2020
Report
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.Source: Project report, RISIS 2, D4.2, 2020
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.Source: Project report, RISIS 2, D4.2, 2020
Project(s): RISIS 2
See at:
ISTI Repository 
| CNR ExploRA
2007
Journal article
Closed Access
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.Source: Lecture notes in computer science 4853 (2007): 195–209. doi:10.1007/978-3-540-76876-0_13
DOI: 10.1007/978-3-540-76876-0_13
Metrics:
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.Source: Lecture notes in computer science 4853 (2007): 195–209. doi:10.1007/978-3-540-76876-0_13
DOI: 10.1007/978-3-540-76876-0_13
Metrics:
See at:
doi.org 
| www.springerlink.com | CNR ExploRA
2007
Contribution to book
Unknown
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.Source: Mobility, Data Mining, and Privacy, edited by F. Giannotti and D. Pedreschi, pp. 335–374. Berlin: Springer-Verlag, 2007
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.Source: Mobility, Data Mining, and Privacy, edited by F. Giannotti and D. Pedreschi, pp. 335–374. Berlin: Springer-Verlag, 2007
See at: CNR ExploRA
2010
Report
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.Source: ISTI Technical reports, 2010
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.Source: ISTI Technical reports, 2010
See at:
ISTI Repository | CNR ExploRA
2011
Conference article
Restricted
Improving geodatabase semantic querying exploiting ontologies
Baglioni M., Masserotti M. V., 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.Source: Geospatial Semantics. 4th International Conference, GeoS 2011, pp. 16–33, Brest, Francia, 12-13 May 2011
DOI: 10.1007/978-3-642-20630-6_2
Metrics:
Baglioni M., Masserotti M. V., 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.Source: Geospatial Semantics. 4th International Conference, GeoS 2011, pp. 16–33, Brest, Francia, 12-13 May 2011
DOI: 10.1007/978-3-642-20630-6_2
Metrics:
See at:
doi.org | www.springerlink.com | CNR ExploRA
2018
Journal article
Open Access
Navigating the unfolding open data landscape in ecology and evolution
Culina A., Baglioni M., Crowther T. W., Visser M. E., Woutersen-Windhouwer 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 On line 2 (2018): 420–426. doi:10.1038/s41559-017-0458-2
DOI: 10.1038/s41559-017-0458-2
Metrics:
Culina A., Baglioni M., Crowther T. W., Visser M. E., Woutersen-Windhouwer 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 On line 2 (2018): 420–426. doi:10.1038/s41559-017-0458-2
DOI: 10.1038/s41559-017-0458-2
Metrics:
See at:
Nature Ecology & Evolution | ISTI Repository | NARCIS | Croatian Scientific Bibliography - CROSBI | www.nature.com | Nature Ecology & Evolution | Nature Ecology & Evolution | CNR ExploRA
2019
Report
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.Source: ISTI Technical reports, 2019
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.Source: ISTI Technical reports, 2019
DOI: 10.5281/zenodo.2643199
DOI: 10.5281/zenodo.2643198
Project(s): OPENAIREPLUS
, OPENAIRE , OpenAIRE2020 , OpenAIRE-Connect , OpenAIRE-Advance Metrics:
See at:
ISTI Repository | ZENODO | CNR ExploRA
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, 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 ExploRA
2022
Software
Unknown
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 ExploRA
2021
Report
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.Source: ISTI Project Report, Be Open, D3.2, 2021
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.Source: ISTI Project Report, Be Open, D3.2, 2021
DOI: 10.5281/zenodo.4585548
DOI: 10.5281/zenodo.4585547
Project(s): BE OPEN
Metrics:
See at:
ZENODO | ZENODO | ISTI Repository | CNR ExploRA
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.Source: Advances in Conceptual Modeling - Challenges and Opportunities. ER 2008 Workshops CMLSA, ECDM, FP-UML, M2AS, RIGiM, SeCoGIS, WISM Workshop on Semantic and Conceptual Issues in GIS, pp. 344–353, Barcellona, Spain, 20-23 ottobre 2008
DOI: 10.1007/978-3-540-87991-6_41
Metrics:
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.Source: Advances in Conceptual Modeling - Challenges and Opportunities. ER 2008 Workshops CMLSA, ECDM, FP-UML, M2AS, RIGiM, SeCoGIS, WISM Workshop on Semantic and Conceptual Issues in GIS, pp. 344–353, Barcellona, Spain, 20-23 ottobre 2008
DOI: 10.1007/978-3-540-87991-6_41
Metrics:
See at:
doi.org | www.springerlink.com | CNR ExploRA
2008
Journal article
Unknown
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) 12 (suppl. 1) (2008): 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) 12 (suppl. 1) (2008): 31–44.
See at: CNR ExploRA
2017
Report
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.Source: Project report, OpenAIRE, Deliverable D4.1, 2017
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.Source: Project report, OpenAIRE, Deliverable D4.1, 2017
Project(s): OpenAIRE-Connect
See at:
support.d4science.org | CNR ExploRA
2017
Report
Restricted
OpenAIRE - OpenAIRE back-end and Invenio upgrade: specification and releaseplan
Manghi P., Atzori C., Bardi A., Baglioni M., Nielsen L. H.
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.Source: Project report, OpenAIRE, Deliverable D4.2, 2017
Project(s): OpenAIRE-Connect
Manghi P., Atzori C., Bardi A., Baglioni M., Nielsen L. H.
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.Source: Project report, OpenAIRE, Deliverable D4.2, 2017
Project(s): OpenAIRE-Connect
See at:
support.d4science.org | CNR ExploRA
2019
Report
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.Source: ISTI Technical reports, 2019
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
2013
Journal article
Restricted
How you move reveals who you are: Understanding human behavior by analyzing trajectory data
Renso C., Baglioni M., Fernandes De Macêdo J. A., Trasarti R., Wachowicz M.
The widespread use of mobile devices is producing a huge amount of trajectory data, making the discovery of movement patterns possible, which are crucial for understanding human behavior. Significant advances have been made with regard to knowledge discovery, but the process now needs to be extended bearing in mind the emerging field of behavior informatics. This paper describes the formalization of a semantic-enriched KDD process for supporting meaningful pattern interpretations of human behavior. Our approach is based on the integration of inductive reasoning (movement pattern discovery) and deductive reasoning (human behavior inference). We describe the implemented Athena system, which supports such a process, along with the experimental results on two different application domains related to traffic and recreation management. © 2012 Springer-Verlag London Limited.Source: Knowledge and Information Systems 37 (2013): 331–362. doi:10.1007/s10115-012-0511-z
DOI: 10.1007/s10115-012-0511-z
Metrics:
Renso C., Baglioni M., Fernandes De Macêdo J. A., Trasarti R., Wachowicz M.
The widespread use of mobile devices is producing a huge amount of trajectory data, making the discovery of movement patterns possible, which are crucial for understanding human behavior. Significant advances have been made with regard to knowledge discovery, but the process now needs to be extended bearing in mind the emerging field of behavior informatics. This paper describes the formalization of a semantic-enriched KDD process for supporting meaningful pattern interpretations of human behavior. Our approach is based on the integration of inductive reasoning (movement pattern discovery) and deductive reasoning (human behavior inference). We describe the implemented Athena system, which supports such a process, along with the experimental results on two different application domains related to traffic and recreation management. © 2012 Springer-Verlag London Limited.Source: Knowledge and Information Systems 37 (2013): 331–362. doi:10.1007/s10115-012-0511-z
DOI: 10.1007/s10115-012-0511-z
Metrics:
See at:
Knowledge and Information Systems | link.springer.com | CNR ExploRA
2021
Conference article
Open Access
Reflections on the misuses of ORCID iDs
Baglioni M., Mannocci A., Manghi P., Atzori C., Bardi A., La Bruzzo S.
Since 2012, the "Open Researcher and Contributor Identification Initiative" (ORCID) has been successfully running a worldwide registry, with the aim of unequivocally pinpoint researchers and the body of knowledge they contributed to. In practice, ORCID clients, e.g., publishers, repositories, and CRIS systems, make sure their metadata can refer to iDs in the ORCID registry to associate authors and their work unambiguously. However, the ORCID infrastructure still suffers from several "service misuses", which put at risk its very mission and should be therefore identified and tackled. In this paper, we classify and qualitatively document such misuses, occurring from both users (researchers and organisations) of the ORCID registry and the ORCID clients. We conclude providing an outlook and a few recommendations aiming at improving the exploitation of the ORCID infrastructure.Source: IRCDL 2021 - 17th Italian Research Conference on Digital Libraries, pp. 117–125, Online conference, 18-19/02/2021
Project(s): OpenAIRE-Advance
Baglioni M., Mannocci A., Manghi P., Atzori C., Bardi A., La Bruzzo S.
Since 2012, the "Open Researcher and Contributor Identification Initiative" (ORCID) has been successfully running a worldwide registry, with the aim of unequivocally pinpoint researchers and the body of knowledge they contributed to. In practice, ORCID clients, e.g., publishers, repositories, and CRIS systems, make sure their metadata can refer to iDs in the ORCID registry to associate authors and their work unambiguously. However, the ORCID infrastructure still suffers from several "service misuses", which put at risk its very mission and should be therefore identified and tackled. In this paper, we classify and qualitatively document such misuses, occurring from both users (researchers and organisations) of the ORCID registry and the ORCID clients. We conclude providing an outlook and a few recommendations aiming at improving the exploitation of the ORCID infrastructure.Source: IRCDL 2021 - 17th Italian Research Conference on Digital Libraries, pp. 117–125, Online conference, 18-19/02/2021
Project(s): OpenAIRE-Advance
See at:
ceur-ws.org | ISTI Repository | CNR ExploRA
2021
Dataset
Unknown
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
Metrics:
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
Metrics:
See at: CNR ExploRA
2022
Conference article
Open Access
"Knock Knock! Who's There?" A study on scholarly repositories' availability
Mannocci A., Baglioni M., Manghi P.
Scholarly repositories are the cornerstone of modern open science, and their availability is vital for enacting its practices. To this end, scholarly registries such as FAIRsharing, re3data, OpenDOAR and ROAR give them presence and visibility across different research communities, disciplines, and applications by assigning an identifier and persisting their profiles with summary metadata. Alas, like any other resource available on the Web, scholarly repositories, be they tailored for literature, software or data, are quite dynamic and can be frequently changed, moved, merged or discontinued. Therefore, their references are prone to link rot over time, and their availability often boils down to whether the homepage URLs indicated in authoritative repository profiles within scholarly registries respond or not. For this study, we harvested the content of four prominent scholarly registries and resolved over 13 thousand unique repository URLs. By performing a quantitative analysis on such an extensive collection of repositories, this paper aims to provide a global snapshot of their availability, which bewilderingly is far from granted.Source: TPDL 2022 - 26th International Conference on Theory and Practice of Digital Libraries, pp. 306–312, Padua, Italy, 20-23/09/2022
DOI: 10.1007/978-3-031-16802-4_26
Project(s): OpenAIRE Nexus
Metrics:
Mannocci A., Baglioni M., Manghi P.
Scholarly repositories are the cornerstone of modern open science, and their availability is vital for enacting its practices. To this end, scholarly registries such as FAIRsharing, re3data, OpenDOAR and ROAR give them presence and visibility across different research communities, disciplines, and applications by assigning an identifier and persisting their profiles with summary metadata. Alas, like any other resource available on the Web, scholarly repositories, be they tailored for literature, software or data, are quite dynamic and can be frequently changed, moved, merged or discontinued. Therefore, their references are prone to link rot over time, and their availability often boils down to whether the homepage URLs indicated in authoritative repository profiles within scholarly registries respond or not. For this study, we harvested the content of four prominent scholarly registries and resolved over 13 thousand unique repository URLs. By performing a quantitative analysis on such an extensive collection of repositories, this paper aims to provide a global snapshot of their availability, which bewilderingly is far from granted.Source: TPDL 2022 - 26th International Conference on Theory and Practice of Digital Libraries, pp. 306–312, Padua, Italy, 20-23/09/2022
DOI: 10.1007/978-3-031-16802-4_26
Project(s): OpenAIRE Nexus
Metrics:
See at:
ISTI Repository | link.springer.com | CNR ExploRA
2022
Report
Open Access
Data model description of the OpenAIRE Research Graph
La Bruzzo S. F., Artini M., Atzori C., Bardi A., Baglioni M., De Bonis M., Mannocci A., Manghi P., Pavone G.
The OpenAIRE Graph (formerly known as the OpenAIRE Research Graph) is one of the largest open scholarly record collections worldwide, key to fostering Open Science and establishing its practices in 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 into the hands of the scientific community. Imagine a vast collection of research products all linked together, contextualized, and openly available. For the past years, OpenAIRE has been working to gather this valuable record. It is a massive collection of metadata and links between scientific products such as articles, datasets, software, and other research products, entities like organizations, funders, funding streams, projects, communities, and data sources. This technical Report describes the public data model adopted by the OpenAIRE Graph.Source: ISTI Technical Report, ISTI-2022-TR/031, 2022
DOI: 10.32079/isti-tr-2022/031
Metrics:
La Bruzzo S. F., Artini M., Atzori C., Bardi A., Baglioni M., De Bonis M., Mannocci A., Manghi P., Pavone G.
The OpenAIRE Graph (formerly known as the OpenAIRE Research Graph) is one of the largest open scholarly record collections worldwide, key to fostering Open Science and establishing its practices in 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 into the hands of the scientific community. Imagine a vast collection of research products all linked together, contextualized, and openly available. For the past years, OpenAIRE has been working to gather this valuable record. It is a massive collection of metadata and links between scientific products such as articles, datasets, software, and other research products, entities like organizations, funders, funding streams, projects, communities, and data sources. This technical Report describes the public data model adopted by the OpenAIRE Graph.Source: ISTI Technical Report, ISTI-2022-TR/031, 2022
DOI: 10.32079/isti-tr-2022/031
Metrics:
See at:
ISTI Repository | CNR ExploRA