MUSING project is to design and test software tools in order to support the activities of small and medium sized businesses. In this paper we examine financial risk management and, more specifically, the self-assessment of business plans. The role of intangible assets is discussed, and we report on how intangible assets can be collected, how they can be represented, taking into account their semantic relationships, and how they can be used to build an analytical tool for business plans. The basic technology embedded in the tool is the construction of classification trees, a well-known technique in inductive learning. We show how using knowledge of intangible assets can improve the construction of the classifier, as proved by the testing carried out so far.Source: QUALITY TECHNOLOGY & QUANTITATIVE MANAGEMENT, vol. 7 (issue 1), pp. 35-50
Turini F, Baglioni M, Bellandi A, Furletti B, Pratesi C
One of the main objectives of the European MUSING project is to design and test software tools in order to support the activities of small and medium sized businesses. In this paper we examine financial risk management and, more specifically, the self-assessment of business plans. The role of intangible assets is discussed, and we report on how intangible assets can be collected, how they can be represented, taking into account their semantic relationships, and how they can be used to build an analytical tool for business plans. The basic technology embedded in the tool is the construction of classification trees, a well-known technique in inductive learning. We show how using knowledge of intangible assets can improve the construction of the classifier, as proved by the testing carried out so far.Source: QUALITY TECHNOLOGY & QUANTITATIVE MANAGEMENT, vol. 7 (issue 1), pp. 35-50
See at:
CNR IRIS | CNR IRIS | www.tandfonline.com
2017
Other
Restricted
OpenAIRE - D4.1 OpenAIREdata model extension
Manghi P, Atzori C, Bardi A, Baglioni M, Zoppi F
The aim of this deliverable is to describe how the OpenAIRE data model is extended for the representation of artefacts different from publications and datasets. In particular, OpenAIRE-Connect extends the OpenAIRE data model with: (i) entities for there presentation of research communities, research methods and research packages; (ii) relationships between those new entities and the already existing OpenAIRE entities; (iii) new controlled vocabularies for properties of research methods and packages; and(iv) new termstobeaddedtocontrolledvocabulariesalreadyinusebytheOpenAIREinfrastructure. Requirements have been collected from the research communities involved in OpenAIRE-Connect, which helpedthedefinitionofthemodelextensionsbyspecifyingtheircurrentpracticeanddesiderataaboutthe publishingofresearchartefactsintheirspecificdiscipline.Inadditiontotherequirementsoftheresearch communities, requirements and expectations from the existing "consumers" of the OpenAIRE infrastructure, including data sources (providing content to OpenAIRE), portal end-users of various roles (researchers, project coordinators, general public, research communities), OpenAIRE data curators (responsibleoftheworkflowsforcollecting,harmonizing,de-duplicating,inferringcontent),andthird-party services(accessing content via APIs), have been considered. The data model will be subject to changes in the future, depending on the evolution of the requirements of the OpenAIRE infrastructure and of the communities involved in OpenAIRE-Connect.Project(s): OpenAIRE-Connect
Manghi P, Atzori C, Bardi A, Baglioni M, Zoppi F
The aim of this deliverable is to describe how the OpenAIRE data model is extended for the representation of artefacts different from publications and datasets. In particular, OpenAIRE-Connect extends the OpenAIRE data model with: (i) entities for there presentation of research communities, research methods and research packages; (ii) relationships between those new entities and the already existing OpenAIRE entities; (iii) new controlled vocabularies for properties of research methods and packages; and(iv) new termstobeaddedtocontrolledvocabulariesalreadyinusebytheOpenAIREinfrastructure. Requirements have been collected from the research communities involved in OpenAIRE-Connect, which helpedthedefinitionofthemodelextensionsbyspecifyingtheircurrentpracticeanddesiderataaboutthe publishingofresearchartefactsintheirspecificdiscipline.Inadditiontotherequirementsoftheresearch communities, requirements and expectations from the existing "consumers" of the OpenAIRE infrastructure, including data sources (providing content to OpenAIRE), portal end-users of various roles (researchers, project coordinators, general public, research communities), OpenAIRE data curators (responsibleoftheworkflowsforcollecting,harmonizing,de-duplicating,inferringcontent),andthird-party services(accessing content via APIs), have been considered. The data model will be subject to changes in the future, depending on the evolution of the requirements of the OpenAIRE infrastructure and of the communities involved in OpenAIRE-Connect.Project(s): OpenAIRE-Connect
See at:
CNR IRIS | CNR IRIS | support.d4science.org
2017
Other
Restricted
OpenAIRE - OpenAIRE back-end and Invenio upgrade: specification and releaseplan
Manghi P, Atzori C, Bardi A, Baglioni M, Nielsen Lh
The aim of this document is to explain in detail how the software release plan for upgrading OpenAIRE back-ends and Invenio according to the data model described in D4.1OpenAIREDatamodelextension will be accomplished by the technical partners. For this, it will illustrate the plan of design, development, testing, and integration into beta and production of the infrastructure services to be delivered by T4.1 (OpenAIRE extension to research methods and artifact packages) and T4.2 OpenAIRE's Zenodo for research methodsandartifactpackages).Theplan's technical activities will be supervised and led by CNR and carried out across the technical partners CNR and CERN, in synergy with the partners Jisc, UMinho, UniHB, PIN, CNRS,IRD,ICRE8. The deliverable is on-going and will be updated at M15 (before first BETA release of the service), M23 (beforesecondBETAreleaseoftheservice),andM27 (beforeproductionreleaseoftheservice).The first release of this document reports on extensions to be provided byM8. Toease the update of the planand support the collaborativeapproach, the deliverableis published as a wiki and is available at https://support.d4science.org/projects/openaire-connect-wiki/wiki/D4_2.Project(s): OpenAIRE-Connect
Manghi P, Atzori C, Bardi A, Baglioni M, Nielsen Lh
The aim of this document is to explain in detail how the software release plan for upgrading OpenAIRE back-ends and Invenio according to the data model described in D4.1OpenAIREDatamodelextension will be accomplished by the technical partners. For this, it will illustrate the plan of design, development, testing, and integration into beta and production of the infrastructure services to be delivered by T4.1 (OpenAIRE extension to research methods and artifact packages) and T4.2 OpenAIRE's Zenodo for research methodsandartifactpackages).Theplan's technical activities will be supervised and led by CNR and carried out across the technical partners CNR and CERN, in synergy with the partners Jisc, UMinho, UniHB, PIN, CNRS,IRD,ICRE8. The deliverable is on-going and will be updated at M15 (before first BETA release of the service), M23 (beforesecondBETAreleaseoftheservice),andM27 (beforeproductionreleaseoftheservice).The first release of this document reports on extensions to be provided byM8. Toease the update of the planand support the collaborativeapproach, the deliverableis published as a wiki and is available at https://support.d4science.org/projects/openaire-connect-wiki/wiki/D4_2.Project(s): OpenAIRE-Connect
See at:
CNR IRIS | CNR IRIS | support.d4science.org
2019
Other
Open Access
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.
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.
See at:
CNR IRIS | ISTI Repository | CNR IRIS