Typology
operator:
and / or
Language
operator:
and / or
Date
operator:
and / or
Rights
operator:
and / or
2020
Report
Open Access
AIMH research activities 2020
Aloia N., Amato G., Bartalesi V., Benedetti F., Bolettieri P., Carrara F., Casarosa V., Ciampi L., Concordia C., Corbara S., Esuli A., Falchi F., Gennaro C., Lagani G., Massoli F. V., Meghini C., Messina N., Metilli D., Molinari A., Moreo A., Nardi A., Pedrotti A., Pratelli N., Rabitti F., Savino P., Sebastiani F., Thanos C., Trupiano L., Vadicamo L., Vairo C.
Annual Report of the Artificial Intelligence for Media and Humanities laboratory (AIMH) research activities in 2020.Source: ISTI Annual Report, ISTI-2020-AR/001, 2020
DOI: 10.32079/isti-ar-2020/001
Metrics:
Aloia N., Amato G., Bartalesi V., Benedetti F., Bolettieri P., Carrara F., Casarosa V., Ciampi L., Concordia C., Corbara S., Esuli A., Falchi F., Gennaro C., Lagani G., Massoli F. V., Meghini C., Messina N., Metilli D., Molinari A., Moreo A., Nardi A., Pedrotti A., Pratelli N., Rabitti F., Savino P., Sebastiani F., Thanos C., Trupiano L., Vadicamo L., Vairo C.
Annual Report of the Artificial Intelligence for Media and Humanities laboratory (AIMH) research activities in 2020.Source: ISTI Annual Report, ISTI-2020-AR/001, 2020
DOI: 10.32079/isti-ar-2020/001
Metrics:
See at:
ISTI Repository 
| CNR ExploRA
2021
Contribution to conference
Open Access
The Hypermedia Dante Network Project
Tomazzoli G., Livraghi L. M. G., Metilli D., Pratelli N., Bartalesi V.
In this paper, we present the Hypermedia Dante Network (HDN) project. First, we briefly introduce the relevant state of the art on Dante's commentaries and their digital representation, and we outline the project goals. In the main section, we present the core features of the HDN ontology, an evolution of the DanteSources ontology that aims at representing knowledge about Dante's primary sources as they are identified by a vast range of commentaries. Then, we describe the tool that has been developed to process Dante's commentaries and populate the HDN ontology. Finally, we comment on the project's usability and possible outcomes for both scholars and common users.Source: AIUCD 2021 - DH per la società: e-guaglianza, partecipazione, diritti e valori nell'era digitale, pp. 269–274, Pisa, 19-22/01/2021
Tomazzoli G., Livraghi L. M. G., Metilli D., Pratelli N., Bartalesi V.
In this paper, we present the Hypermedia Dante Network (HDN) project. First, we briefly introduce the relevant state of the art on Dante's commentaries and their digital representation, and we outline the project goals. In the main section, we present the core features of the HDN ontology, an evolution of the DanteSources ontology that aims at representing knowledge about Dante's primary sources as they are identified by a vast range of commentaries. Then, we describe the tool that has been developed to process Dante's commentaries and populate the HDN ontology. Finally, we comment on the project's usability and possible outcomes for both scholars and common users.Source: AIUCD 2021 - DH per la società: e-guaglianza, partecipazione, diritti e valori nell'era digitale, pp. 269–274, Pisa, 19-22/01/2021
See at:
aiucd2021.labcd.unipi.it | ISTI Repository | CNR ExploRA
2023
Conference article
Open Access
A web tool to create and visualise semantic story maps
Bartalesi V., Lenzi E., Pratelli N.
This paper presents the Story Map Building and Visualizing Tool (SMBVT), a sofware that allows users to create and visualise semantic story maps using a user-friendly web interface. The tool uses Wikidata as external reference knowledge base and exploits Semantic Web technologies in the back-end system to represent stories modelled on the Narrative ontology, a CRM-based vocabulary for representing narratives. SMBVT is entirely open-source and accessible afer free registration.Source: Text2Story 2023 - Sixth Workshop on Narrative Extraction From Texts, pp. 163–169, Dublin, Ireland, 02/04/2023
Bartalesi V., Lenzi E., Pratelli N.
This paper presents the Story Map Building and Visualizing Tool (SMBVT), a sofware that allows users to create and visualise semantic story maps using a user-friendly web interface. The tool uses Wikidata as external reference knowledge base and exploits Semantic Web technologies in the back-end system to represent stories modelled on the Narrative ontology, a CRM-based vocabulary for representing narratives. SMBVT is entirely open-source and accessible afer free registration.Source: Text2Story 2023 - Sixth Workshop on Narrative Extraction From Texts, pp. 163–169, Dublin, Ireland, 02/04/2023
See at:
ceur-ws.org | ISTI Repository | CNR ExploRA
2023
Contribution to conference
Open Access
Towards digital twins of territories through semantic story maps
Bartalesi V., Coro G., Lenzi E., Pratelli N., Pagano P.
Digital maps greatly support storytelling about territories, especially when enriched with data describing cultural, societal, and ecological aspects, conveying emotional messages that describe the territory as a whole. Story maps are interactive online digital narratives that can describe a territory beyond its map by enriching the map with text, pictures, videos, and other multimedia information. This paper outlines how online story maps can fill the gap between a map and a territory in narratives to create a digital twin of different territories as inter-connected semantic storiesSource: BUILD-IT 2023, pp. 41–45, Rome, Italy, 19/10/2023-20/10/2023
Bartalesi V., Coro G., Lenzi E., Pratelli N., Pagano P.
Digital maps greatly support storytelling about territories, especially when enriched with data describing cultural, societal, and ecological aspects, conveying emotional messages that describe the territory as a whole. Story maps are interactive online digital narratives that can describe a territory beyond its map by enriching the map with text, pictures, videos, and other multimedia information. This paper outlines how online story maps can fill the gap between a map and a territory in narratives to create a digital twin of different territories as inter-connected semantic storiesSource: BUILD-IT 2023, pp. 41–45, Rome, Italy, 19/10/2023-20/10/2023
See at:
inm.cnr.it | ISTI Repository | CNR ExploRA
2021
Software
Unknown
HDN Annotation Tool
Bartalesi Lenzi V., Pratelli N., Metilli D., Meghini C.
To facilitate the process of populating the ontology developed within the Hypermedia Dante Network (HDN) project (PRIN 2020-2023), we implemented a semi-automatic tool called HDN Annotation Tool. The tool supports scholars to build a knowledge base of the primary sources of Dante Alighieri's Divine Comedy. The tool was developed using a Python backend with the Django framework, and a frontend built with HTML5, JavaScript, and the Bootstrap library. It takes as input the JSON file, where the knowledge automatically extracted from the corpus of the Dartmouth Dante Project (DDP) is stored and shows the relevant information in the corresponding fields of the tool interface. After analyzing the commentaries of the DDP, scholars use the interface of the tool to insert knowledge about primary sources. The tool is accessible through the HDN-Lab, which is the Virtual Research Environment (VRE) of the project, hosted on the D4Science infrastructure.
Bartalesi Lenzi V., Pratelli N., Metilli D., Meghini C.
To facilitate the process of populating the ontology developed within the Hypermedia Dante Network (HDN) project (PRIN 2020-2023), we implemented a semi-automatic tool called HDN Annotation Tool. The tool supports scholars to build a knowledge base of the primary sources of Dante Alighieri's Divine Comedy. The tool was developed using a Python backend with the Django framework, and a frontend built with HTML5, JavaScript, and the Bootstrap library. It takes as input the JSON file, where the knowledge automatically extracted from the corpus of the Dartmouth Dante Project (DDP) is stored and shows the relevant information in the corresponding fields of the tool interface. After analyzing the commentaries of the DDP, scholars use the interface of the tool to insert knowledge about primary sources. The tool is accessible through the HDN-Lab, which is the Virtual Research Environment (VRE) of the project, hosted on the D4Science infrastructure.
See at: dante.d4science.org | CNR ExploRA
2021
Conference article
Open Access
The IMAGO project: towards a knowledge base of medieval and renaissance geographical works
Bartalesi Lenzi V., Pratelli N.
The image of the world created by the Medieval and Renaissance culture was crucial to the development of Western thought in European history. To the best of our knowledge Medieval and Renaissance geographical works have not been studied using digital methods. The three years (2020-2023) Italian National research project IMAGO - Index Medii Aevi Geographiae Operum - aims at providing a systematic overview of this literature using Semantic Web technologies. As the first step to develop tools to support scholars in creating, evolving and consulting a knowledge base (KB) of the geographical works, we created an OWL 2 DL ontology. Following the re-use logic and to maximize the interoperability, we developed the ontology as an extension of two reference ontologies, that is the CIDOC CRM vocabulary and its extension FRBRoo, including its in-progress reformulation, LRMoo. In this paper, we present the project, the ontology and the tool to populate it that we developed. Furthermore, we present a preliminary study to map the works collected in the IMAGO KB and the manuscripts stored in the KB of the Mapping Manuscript Migrations project.Source: SWODCH 2021 - International Joint Workshop on Semantic Web and Ontology Design for Cultural Heritage, Bolzano, 20-21/09/2021
Bartalesi Lenzi V., Pratelli N.
The image of the world created by the Medieval and Renaissance culture was crucial to the development of Western thought in European history. To the best of our knowledge Medieval and Renaissance geographical works have not been studied using digital methods. The three years (2020-2023) Italian National research project IMAGO - Index Medii Aevi Geographiae Operum - aims at providing a systematic overview of this literature using Semantic Web technologies. As the first step to develop tools to support scholars in creating, evolving and consulting a knowledge base (KB) of the geographical works, we created an OWL 2 DL ontology. Following the re-use logic and to maximize the interoperability, we developed the ontology as an extension of two reference ontologies, that is the CIDOC CRM vocabulary and its extension FRBRoo, including its in-progress reformulation, LRMoo. In this paper, we present the project, the ontology and the tool to populate it that we developed. Furthermore, we present a preliminary study to map the works collected in the IMAGO KB and the manuscripts stored in the KB of the Mapping Manuscript Migrations project.Source: SWODCH 2021 - International Joint Workshop on Semantic Web and Ontology Design for Cultural Heritage, Bolzano, 20-21/09/2021
See at:
ceur-ws.org | ISTI Repository | CNR ExploRA
2021
Report
Open Access
AIMH research activities 2021
Aloia N., Amato G., Bartalesi V., Benedetti F., Bolettieri P., Cafarelli D., Carrara F., Casarosa V., Coccomini D., Ciampi L., Concordia C., Corbara S., Di Benedetto M., Esuli A., Falchi F., Gennaro C., Lagani G., Massoli F. V., Meghini C., Messina N., Metilli D., Molinari A., Moreo A., Nardi A., Pedrotti A., Pratelli N., Rabitti F., Savino P., Sebastiani F., Sperduti G., Thanos C., Trupiano L., Vadicamo L., Vairo C.
The Artificial Intelligence for Media and Humanities laboratory (AIMH) has the mission to investigate and advance the state of the art in the Artificial Intelligence field, specifically addressing applications to digital media and digital humanities, and taking also into account issues related to scalability. This report summarize the 2021 activities of the research group.Source: ISTI Annual Report, ISTI-2021-AR/003, pp.1–34, 2021
DOI: 10.32079/isti-ar-2021/003
Metrics:
Aloia N., Amato G., Bartalesi V., Benedetti F., Bolettieri P., Cafarelli D., Carrara F., Casarosa V., Coccomini D., Ciampi L., Concordia C., Corbara S., Di Benedetto M., Esuli A., Falchi F., Gennaro C., Lagani G., Massoli F. V., Meghini C., Messina N., Metilli D., Molinari A., Moreo A., Nardi A., Pedrotti A., Pratelli N., Rabitti F., Savino P., Sebastiani F., Sperduti G., Thanos C., Trupiano L., Vadicamo L., Vairo C.
The Artificial Intelligence for Media and Humanities laboratory (AIMH) has the mission to investigate and advance the state of the art in the Artificial Intelligence field, specifically addressing applications to digital media and digital humanities, and taking also into account issues related to scalability. This report summarize the 2021 activities of the research group.Source: ISTI Annual Report, ISTI-2021-AR/003, pp.1–34, 2021
DOI: 10.32079/isti-ar-2021/003
Metrics:
See at:
ISTI Repository | CNR ExploRA
2022
Software
Unknown
Story Map Building and Visualising Tool (SMBVT)
Lenzi E., Bartalesi V., Pratelli N., Coro G., Pagano P.
In the context of the MOVING (MOuntain Valorisation through INterconnectedness and Green growth) project, we released an open-source software - the MOVING Story Map Building and Visualization Tool (SMBVT) - that allows users to create and visualise story maps within a collaborative environment and using a user-friendly Web interface. The tool uses Semantic Web technologies and the Narrative Ontology to represent the stories of the MOVING mountain Value Chains. The MOVING community access SMBVT through The MOVING story map Virtual Research Environment and creates the events of the story. For each event, the user can add: a title, a textual description, start and end dates, the geographic coordinates, a media object (i.e. a video or image), notes, and digital objects. The tool takes Wikidata as reference KB and assigns Wikidata Internationalized Resource Identifiers (IRIs) to the story components (i.e. the entities that take part in an event). All the knowledge collected by SMBVT is stored in a JSON Postgres DB. When a story is completed, the tool automatically creates the corresponding visualisation using StoryMapJS library and makes available a corresponding URL that can be freely shared. Finally, SMBVT saves the collected knowledge as a Web Ontology Language (OWL) graph and publishes it as a Linked Open Data.Project(s): "CMG Collaborative Research": A Systematic Approach to Large Amplitude Internal Wave Dynamics: An Integrated Mathematical, Observational, and Remote Sensing Model, Blue Cloud
, MOVING
Lenzi E., Bartalesi V., Pratelli N., Coro G., Pagano P.
In the context of the MOVING (MOuntain Valorisation through INterconnectedness and Green growth) project, we released an open-source software - the MOVING Story Map Building and Visualization Tool (SMBVT) - that allows users to create and visualise story maps within a collaborative environment and using a user-friendly Web interface. The tool uses Semantic Web technologies and the Narrative Ontology to represent the stories of the MOVING mountain Value Chains. The MOVING community access SMBVT through The MOVING story map Virtual Research Environment and creates the events of the story. For each event, the user can add: a title, a textual description, start and end dates, the geographic coordinates, a media object (i.e. a video or image), notes, and digital objects. The tool takes Wikidata as reference KB and assigns Wikidata Internationalized Resource Identifiers (IRIs) to the story components (i.e. the entities that take part in an event). All the knowledge collected by SMBVT is stored in a JSON Postgres DB. When a story is completed, the tool automatically creates the corresponding visualisation using StoryMapJS library and makes available a corresponding URL that can be freely shared. Finally, SMBVT saves the collected knowledge as a Web Ontology Language (OWL) graph and publishes it as a Linked Open Data.Project(s): "CMG Collaborative Research": A Systematic Approach to Large Amplitude Internal Wave Dynamics: An Integrated Mathematical, Observational, and Remote Sensing Model, Blue Cloud
, MOVING See at: github.com | CNR ExploRA
2022
Software
Unknown
IMAGO Annotation Tool
Pratelli N., Bartalesi V., Lenzi E.
To populate the ontology developed within the Index Medii Aevi Geographiae Operum (IMAGO) -- Italian National Research Project (2020-23), we developed a semi-automatic Web tool, called IMAGO Annotation Tool, to allow scholars to insert knowledge about Medieval and Reinassance works through a user-friendly interface. The tool was created to reduce the time to insert knowledge and to avoid the insertion of mistakes thanks to the use of predefined lists of works, authors, libraries, places, geographic coordinates, and literary genres. Each field of the interface maps a class of the IMAGO ontology. The frontend interface is built using HTML5, CSS3, JavaScript, and the Bootstrap library, using a Python backend, e.i., a Django framework and a PostgreSQL DB. Once the data about a work is inserted through the tool interface, this is encoded as an OWL knowledge base and stored in a triple store. The data is first exported to a JSON object. Indeed our software uses a JSON schema to represent the data, structured according to the IMAGO ontology classes. The JSON object is processed by Java software, which transforms it into an OWL graph encoded in RDF/XML and Turtle formats. This software carries out its task by relying on the Apache Jena library. The graph is finally stored in a Fuseki triple store, and it can be queried through a SPARQL endpoint.
Pratelli N., Bartalesi V., Lenzi E.
To populate the ontology developed within the Index Medii Aevi Geographiae Operum (IMAGO) -- Italian National Research Project (2020-23), we developed a semi-automatic Web tool, called IMAGO Annotation Tool, to allow scholars to insert knowledge about Medieval and Reinassance works through a user-friendly interface. The tool was created to reduce the time to insert knowledge and to avoid the insertion of mistakes thanks to the use of predefined lists of works, authors, libraries, places, geographic coordinates, and literary genres. Each field of the interface maps a class of the IMAGO ontology. The frontend interface is built using HTML5, CSS3, JavaScript, and the Bootstrap library, using a Python backend, e.i., a Django framework and a PostgreSQL DB. Once the data about a work is inserted through the tool interface, this is encoded as an OWL knowledge base and stored in a triple store. The data is first exported to a JSON object. Indeed our software uses a JSON schema to represent the data, structured according to the IMAGO ontology classes. The JSON object is processed by Java software, which transforms it into an OWL graph encoded in RDF/XML and Turtle formats. This software carries out its task by relying on the Apache Jena library. The graph is finally stored in a Fuseki triple store, and it can be queried through a SPARQL endpoint.
See at: imagoarchive.it | CNR ExploRA
2022
Conference article
Open Access
A knowledge base of medieval and renaissance geographic Latin works
Bartalesi V., Pratelli N., Lenzi E.
The geography of the world created during the Middle Ages and Renaissance (VI-XV centuries) was crucial to the development of Western thought in the European history. Until now, to the best of our knowledge, Medieval and Renaissance geographic Latin literature has not been studied using digital methods. The Italian National research project IMAGO - Index Medii Aevi Geographiae Operum - (2020-2023) aims at providing a systematic overview of this literature using Semantic Web technologies and the Linked Open Data paradigm. As the first step to develop tools to support scholars in creating, evolving and consulting a knowledge base (KB) of the geographic works, we created an OWL 2 DL ontology. To maximize its interoperability, we developed the ontology as an extension of two reference vocabularies: the CIDOC CRM and FRBRoo (including its in-progress reformulation LRMoo). In this paper, we briefly present the project, the ontology, and the automatic and semi-automatic tools we developed to populate it. The final aim of the project is the creation of a Web application allowing scholars to freely access and visualise the data collected in the IMAGO knowledge base.Source: IRCDL 2022 - 18th Italian Research Conference on Digital Libraries, Padua, Italy, 24-25/02/2022
Bartalesi V., Pratelli N., Lenzi E.
The geography of the world created during the Middle Ages and Renaissance (VI-XV centuries) was crucial to the development of Western thought in the European history. Until now, to the best of our knowledge, Medieval and Renaissance geographic Latin literature has not been studied using digital methods. The Italian National research project IMAGO - Index Medii Aevi Geographiae Operum - (2020-2023) aims at providing a systematic overview of this literature using Semantic Web technologies and the Linked Open Data paradigm. As the first step to develop tools to support scholars in creating, evolving and consulting a knowledge base (KB) of the geographic works, we created an OWL 2 DL ontology. To maximize its interoperability, we developed the ontology as an extension of two reference vocabularies: the CIDOC CRM and FRBRoo (including its in-progress reformulation LRMoo). In this paper, we briefly present the project, the ontology, and the automatic and semi-automatic tools we developed to populate it. The final aim of the project is the creation of a Web application allowing scholars to freely access and visualise the data collected in the IMAGO knowledge base.Source: IRCDL 2022 - 18th Italian Research Conference on Digital Libraries, Padua, Italy, 24-25/02/2022
See at:
ceur-ws.org | ISTI Repository | ISTI Repository | CNR ExploRA
2022
Report
Open Access
AIMH research activities 2022
Aloia N., Amato G., Bartalesi V., Benedetti F., Bolettieri P., Cafarelli D., Carrara F., Casarosa V., Ciampi L., Coccomini D. A., Concordia C., Corbara S., Di Benedetto M., Esuli A., Falchi F., Gennaro C., Lagani G., Lenzi E., Meghini C., Messina N., Metilli D., Molinari A., Moreo A., Nardi A., Pedrotti A., Pratelli N., Rabitti F., Savino P., Sebastiani F., Sperduti G., Thanos C., Trupiano L., Vadicamo L., Vairo C.
The Artificial Intelligence for Media and Humanities laboratory (AIMH) has the mission to investigate and advance the state of the art in the Artificial Intelligence field, specifically addressing applications to digital media and digital humanities, and taking also into account issues related to scalability. This report summarize the 2022 activities of the research group.Source: ISTI Annual reports, 2022
DOI: 10.32079/isti-ar-2022/002
Metrics:
Aloia N., Amato G., Bartalesi V., Benedetti F., Bolettieri P., Cafarelli D., Carrara F., Casarosa V., Ciampi L., Coccomini D. A., Concordia C., Corbara S., Di Benedetto M., Esuli A., Falchi F., Gennaro C., Lagani G., Lenzi E., Meghini C., Messina N., Metilli D., Molinari A., Moreo A., Nardi A., Pedrotti A., Pratelli N., Rabitti F., Savino P., Sebastiani F., Sperduti G., Thanos C., Trupiano L., Vadicamo L., Vairo C.
The Artificial Intelligence for Media and Humanities laboratory (AIMH) has the mission to investigate and advance the state of the art in the Artificial Intelligence field, specifically addressing applications to digital media and digital humanities, and taking also into account issues related to scalability. This report summarize the 2022 activities of the research group.Source: ISTI Annual reports, 2022
DOI: 10.32079/isti-ar-2022/002
Metrics:
See at:
ISTI Repository | CNR ExploRA
2023
Journal article
Open Access
From unstructured texts to semantic story maps
Bartalesi V., Coro G., Lenzi E., Pagano P., Pratelli N.
Digital maps greatly support storytelling about territories, especially when enriched with data describing cultural, societal, and ecological aspects, conveying emotional messages that describe the territory as a whole. Story maps are interactive online digital narratives that can describe a territory beyond its map by enriching the map with text, pictures, videos, and other multimedia information. This paper presents a semi-automatic workflow to produce story maps from textual documents containing territory data. An expert first assembles one territory-contextual document containing text and images. Then, automatic processes use natural language processing and Wikidata services to (i) extract key concepts (entities) and geospatial coordinates associated with the territory, (ii) assemble a logically-ordered sequence of enriched story-map events, and (iii) openly publish online story maps and an interoperable Linked Open Data semantic knowledge base for event exploration and inter-story correlation analyses. Our workflow uses an Open Science-oriented methodology to publish all processes and data. Through our workflow, we produced story maps for the value chains and territories of 23 rural European areas of 16 countries. Through numerical evaluation, we demonstrated that territory experts considered the story maps effective in describing their territories, and appropriate for communicating with citizens and stakeholders.Source: International journal of digital earth (Online) 16 (2023): 234–250. doi:10.1080/17538947.2023.2168774
DOI: 10.1080/17538947.2023.2168774
Project(s): MOVING
Metrics:
Bartalesi V., Coro G., Lenzi E., Pagano P., Pratelli N.
Digital maps greatly support storytelling about territories, especially when enriched with data describing cultural, societal, and ecological aspects, conveying emotional messages that describe the territory as a whole. Story maps are interactive online digital narratives that can describe a territory beyond its map by enriching the map with text, pictures, videos, and other multimedia information. This paper presents a semi-automatic workflow to produce story maps from textual documents containing territory data. An expert first assembles one territory-contextual document containing text and images. Then, automatic processes use natural language processing and Wikidata services to (i) extract key concepts (entities) and geospatial coordinates associated with the territory, (ii) assemble a logically-ordered sequence of enriched story-map events, and (iii) openly publish online story maps and an interoperable Linked Open Data semantic knowledge base for event exploration and inter-story correlation analyses. Our workflow uses an Open Science-oriented methodology to publish all processes and data. Through our workflow, we produced story maps for the value chains and territories of 23 rural European areas of 16 countries. Through numerical evaluation, we demonstrated that territory experts considered the story maps effective in describing their territories, and appropriate for communicating with citizens and stakeholders.Source: International journal of digital earth (Online) 16 (2023): 234–250. doi:10.1080/17538947.2023.2168774
DOI: 10.1080/17538947.2023.2168774
Project(s): MOVING
Metrics:
See at:
ISTI Repository | ISTI Repository | www.tandfonline.com | CNR ExploRA
2022
Conference article
Open Access
A geographical extension for NOnt ontology
Pratelli N.
Digital Libraries (DLs) are full of narratives. Besides its richness, DLs services often retrieve narrative components, but not the narratives as a whole. To formally represent this knowledge and to create and visualize narratives the Digital Humanities group of ISTI-CNR has developed the Narrative Ontology (NOnt) and the Narrative Building and Visualising Tool (NBVT). In this context, my research aims to investigate the possibility to introduce the geospatial dimension of narratives in NOnt. Moreover, my research aims to extend the functionalities of NBVT to enrich the narratives with geospatial information. As a case study, I have chosen to create narratives about mountain ecosystems and economic value chains produced within the Mountain Valorization through Interconnectedness and Green Growth (MOVING) European project (2020-2023). Currently, my research is still at an early stage and I have started to conduct a state-of-the-art study of the geospatial and spatiotemporal RDF/S representation techniques. Eventually, I will evaluate the extension of NOnt.Source: TPDL-WS-DC 2022 - Workshops and Doctoral Consortium at TPDL 2022, pp. 126–133, Padua, Italy, 20/09/2022
Pratelli N.
Digital Libraries (DLs) are full of narratives. Besides its richness, DLs services often retrieve narrative components, but not the narratives as a whole. To formally represent this knowledge and to create and visualize narratives the Digital Humanities group of ISTI-CNR has developed the Narrative Ontology (NOnt) and the Narrative Building and Visualising Tool (NBVT). In this context, my research aims to investigate the possibility to introduce the geospatial dimension of narratives in NOnt. Moreover, my research aims to extend the functionalities of NBVT to enrich the narratives with geospatial information. As a case study, I have chosen to create narratives about mountain ecosystems and economic value chains produced within the Mountain Valorization through Interconnectedness and Green Growth (MOVING) European project (2020-2023). Currently, my research is still at an early stage and I have started to conduct a state-of-the-art study of the geospatial and spatiotemporal RDF/S representation techniques. Eventually, I will evaluate the extension of NOnt.Source: TPDL-WS-DC 2022 - Workshops and Doctoral Consortium at TPDL 2022, pp. 126–133, Padua, Italy, 20/09/2022
See at:
ceur-ws.org | ISTI Repository | CNR ExploRA
2023
Journal article
Open Access
A roadmap for craft understanding, education, training, and preservation
Zabulis X., Partarakis N., Demeridou I., Doulgeraki P., Zidianakis E., Argyros A., Theodoridou M., Marketakis Y., Meghini C., Bartalesi V., Pratelli N., Holz C., Streli P., Meier M., Seidler M. K., Werup L., Sichani P. F., Manitsaris S., Senteri G., Dubois A., Ringas C., Ziova A., Tasiopoulou E., Kaplanidi D., Arnaud D., Hee P., Canavate G., Benvenuti M. A., Krivokapic J.
A roadmap is proposed that defines a systematic approach for craft preservation and its evaluation. The proposed roadmap aims to deepen craft understanding so that blueprints of appropriate tools that support craft documentation, education, and training can be designed while achieving preservation through the stimulation and diversification of practitioner income. In addition to this roadmap, an evaluation strategy is proposed to validate the efficacy of the developed results and provide a benchmark for the efficacy of craft preservation approaches. The proposed contribution aims at the catalyzation of craft education and training with digital aids, widening access and engagement to crafts, economizing learning, increasing exercisability, and relaxing remoteness constraints in craft learning.Source: Heritage (Basel) Online 6 (2023): 5305–5328. doi:10.3390/heritage6070280
DOI: 10.3390/heritage6070280
Metrics:
Zabulis X., Partarakis N., Demeridou I., Doulgeraki P., Zidianakis E., Argyros A., Theodoridou M., Marketakis Y., Meghini C., Bartalesi V., Pratelli N., Holz C., Streli P., Meier M., Seidler M. K., Werup L., Sichani P. F., Manitsaris S., Senteri G., Dubois A., Ringas C., Ziova A., Tasiopoulou E., Kaplanidi D., Arnaud D., Hee P., Canavate G., Benvenuti M. A., Krivokapic J.
A roadmap is proposed that defines a systematic approach for craft preservation and its evaluation. The proposed roadmap aims to deepen craft understanding so that blueprints of appropriate tools that support craft documentation, education, and training can be designed while achieving preservation through the stimulation and diversification of practitioner income. In addition to this roadmap, an evaluation strategy is proposed to validate the efficacy of the developed results and provide a benchmark for the efficacy of craft preservation approaches. The proposed contribution aims at the catalyzation of craft education and training with digital aids, widening access and engagement to crafts, economizing learning, increasing exercisability, and relaxing remoteness constraints in craft learning.Source: Heritage (Basel) Online 6 (2023): 5305–5328. doi:10.3390/heritage6070280
DOI: 10.3390/heritage6070280
Metrics:
See at:
ISTI Repository | www.mdpi.com | CNR ExploRA
2023
Report
Open Access
AIMH Research Activities 2023
Aloia N., Amato G., Bartalesi V., Bianchi L., Bolettieri P., Bosio C., Carraglia M., Carrara F., Casarosa V., Ciampi L., Coccomini D. A., Concordia C., Corbara S., De Martino C., Di Benedetto M., Esuli A., Falchi F., Fazzari E., Gennaro C., Lagani G., Lenzi E., Meghini C., Messina N., Molinari A., Moreo A., Nardi A., Pedrotti A., Pratelli N., Puccetti G., Rabitti F., Savino P., Sebastiani F., Sperduti G., Thanos C., Trupiano L., Vadicamo L., Vairo C., Versienti L.
The AIMH (Artificial Intelligence for Media and Humanities) laboratory is dedicated to exploring and pushing the boundaries in the field of Artificial Intelligence, with a particular focus on its application in digital media and humanities. This lab's objective is to enhance the current state of AI technology particularly on deep learning, text analysis, computer vision, multimedia information retrieval, multimedia content analysis, recognition, and retrieval. This report encapsulates the laboratory's progress and activities throughout the year 2023.Source: ISTI Annual Reports, 2023
DOI: 10.32079/isti-ar-2023/001
Metrics:
Aloia N., Amato G., Bartalesi V., Bianchi L., Bolettieri P., Bosio C., Carraglia M., Carrara F., Casarosa V., Ciampi L., Coccomini D. A., Concordia C., Corbara S., De Martino C., Di Benedetto M., Esuli A., Falchi F., Fazzari E., Gennaro C., Lagani G., Lenzi E., Meghini C., Messina N., Molinari A., Moreo A., Nardi A., Pedrotti A., Pratelli N., Puccetti G., Rabitti F., Savino P., Sebastiani F., Sperduti G., Thanos C., Trupiano L., Vadicamo L., Vairo C., Versienti L.
The AIMH (Artificial Intelligence for Media and Humanities) laboratory is dedicated to exploring and pushing the boundaries in the field of Artificial Intelligence, with a particular focus on its application in digital media and humanities. This lab's objective is to enhance the current state of AI technology particularly on deep learning, text analysis, computer vision, multimedia information retrieval, multimedia content analysis, recognition, and retrieval. This report encapsulates the laboratory's progress and activities throughout the year 2023.Source: ISTI Annual Reports, 2023
DOI: 10.32079/isti-ar-2023/001
Metrics:
See at:
ISTI Repository | CNR ExploRA
2021
Journal article
Open Access
Towards a knowledge base of medieval and renaissance geographical Latin works: the IMAGO ontology
Bartalesi V., Metilli D., Pratelli N., Pontari P.
In this article we present the first achievement of the Index Medii Aevi Geographiae Operum (IMAGO)--Italian National Research Project (2020-23), that is, the ontology we have created in order to formally represent the knowledge about the geographical works written in Middle Ages and Renaissance (6th-15th centuries). The IMAGO ontology is derived from a strict collaboration between the Institute of Information Science and Technologies (ISTI) of the Italian National Research Council (CNR) and the scholars who are involved in the project, who have supported ISTI-CNR in defining a conceptualization of the domain of knowledge. Following the re-use logic, we have selected as reference ontologies the International Committee on Documentation CRM vocabulary and its extension FRBRoo, including its in-progress reformulation, LRMoo. This research is included in a wider project context whose final aim is the creation of a knowledge base (KB) of Latin geographic literature of the Middle Ages and Renaissance Humanism in which the data are formally represented following the Linked Open Data paradigm and using the Semantic Web languages. At the end of the project, this KB will be accessed through a Web application that allows retrieving and consulting the collected data in a user-friendly way for scholars and general users, e.g. tables, maps, CSV files.Source: Digital Scholarship in the Humanities (2021). doi:10.1093/llc/fqab060
DOI: 10.1093/llc/fqab060
Metrics:
Bartalesi V., Metilli D., Pratelli N., Pontari P.
In this article we present the first achievement of the Index Medii Aevi Geographiae Operum (IMAGO)--Italian National Research Project (2020-23), that is, the ontology we have created in order to formally represent the knowledge about the geographical works written in Middle Ages and Renaissance (6th-15th centuries). The IMAGO ontology is derived from a strict collaboration between the Institute of Information Science and Technologies (ISTI) of the Italian National Research Council (CNR) and the scholars who are involved in the project, who have supported ISTI-CNR in defining a conceptualization of the domain of knowledge. Following the re-use logic, we have selected as reference ontologies the International Committee on Documentation CRM vocabulary and its extension FRBRoo, including its in-progress reformulation, LRMoo. This research is included in a wider project context whose final aim is the creation of a knowledge base (KB) of Latin geographic literature of the Middle Ages and Renaissance Humanism in which the data are formally represented following the Linked Open Data paradigm and using the Semantic Web languages. At the end of the project, this KB will be accessed through a Web application that allows retrieving and consulting the collected data in a user-friendly way for scholars and general users, e.g. tables, maps, CSV files.Source: Digital Scholarship in the Humanities (2021). doi:10.1093/llc/fqab060
DOI: 10.1093/llc/fqab060
Metrics:
See at:
ISTI Repository | academic.oup.com 
| CNR ExploRA
2021
Journal article
Open Access
A formal representation of the divine comedy's primary sources: The Hypermedia Dante Network ontology
Bartalesi V., Pratelli N., Meghini C., Metilli D., Tomazzoli G., Livraghi L. M. G., Zaccarello M.
Hypermedia Dante Network (HDN) is a 3-year Italian National Research Project, started in 2020, which aims to enrich the functionalities of the DanteSources Digital Library to efficiently represent knowledge about the primary sources of Dante's Comedy. DanteSources allows users to retrieve and visualize the list and the distribution of Dante's primary sources that have been identified by recent commentaries of five of Dante's minor works (i.e. Vita nova, De vulgari eloquentia, Convivio, De Monarchia, and Rime). The digital library is based on a formal ontology expressed in Resource Description Framework Schema (RDFS) language. Based on the DanteSources experience, the HDN project aims to formally represent the primary sources of the Divine Comedy whose identification is based on several commentaries included in the Dartmouth Dante Project corpus. To reach this goal, we restructured and extended the DanteSources ontology to provide a wider and more complete representation of the knowledge concerning the primary sources of the Comedy. In this article, we present the result of this effort, i.e. the HDN ontology. The ontology is expressed in OWL and has as reference ontologies the CIDOC CRM and its extension FRBRoo, including its in-progress reformulation LRMoo. We also briefly describe the semi-automatic tool that will be used by the scholars to populate the ontology.Source: Digital Scholarship in the Humanities 37 (2021): 630–643. doi:10.1093/llc/fqab080
DOI: 10.1093/llc/fqab080
Metrics:
Bartalesi V., Pratelli N., Meghini C., Metilli D., Tomazzoli G., Livraghi L. M. G., Zaccarello M.
Hypermedia Dante Network (HDN) is a 3-year Italian National Research Project, started in 2020, which aims to enrich the functionalities of the DanteSources Digital Library to efficiently represent knowledge about the primary sources of Dante's Comedy. DanteSources allows users to retrieve and visualize the list and the distribution of Dante's primary sources that have been identified by recent commentaries of five of Dante's minor works (i.e. Vita nova, De vulgari eloquentia, Convivio, De Monarchia, and Rime). The digital library is based on a formal ontology expressed in Resource Description Framework Schema (RDFS) language. Based on the DanteSources experience, the HDN project aims to formally represent the primary sources of the Divine Comedy whose identification is based on several commentaries included in the Dartmouth Dante Project corpus. To reach this goal, we restructured and extended the DanteSources ontology to provide a wider and more complete representation of the knowledge concerning the primary sources of the Comedy. In this article, we present the result of this effort, i.e. the HDN ontology. The ontology is expressed in OWL and has as reference ontologies the CIDOC CRM and its extension FRBRoo, including its in-progress reformulation LRMoo. We also briefly describe the semi-automatic tool that will be used by the scholars to populate the ontology.Source: Digital Scholarship in the Humanities 37 (2021): 630–643. doi:10.1093/llc/fqab080
DOI: 10.1093/llc/fqab080
Metrics:
See at:
ISTI Repository | academic.oup.com | CNR ExploRA
2022
Journal article
Open Access
Linking different scientific digital libraries in Digital Humanities: the IMAGO case study
Bartalesi V., Pratelli N., Lenzi E.
In the last years, several scientific digital libraries (DLs) in digital humanities (DH) field have been developed following the Open Science principles. These DLs aim at sharing the research outcomes, in several cases as FAIR data, and at creating linked information spaces. In several cases, to reach these aims the Semantic Web technologies and Linked Data have been used. This paper presents how the current scientific DLs in the DH field can provide the creation of linked information spaces and navigational services that allow users to navigate them, using Semantic Web technologies to formally represent, search and browsing knowledge. To support the argument, we present our experience in developing a scientific DL supporting scholars in creating, evolving and consulting a knowledge base related to Medieval and Renaissance geographical works within the three years (2020-2023) Italian National research project IMAGO--Index Medii Aevi Geographiae Operum. In the presented case study, a linked information space was created to allow users to discover and navigate knowledge across multiple repositories, thanks to the extensive use of ontologies. In particular, the linked information spaces created within the IMAGO project make use of five different datasets, i.e. Wikidata, the MIRABILE digital archive, the Nuovo Soggettario thesaurus, Mapping Manuscript Migration knowledge base and the Pleiades gazetteer. The linking among different datasets allows to considerably enrich the knowledge collected in the IMAGO KB.Source: International journal on digital libraries (Internet) (2022). doi:10.1007/s00799-022-00331-4
DOI: 10.1007/s00799-022-00331-4
Metrics:
Bartalesi V., Pratelli N., Lenzi E.
In the last years, several scientific digital libraries (DLs) in digital humanities (DH) field have been developed following the Open Science principles. These DLs aim at sharing the research outcomes, in several cases as FAIR data, and at creating linked information spaces. In several cases, to reach these aims the Semantic Web technologies and Linked Data have been used. This paper presents how the current scientific DLs in the DH field can provide the creation of linked information spaces and navigational services that allow users to navigate them, using Semantic Web technologies to formally represent, search and browsing knowledge. To support the argument, we present our experience in developing a scientific DL supporting scholars in creating, evolving and consulting a knowledge base related to Medieval and Renaissance geographical works within the three years (2020-2023) Italian National research project IMAGO--Index Medii Aevi Geographiae Operum. In the presented case study, a linked information space was created to allow users to discover and navigate knowledge across multiple repositories, thanks to the extensive use of ontologies. In particular, the linked information spaces created within the IMAGO project make use of five different datasets, i.e. Wikidata, the MIRABILE digital archive, the Nuovo Soggettario thesaurus, Mapping Manuscript Migration knowledge base and the Pleiades gazetteer. The linking among different datasets allows to considerably enrich the knowledge collected in the IMAGO KB.Source: International journal on digital libraries (Internet) (2022). doi:10.1007/s00799-022-00331-4
DOI: 10.1007/s00799-022-00331-4
Metrics:
See at:
ISTI Repository | link.springer.com | CNR ExploRA
2022
Report
Unknown
MOVING D3.3 - Tools for science-society-policy interfaces. Using semantic story maps to describe a territory beyond its map
Bartalesi V., Coro G., Lenzi E., Pratelli N., Pagano P.
Maps have always stimulated people's imagination and spatiotemporally supported storytelling; however, they cannot alone represent the life and emotions associated with the territories they describe. Story maps are an IT solution to enrich maps with such information. They are online applications enriched with multimedia and textual information that tell map-based stories. Current software for story map building is either commercial or requires advanced IT skills that make it hardly used by environmental experts. This deliverable describes the Story Map Building and Visualizing Tool (SBVMT), an open-source and free-to-use tool to build and publish story maps, which overcomes common drawbacks of other software by operating within the open-science e-Infrastructure (D4Science) used in the MOVING Project. SBVMT includes new features such as an ontology to represent story maps, Semantic Web technologies for data representation, automatic connection to Wikidata, secure multi-user collaboration in story building, and visualisation of the narrative either as a story map or a timeline. This deliverable shows how SBVMT can overcome the perceptual gap between territory and map. We evaluated its usability and effectiveness from both the point of view of experts building the story map and users interacting with it. Using SMBVT we created the story maps related to the MOVING selected regions. Furthermore, exploiting the semantic web technologies, we implemented several SPARQL queries that allow linking different stories and discovering new knowledge.Source: ISTI Research Report, MOVING, D3.3, 2022
Project(s): MOVING
Bartalesi V., Coro G., Lenzi E., Pratelli N., Pagano P.
Maps have always stimulated people's imagination and spatiotemporally supported storytelling; however, they cannot alone represent the life and emotions associated with the territories they describe. Story maps are an IT solution to enrich maps with such information. They are online applications enriched with multimedia and textual information that tell map-based stories. Current software for story map building is either commercial or requires advanced IT skills that make it hardly used by environmental experts. This deliverable describes the Story Map Building and Visualizing Tool (SBVMT), an open-source and free-to-use tool to build and publish story maps, which overcomes common drawbacks of other software by operating within the open-science e-Infrastructure (D4Science) used in the MOVING Project. SBVMT includes new features such as an ontology to represent story maps, Semantic Web technologies for data representation, automatic connection to Wikidata, secure multi-user collaboration in story building, and visualisation of the narrative either as a story map or a timeline. This deliverable shows how SBVMT can overcome the perceptual gap between territory and map. We evaluated its usability and effectiveness from both the point of view of experts building the story map and users interacting with it. Using SMBVT we created the story maps related to the MOVING selected regions. Furthermore, exploiting the semantic web technologies, we implemented several SPARQL queries that allow linking different stories and discovering new knowledge.Source: ISTI Research Report, MOVING, D3.3, 2022
Project(s): MOVING
See at: CNR ExploRA
2023
Journal article
Open Access
Using Semantic Web to create and explore an index of toponyms cited in Medieval geographical works
Bartalesi V., Pratelli N., Lenzi E., Pontari P.
Western thought in European history was mainly affected by the image of the world created during the Middle Ages and Renaissance. The most popular reason to travel during the Middle Ages was taking a pilgrimage. Jerusalem, Rome, and Santiago de Compostela were the most popular destinations. It is not surprising that a lot of works written by travellers as guides for pilgrims exist. By the beginning of the Renaissance, a more precise image of the world was defined thanks to the discovery of ancient geographical models, especially the work of Ptolemy. The three years (2020-2023) Italian National research project IMAGO - Index Medii Aevi Geographiae Operum - aims to provide a systematic overview of the medieval and renaissance Latin geographical literature using the Semantic Web technologies and the LOD paradigm. Indeed, until now, this literature has not been studied using digital methods. In particular, this paper presents how we formally represented the knowledge about the toponyms, or place names, in the IMAGO ontology. To maximise the interoperability, we developed the IMAGO ontology as an extension of two reference vocabularies: the CIDOC CRM and its extension FRBRoo, including its in-progress reformulation, LRMoo. Furthermore, we used Wikidata as reference knowledge base. As case study, we chose to represent the knowledge related to the toponyms cited by the Italian poet Dante Alighieri in his Latin works. We carried out a first experiment for visualising the knowledge about these toponyms on a map and in the form of tables and CSV files.Source: Journal on computing and cultural heritage (Online) (2023). doi:10.1145/3582263
DOI: 10.1145/3582263
Metrics:
Bartalesi V., Pratelli N., Lenzi E., Pontari P.
Western thought in European history was mainly affected by the image of the world created during the Middle Ages and Renaissance. The most popular reason to travel during the Middle Ages was taking a pilgrimage. Jerusalem, Rome, and Santiago de Compostela were the most popular destinations. It is not surprising that a lot of works written by travellers as guides for pilgrims exist. By the beginning of the Renaissance, a more precise image of the world was defined thanks to the discovery of ancient geographical models, especially the work of Ptolemy. The three years (2020-2023) Italian National research project IMAGO - Index Medii Aevi Geographiae Operum - aims to provide a systematic overview of the medieval and renaissance Latin geographical literature using the Semantic Web technologies and the LOD paradigm. Indeed, until now, this literature has not been studied using digital methods. In particular, this paper presents how we formally represented the knowledge about the toponyms, or place names, in the IMAGO ontology. To maximise the interoperability, we developed the IMAGO ontology as an extension of two reference vocabularies: the CIDOC CRM and its extension FRBRoo, including its in-progress reformulation, LRMoo. Furthermore, we used Wikidata as reference knowledge base. As case study, we chose to represent the knowledge related to the toponyms cited by the Italian poet Dante Alighieri in his Latin works. We carried out a first experiment for visualising the knowledge about these toponyms on a map and in the form of tables and CSV files.Source: Journal on computing and cultural heritage (Online) (2023). doi:10.1145/3582263
DOI: 10.1145/3582263
Metrics:
See at:
ISTI Repository | ISTI Repository | dl.acm.org | CNR ExploRA