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
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.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.DOI: 10.1007/978-3-540-76876-0_13
Metrics:
See at:
doi.org 
| 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.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.DOI: 10.1007/978-3-540-87991-6_41
Metrics:
See at:
doi.org | CNR IRIS | CNR IRIS | www.springerlink.com
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
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.DOI: 10.1007/978-3-642-20630-6_2
Metrics:
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.DOI: 10.1007/978-3-642-20630-6_2
Metrics:
See at:
doi.org | CNR IRIS | CNR IRIS | CNR IRIS | www.springerlink.com
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
DOI: 10.1080/16843703.2010.11673217
Metrics:
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
DOI: 10.1080/16843703.2010.11673217
Metrics:
See at:
Quality Technology & Quantitative Management | CNR IRIS | CNR IRIS | www.tandfonline.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
DOI: 10.1038/s41559-017-0458-2
Metrics:
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
DOI: 10.1038/s41559-017-0458-2
Metrics:
See at:
Nature Ecology & Evolution | CNR IRIS | ISTI Repository | NARCIS | Croatian Scientific Bibliography - CROSBI | www.nature.com | Nature Ecology & Evolution | Nature Ecology & Evolution | CNR IRIS
2023
Other
Open Access
Community building con OpenAIRE CONNECT
Bardi A, Baglioni M
Le comunità di ricerca, le reti universitarie, le infrastrutture di ricerca mirano a massimizzare il loro impatto sulla ricerca e sulla società e a dotare i loro ricercatori di strumenti comuni, politiche e linee guida condivise per migliorare la qualità della ricerca. Tuttavia, spesso non è facile ottenere la visibilità che meritano nei confronti degli enti finanziatori o del personale di ricerca. Analizzando il panorama attuale è possibile identificare un insieme di attività strategiche: 1. Ampia diffusione di tutte le attività e dei risultati dei ricercatori sia all'interno che al di fuori della propria comunità; 2. Monitoraggio dei risultati della ricerca della comunità; 3. Promozione e monitoraggio dell'adozione delle pratiche di Open Science (ad es. dati FAIR e pubblicazione in Open Access); 4. Monitoraggio dell'aderenza alle politiche condivise e alle best practices del dominio; 5. Centralizzazione della fornitura di servizi condivisi per ridurre i costi e raggiungere un maggior numero di utenti (ad es. per programmi di formazione rivolti a responsabili della ricerca, amministratori, ricercatori, studenti). Queste attività non sono semplici da realizzare in modo sostenibile. Spesso, il monitoraggio dei risultati della ricerca viene fatto manualmente, richiedendo molto sforzo per comunicare con ogni membro della comunità (sia persone che organizzazioni), garantire la qualità e armonizzare i dati raccolti in modo che possano essere diffusi e/o analizzati. Un altro problema comune è monitorare l'adozione delle pratiche di pubblicazione Open Science dei ricercatori, identificare le lacune e preparare tutorial e formazione per supportarli. OpenAIRE, un'infrastruttura di comunicazione scientifica impegnata nella promozione dell'Open Science, sta collaborando con diverse alleanze di università (ad es. Aurora, EUT+, EUTOPIA, FIT FORTHEM), infrastrutture di ricerca (ad es. EMBRC, IPERION-HS, DARIAH) e comunità specifiche del dominio (ad es. scienze marine, neuroinformatica) per affrontare queste sfide. Dal punto di vista tecnico, OpenAIRE opera il servizio CONNECT (https://connect.openaire.eu), attraverso il quale una comunità può avere un gateway personalizzabile dove scoprire tutti i prodotti della ricerca della comunità tramite un unico punto di accesso e servizi per facilitare l'adozione e il monitoraggio delle pratiche di Open Science. Dal punto di vista della formazione, le collaborazioni ci danno l'opportunità di arricchire e scambiare materiale formativo, competenze e impostare una strategia di disseminazione congiunta per migliorare ulteriormente la visibilità all'interno delle comunità, della rete OpenAIRE e oltre. La demo presenterà uno dei gateway pubblici per mostrare tutte le funzionalità integrate disponibili agli utenti, fra cui: cercare i prodotti della ricerca, collegarli tra loro e con i progetti che li hanno finanziati, cercare repository Open Access per depositare qualsiasi tipo di prodotto della ricerca, l'integrazione con il servizio ORCID. Presenterà anche la dashboard di amministrazione che può essere utilizzata dai curatori della comunità per configurare il gateway in termini di contenuti e aspetto.
Bardi A, Baglioni M
Le comunità di ricerca, le reti universitarie, le infrastrutture di ricerca mirano a massimizzare il loro impatto sulla ricerca e sulla società e a dotare i loro ricercatori di strumenti comuni, politiche e linee guida condivise per migliorare la qualità della ricerca. Tuttavia, spesso non è facile ottenere la visibilità che meritano nei confronti degli enti finanziatori o del personale di ricerca. Analizzando il panorama attuale è possibile identificare un insieme di attività strategiche: 1. Ampia diffusione di tutte le attività e dei risultati dei ricercatori sia all'interno che al di fuori della propria comunità; 2. Monitoraggio dei risultati della ricerca della comunità; 3. Promozione e monitoraggio dell'adozione delle pratiche di Open Science (ad es. dati FAIR e pubblicazione in Open Access); 4. Monitoraggio dell'aderenza alle politiche condivise e alle best practices del dominio; 5. Centralizzazione della fornitura di servizi condivisi per ridurre i costi e raggiungere un maggior numero di utenti (ad es. per programmi di formazione rivolti a responsabili della ricerca, amministratori, ricercatori, studenti). Queste attività non sono semplici da realizzare in modo sostenibile. Spesso, il monitoraggio dei risultati della ricerca viene fatto manualmente, richiedendo molto sforzo per comunicare con ogni membro della comunità (sia persone che organizzazioni), garantire la qualità e armonizzare i dati raccolti in modo che possano essere diffusi e/o analizzati. Un altro problema comune è monitorare l'adozione delle pratiche di pubblicazione Open Science dei ricercatori, identificare le lacune e preparare tutorial e formazione per supportarli. OpenAIRE, un'infrastruttura di comunicazione scientifica impegnata nella promozione dell'Open Science, sta collaborando con diverse alleanze di università (ad es. Aurora, EUT+, EUTOPIA, FIT FORTHEM), infrastrutture di ricerca (ad es. EMBRC, IPERION-HS, DARIAH) e comunità specifiche del dominio (ad es. scienze marine, neuroinformatica) per affrontare queste sfide. Dal punto di vista tecnico, OpenAIRE opera il servizio CONNECT (https://connect.openaire.eu), attraverso il quale una comunità può avere un gateway personalizzabile dove scoprire tutti i prodotti della ricerca della comunità tramite un unico punto di accesso e servizi per facilitare l'adozione e il monitoraggio delle pratiche di Open Science. Dal punto di vista della formazione, le collaborazioni ci danno l'opportunità di arricchire e scambiare materiale formativo, competenze e impostare una strategia di disseminazione congiunta per migliorare ulteriormente la visibilità all'interno delle comunità, della rete OpenAIRE e oltre. La demo presenterà uno dei gateway pubblici per mostrare tutte le funzionalità integrate disponibili agli utenti, fra cui: cercare i prodotti della ricerca, collegarli tra loro e con i progetti che li hanno finanziati, cercare repository Open Access per depositare qualsiasi tipo di prodotto della ricerca, l'integrazione con il servizio ORCID. Presenterà anche la dashboard di amministrazione che può essere utilizzata dai curatori della comunità per configurare il gateway in termini di contenuti e aspetto.
See at:
CNR IRIS | zenodo.org | CNR IRIS
2023
Contribution to conference
Open Access
OpenAIRE CONNECT for research alliances
Malaguarnera G, Bardi A, Baglioni M, Kokogiannaki A
Research alliances like university networks or associations gather their members, with common or complementary backgrounds, to maximize their impact on research and society and empower their researchers with common tools, shared policies and guidelines to improve the quality of the research. Via the alliance, members and their affiliated researchers have more collaboration and funding opportunities. However, often it is not easy for an alliance to gain the deserved visibility towards funding organizations or the research staff. By analyzing the current landscape of research alliances it is possible to identify a set of strategic activities: - Wide dissemination of all activities and researchers' results within and beyond the alliance itself; - Tracking the research outputs of the members, especially those resulted from a collaboration among the members of the alliance - Promote Open Access and other Open Science practices (e.g. data sharing and Open Access publishing) to foster a more free circulation of knowledge within and beyond the researchers of the alliance, increase collaboration opportunities, and use it an accelerator towards the Sustainable Development Goals (SDGs) as suggested by UNESCO - Tracking the adherence to shared policies, domain best practices (for thematic alliances) and Open Science practices - Find sustainable common solutions for services shared among the members, reducing the costs and reaching a higher number of users (e.g. for training programs targeting research managers, administrators, researchers, students) Addressing those activities in a sustainable way is in some cases not straightforward. Often, the tracking of research outcome is done manually, requiring a lot of effort for communicating with the single members, ensuring the quality and harmonizing the collected data so that it can be disseminated and/or analyzed. Another common problem is tracking the uptake of Open Science publishing practices of the researchers, identifying gaps and preparing tutorials and training to help them. OpenAIRE, a scholarly communication infrastructure committed to the promotion of Open Science, is collaborating with several research alliances (Aurora, EUT+, EUTOPIA, FIT FORTHEM) to address those challenges. From the technical point of view, OpenAIRE provides to each alliance a customizable gateway where all research products of the members can be discovered via a single entry point and services to ease the adoption and tracking of Open Science practices (see https://connect.openaire.eu for the list of exiting gateways and more information). From the training point of view, the collaborations give us the opportunity to enrich and exchange training material, expertise, and set up a joint dissemination strategy to further improve the visibility within the alliances, the OpenAIRE network, and beyond.DOI: 10.5281/zenodo.8300745
DOI: 10.5281/zenodo.8300744
Project(s): FAIRCORE4EOSC
, EOSC Future , OpenAIRE Nexus
Metrics:
Malaguarnera G, Bardi A, Baglioni M, Kokogiannaki A
Research alliances like university networks or associations gather their members, with common or complementary backgrounds, to maximize their impact on research and society and empower their researchers with common tools, shared policies and guidelines to improve the quality of the research. Via the alliance, members and their affiliated researchers have more collaboration and funding opportunities. However, often it is not easy for an alliance to gain the deserved visibility towards funding organizations or the research staff. By analyzing the current landscape of research alliances it is possible to identify a set of strategic activities: - Wide dissemination of all activities and researchers' results within and beyond the alliance itself; - Tracking the research outputs of the members, especially those resulted from a collaboration among the members of the alliance - Promote Open Access and other Open Science practices (e.g. data sharing and Open Access publishing) to foster a more free circulation of knowledge within and beyond the researchers of the alliance, increase collaboration opportunities, and use it an accelerator towards the Sustainable Development Goals (SDGs) as suggested by UNESCO - Tracking the adherence to shared policies, domain best practices (for thematic alliances) and Open Science practices - Find sustainable common solutions for services shared among the members, reducing the costs and reaching a higher number of users (e.g. for training programs targeting research managers, administrators, researchers, students) Addressing those activities in a sustainable way is in some cases not straightforward. Often, the tracking of research outcome is done manually, requiring a lot of effort for communicating with the single members, ensuring the quality and harmonizing the collected data so that it can be disseminated and/or analyzed. Another common problem is tracking the uptake of Open Science publishing practices of the researchers, identifying gaps and preparing tutorials and training to help them. OpenAIRE, a scholarly communication infrastructure committed to the promotion of Open Science, is collaborating with several research alliances (Aurora, EUT+, EUTOPIA, FIT FORTHEM) to address those challenges. From the technical point of view, OpenAIRE provides to each alliance a customizable gateway where all research products of the members can be discovered via a single entry point and services to ease the adoption and tracking of Open Science practices (see https://connect.openaire.eu for the list of exiting gateways and more information). From the training point of view, the collaborations give us the opportunity to enrich and exchange training material, expertise, and set up a joint dissemination strategy to further improve the visibility within the alliances, the OpenAIRE network, and beyond.DOI: 10.5281/zenodo.8300745
DOI: 10.5281/zenodo.8300744
Project(s): FAIRCORE4EOSC
, EOSC Future , OpenAIRE Nexus Metrics:
See at:
ZENODO | ZENODO | CNR IRIS | ISTI Repository | zenodo.org | 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
not yet published
Conference article
Open Access
Exploring scientometrics with the OpenAIRE Graph: introducing the OpenAIRE Beginner's Kit
Mannocci A., Baglioni M.
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.
Mannocci A., Baglioni M.
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.
2020
Conference article
Open Access
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.DOI: 10.1007/978-3-030-54956-5_15
Project(s): OpenAIRE-Advance
Metrics:
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.DOI: 10.1007/978-3-030-54956-5_15
Project(s): OpenAIRE-Advance
Metrics:
See at:
ZENODO | zenodo.org | Lecture Notes in Computer Science | CNR IRIS | CNR IRIS | link.springer.com
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.
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
2017
Other
Restricted
OpenAIRE - OpenAIRE publishing APIs: specification and release plan
Manghi P, Bardi A, Baglioni M, Atzori C
The aim of this deliverable is to provide the specification of the software and the release plan for the OpenAIRE publishing APIsthat support third-party services at publishingmetadata about interlinked and packaged research productsin to the OpenAIRE Information Graph. The OpenAIRE publishing APIs supports the concept of "continuous publishing" in digital research settings where researchers conduct their activities in digital laboratories using ICT tools and services for processing and analysing research data. By using the OpenAIRE publishing APIs, a service/tool can automatically publish metadata on behalf of the researchers. The service/tool and its underlying infrastructure is responsible for keeping persistent identifiers, preserving the payload of the objects and the metadata.The service pushes metadata into OpenAIRE,the effect being: o the metadata record is immediately visible via the OpenAIRE search portal and APIs; o the metadata record will be cleaned and de-duplicated in a second stage according to the OpenAIRE content provision workflow described at https://www.openaire.eu/aggregation-and-contentprovision-workflows and http://doi.org/10.5281/zenodo.996006. Researchers benefit from a service that uses the OpenAIRE publishing APIs in several ways: o The service will support the generation of metadata to improve the FAIRness of the relative research products; o Researchers are relieved of the burden of depositing the products they want to publish in a repositoryexternaltotheirdigitallaboratory; o Researchers can choose to publish research products at any step of their research activity. The full specification of the APIs are published as a wiki and available at https://support.d4science.org/projects/openaire-connect-wiki/wiki/D4_5.Project(s): OpenAIRE-Connect
Manghi P, Bardi A, Baglioni M, Atzori C
The aim of this deliverable is to provide the specification of the software and the release plan for the OpenAIRE publishing APIsthat support third-party services at publishingmetadata about interlinked and packaged research productsin to the OpenAIRE Information Graph. The OpenAIRE publishing APIs supports the concept of "continuous publishing" in digital research settings where researchers conduct their activities in digital laboratories using ICT tools and services for processing and analysing research data. By using the OpenAIRE publishing APIs, a service/tool can automatically publish metadata on behalf of the researchers. The service/tool and its underlying infrastructure is responsible for keeping persistent identifiers, preserving the payload of the objects and the metadata.The service pushes metadata into OpenAIRE,the effect being: o the metadata record is immediately visible via the OpenAIRE search portal and APIs; o the metadata record will be cleaned and de-duplicated in a second stage according to the OpenAIRE content provision workflow described at https://www.openaire.eu/aggregation-and-contentprovision-workflows and http://doi.org/10.5281/zenodo.996006. Researchers benefit from a service that uses the OpenAIRE publishing APIs in several ways: o The service will support the generation of metadata to improve the FAIRness of the relative research products; o Researchers are relieved of the burden of depositing the products they want to publish in a repositoryexternaltotheirdigitallaboratory; o Researchers can choose to publish research products at any step of their research activity. The full specification of the APIs are published as a wiki and available at https://support.d4science.org/projects/openaire-connect-wiki/wiki/D4_5.Project(s): OpenAIRE-Connect
See at:
CNR IRIS | CNR IRIS | support.d4science.org
2017
Other
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OpeanAIRE - Catch-All Notification BrokerBack-end: specification and release plan
Atzori C, Baglioni M, Bardi A, Manghi P
The aim of this deliverable is to present the functional requirements, a specification of the software,and a release plan for the deployment of the OpenAIRE-connect Catch-All Notification Broker Service ( CAB Service ). The CAB Service will connect all types of research artefacts providers(institutional repositories,publishers, data, repositories,and CRIS systems) and allow them to subscribe and be notified by OpenAIRE of events interesting to them. These notifications will comprise: 1) the existence of artefacts of interest to the providers (which may pertain their collection) 2)the existence of links from artefacts in their collection to other artefacts. The CAB Service will extend OpenAIRE's notification brokering services, which serves literature repositories, and will broaden the content provider base with the ones that serve specific research communities. Content provider managers will be allowed to register as consumers of the service, set and test the service (preview the results of the service over some subscriptions), to commit their subscriptions, and finally to manage their history of notifications overtime. The broker service will be tested in two bata releases and changed and/or updated following the requirements obtained from the betas. The deliverable is published as a wiki and is available at https://support.d4science.org/projects/openaire-connect-wiki/wiki/D5_1.Project(s): OpenAIRE-Connect
Atzori C, Baglioni M, Bardi A, Manghi P
The aim of this deliverable is to present the functional requirements, a specification of the software,and a release plan for the deployment of the OpenAIRE-connect Catch-All Notification Broker Service ( CAB Service ). The CAB Service will connect all types of research artefacts providers(institutional repositories,publishers, data, repositories,and CRIS systems) and allow them to subscribe and be notified by OpenAIRE of events interesting to them. These notifications will comprise: 1) the existence of artefacts of interest to the providers (which may pertain their collection) 2)the existence of links from artefacts in their collection to other artefacts. The CAB Service will extend OpenAIRE's notification brokering services, which serves literature repositories, and will broaden the content provider base with the ones that serve specific research communities. Content provider managers will be allowed to register as consumers of the service, set and test the service (preview the results of the service over some subscriptions), to commit their subscriptions, and finally to manage their history of notifications overtime. The broker service will be tested in two bata releases and changed and/or updated following the requirements obtained from the betas. The deliverable is published as a wiki and is available at https://support.d4science.org/projects/openaire-connect-wiki/wiki/D5_1.Project(s): OpenAIRE-Connect
See at:
CNR IRIS | CNR IRIS | support.d4science.org
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
2013
Journal article
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How you move reveals who you are: Understanding human behavior by analyzing trajectory data
Renso C, Baglioni M, Fernandes De Macêdo Ja, 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, vol. 37 (issue 2), pp. 331-362
DOI: 10.1007/s10115-012-0511-z
Metrics:
Renso C, Baglioni M, Fernandes De Macêdo Ja, 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, vol. 37 (issue 2), pp. 331-362
DOI: 10.1007/s10115-012-0511-z
Metrics:
See at:
Knowledge and Information Systems | CNR IRIS | CNR IRIS | link.springer.com
2021
Journal article
Open Access
We can make a better use of ORCID: five observed misapplications
Baglioni M, Manghi P, Mannocci A, Bardi A
Since 2012, the "Open Researcher and Contributor ID" organisation (ORCID) has been successfully running a worldwide registry, with the aim of "providing a unique, persistent identifier for individuals to use as they engage in research, scholarship, and innovation activities". Any service in the scholarly communication ecosystem (e.g., publishers, repositories, CRIS systems, etc.) can contribute to a non-ambiguous scholarly record by including, during metadata deposition, referrals to iDs in the ORCID registry. The OpenAIRE Research Graph is a scholarly knowledge graph that aggregates both records from the ORCID registry and publication records with ORCID referrals from publishers and repositories worldwide to yield research impact monitoring and Open Science statistics. Graph data analytics revealed "anomalies" due to ORCID registry "misapplications", caused by wrong ORCID referrals and misexploitation of the ORCID registry. Albeit these affect just a minority of ORCID records, they inevitably affect the quality of the ORCID infrastructure and may fuel the rise of detractors and scepticism about the service. In this paper, we classify and qualitatively document such misapplications, identifying five ORCID registrant-related and ORCID referral-related anomalies to raise awareness among ORCID users. We describe the current countermeasures taken by ORCID and, where applicable, provide recommendations. Finally, we elaborate on the importance of a community-steered Open Science infrastructure and the benefits this approach has brought and may bring to ORCID.Source: DATA SCIENCE JOURNAL, vol. 20 (issue 38), pp. 1-12
DOI: 10.5334/dsj-2021-038
Project(s): OpenAIRE-Connect
Metrics:
Baglioni M, Manghi P, Mannocci A, Bardi A
Since 2012, the "Open Researcher and Contributor ID" organisation (ORCID) has been successfully running a worldwide registry, with the aim of "providing a unique, persistent identifier for individuals to use as they engage in research, scholarship, and innovation activities". Any service in the scholarly communication ecosystem (e.g., publishers, repositories, CRIS systems, etc.) can contribute to a non-ambiguous scholarly record by including, during metadata deposition, referrals to iDs in the ORCID registry. The OpenAIRE Research Graph is a scholarly knowledge graph that aggregates both records from the ORCID registry and publication records with ORCID referrals from publishers and repositories worldwide to yield research impact monitoring and Open Science statistics. Graph data analytics revealed "anomalies" due to ORCID registry "misapplications", caused by wrong ORCID referrals and misexploitation of the ORCID registry. Albeit these affect just a minority of ORCID records, they inevitably affect the quality of the ORCID infrastructure and may fuel the rise of detractors and scepticism about the service. In this paper, we classify and qualitatively document such misapplications, identifying five ORCID registrant-related and ORCID referral-related anomalies to raise awareness among ORCID users. We describe the current countermeasures taken by ORCID and, where applicable, provide recommendations. Finally, we elaborate on the importance of a community-steered Open Science infrastructure and the benefits this approach has brought and may bring to ORCID.Source: DATA SCIENCE JOURNAL, vol. 20 (issue 38), pp. 1-12
DOI: 10.5334/dsj-2021-038
Project(s): OpenAIRE-Connect
Metrics:
See at:
datascience.codata.org | CNR IRIS | ISTI Repository | CNR IRIS