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2023
Conference article
Open Access
Self-assess momentary mood in mobile devices: a case study with mature female participants
Senette C., Buzzi M. C., Paratore M. T.
Starting from the assumption that mood has a central role in domain-specific persuasion systems for well-being, the main goal of this study was to investigate the feasibility and acceptability of single-input methods to assess momentary mood as a medium for further interventions in health-related mobile apps destined for mature women. To this aim, we designed a very simple android App providing four user interfaces, each one showing one interactive widget to self-assess mood. Two widgets report a hint about the momentary mood they represent; the last two do not have the hints but were previously refined through questionnaires administered to 63 women (age 45-65) in order to reduce their expressive ambiguity. Next, fifteen women (age 45-65 years) were recruited to use the app for 15 days. Participants were polled about their mood four times a day and data were saved in a remote database. Moreover, users were asked to fill out a preliminary questionnaire, at the first access to the app, and a feedback questionnaire at the end of the testing period. Results appear to prove the feasibility and acceptability of this approach to self-assess momentary mood in the target population and provides some potential input methods to be used in this context.Source: ICCT 2023, Jaipur, India, 9-12/10/2023
Senette C., Buzzi M. C., Paratore M. T.
Starting from the assumption that mood has a central role in domain-specific persuasion systems for well-being, the main goal of this study was to investigate the feasibility and acceptability of single-input methods to assess momentary mood as a medium for further interventions in health-related mobile apps destined for mature women. To this aim, we designed a very simple android App providing four user interfaces, each one showing one interactive widget to self-assess mood. Two widgets report a hint about the momentary mood they represent; the last two do not have the hints but were previously refined through questionnaires administered to 63 women (age 45-65) in order to reduce their expressive ambiguity. Next, fifteen women (age 45-65 years) were recruited to use the app for 15 days. Participants were polled about their mood four times a day and data were saved in a remote database. Moreover, users were asked to fill out a preliminary questionnaire, at the first access to the app, and a feedback questionnaire at the end of the testing period. Results appear to prove the feasibility and acceptability of this approach to self-assess momentary mood in the target population and provides some potential input methods to be used in this context.Source: ICCT 2023, Jaipur, India, 9-12/10/2023
See at:
ISTI Repository 
| CNR ExploRA
2023
Conference article
Open Access
Haptic-based cognitive mapping to support shopping malls exploration
Paratore M. T., Leporini B.
This paper describes a study, which is currently underway, whose aim is to investigate how the haptic channel can be effectively exploited by visually impaired users in a mobile app for the preliminary exploration of an indoor environment, namely a shopping mall. Our goal was to use haptics to convey knowledge of how the points of interest (POIs) are distributed within the physical space, and at the same time provide information about the function of each POI, so that users can get a perception of how functional areas are distributed in the environment "at a glance". Shopping malls are typical indoor environments in which orientation aids are highly appreciated by customers, and many different functional areas persist. We identified seven typical categories of POIs which can be encountered in a mall, and then associated a different vibration pattern each. In order to validate our approach, we designed and developed a prototype for preliminary testing, based on the Android platform. The prototype was periodically debugged with the aid of two visually impaired experienced users, who gave us precious advice throughout the development process. We will describe how this app was conceived, the issues emerged during its development and the positive outcomes produced by a very early testing stage. Finally, we will show that the proposed approach is promising and is worthy of further investigation.Source: EAI GOODTECHS 2022 - 8th EAI International Conference on Smart Objects and Technologies for Social Good, pp. 54–62, Online event, 16-18/11/2022
DOI: 10.1007/978-3-031-28813-5_4
Metrics:
Paratore M. T., Leporini B.
This paper describes a study, which is currently underway, whose aim is to investigate how the haptic channel can be effectively exploited by visually impaired users in a mobile app for the preliminary exploration of an indoor environment, namely a shopping mall. Our goal was to use haptics to convey knowledge of how the points of interest (POIs) are distributed within the physical space, and at the same time provide information about the function of each POI, so that users can get a perception of how functional areas are distributed in the environment "at a glance". Shopping malls are typical indoor environments in which orientation aids are highly appreciated by customers, and many different functional areas persist. We identified seven typical categories of POIs which can be encountered in a mall, and then associated a different vibration pattern each. In order to validate our approach, we designed and developed a prototype for preliminary testing, based on the Android platform. The prototype was periodically debugged with the aid of two visually impaired experienced users, who gave us precious advice throughout the development process. We will describe how this app was conceived, the issues emerged during its development and the positive outcomes produced by a very early testing stage. Finally, we will show that the proposed approach is promising and is worthy of further investigation.Source: EAI GOODTECHS 2022 - 8th EAI International Conference on Smart Objects and Technologies for Social Good, pp. 54–62, Online event, 16-18/11/2022
DOI: 10.1007/978-3-031-28813-5_4
Metrics:
See at:
ISTI Repository | link.springer.com 
| CNR ExploRA
2023
Contribution to book
Open Access
A primer on open science-driven repository platforms
Bardi A., Manghi P., Mannocci A., Ottonello E., Pavone G.
Following Open Science mandates, institutions and communities increasingly demand repositories with native support for publishing scientific literature together with research data, software, and other research products. Such repositories may be thematic or general-purpose and are deeply integrated with the scholarly communication ecosystem to ensure versioning, persistent identifiers, data curation, usage stats, and so on. Identifying the most suitable off-the-shelf repository platform is often a non-trivial task as the choice depends on functional requirements, programming and technical skills, and infrastructure resources. This work analyses four state-of-the-art Open Source repository platforms, namely Dryad, Dataverse, DSpace, and InvenioRDM, from both a functional and a software perspective. This work intends to provide an overview serving as a primer for choosing repository platform solutions in different application scenarios. Moreover, this paper highlights how these platforms reacted to some key Open Science demands, moving away from the original and old-fashioned concept of a repository serving as a static container of files and metadata.Source: Metadata and Semantic Research, edited by Garoufallou E., Vlachidis A., pp. 222–234, 2023
DOI: 10.1007/978-3-031-39141-5_19
Project(s): OpenAIRE Nexus
Metrics:
Bardi A., Manghi P., Mannocci A., Ottonello E., Pavone G.
Following Open Science mandates, institutions and communities increasingly demand repositories with native support for publishing scientific literature together with research data, software, and other research products. Such repositories may be thematic or general-purpose and are deeply integrated with the scholarly communication ecosystem to ensure versioning, persistent identifiers, data curation, usage stats, and so on. Identifying the most suitable off-the-shelf repository platform is often a non-trivial task as the choice depends on functional requirements, programming and technical skills, and infrastructure resources. This work analyses four state-of-the-art Open Source repository platforms, namely Dryad, Dataverse, DSpace, and InvenioRDM, from both a functional and a software perspective. This work intends to provide an overview serving as a primer for choosing repository platform solutions in different application scenarios. Moreover, this paper highlights how these platforms reacted to some key Open Science demands, moving away from the original and old-fashioned concept of a repository serving as a static container of files and metadata.Source: Metadata and Semantic Research, edited by Garoufallou E., Vlachidis A., pp. 222–234, 2023
DOI: 10.1007/978-3-031-39141-5_19
Project(s): OpenAIRE Nexus
Metrics:
See at:
ISTI Repository | link.springer.com | CNR ExploRA
2023
Journal article
Open Access
A self-training automatic infant-cry detector
Coro G., Bardelli S., Cuttano A., Scaramuzzo R. T., Ciantelli M.
Infant cry is one of the first distinctive and informative life signals observed after birth. Neonatologists and automatic assistive systems can analyse infant cry to early-detect pathologies. These analyses extensively use reference expert-curated databases containing annotated infant-cry audio samples. However, these databases are not publicly accessible because of their sensitive data. Moreover, the recorded data can under-represent specific phenomena or the operational conditions required by other medical teams. Additionally, building these databases requires significant investments that few hospitals can afford. This paper describes an open-source workflow for infant-cry detection, which identifies audio segments containing high-quality infant-cry samples with no other overlapping audio events (e.g. machine noise or adult speech). It requires minimal training because it trains an LSTM-with-self-attention model on infant-cry samples automatically detected from the recorded audio through cluster analysis and HMM classification. The audio signal processing uses energy and intonation acoustic features from 100-ms segments to improve spectral robustness to noise. The workflow annotates the input audio with intervals containing infant-cry samples suited for populating a database for neonatological and early diagnosis studies. On 16 min of hospital phone-audio recordings, it reached sufficient infant-cry detection accuracy in 3 neonatal care environments (nursery--69%, sub-intensive--82%, intensive--77%) involving 20 infants subject to heterogeneous cry stimuli, and had substantial agreement with an expert's annotation. Our workflow is a cost-effective solution, particularly suited for a sub-intensive care environment, scalable to monitor from one to many infants. It allows a hospital to build and populate an extensive high-quality infant-cry database with a minimal investment.Source: Neural computing & applications (Print) (2023). doi:10.1007/s00521-022-08129-w
DOI: 10.1007/s00521-022-08129-w
Project(s): EcoScope
Metrics:
Coro G., Bardelli S., Cuttano A., Scaramuzzo R. T., Ciantelli M.
Infant cry is one of the first distinctive and informative life signals observed after birth. Neonatologists and automatic assistive systems can analyse infant cry to early-detect pathologies. These analyses extensively use reference expert-curated databases containing annotated infant-cry audio samples. However, these databases are not publicly accessible because of their sensitive data. Moreover, the recorded data can under-represent specific phenomena or the operational conditions required by other medical teams. Additionally, building these databases requires significant investments that few hospitals can afford. This paper describes an open-source workflow for infant-cry detection, which identifies audio segments containing high-quality infant-cry samples with no other overlapping audio events (e.g. machine noise or adult speech). It requires minimal training because it trains an LSTM-with-self-attention model on infant-cry samples automatically detected from the recorded audio through cluster analysis and HMM classification. The audio signal processing uses energy and intonation acoustic features from 100-ms segments to improve spectral robustness to noise. The workflow annotates the input audio with intervals containing infant-cry samples suited for populating a database for neonatological and early diagnosis studies. On 16 min of hospital phone-audio recordings, it reached sufficient infant-cry detection accuracy in 3 neonatal care environments (nursery--69%, sub-intensive--82%, intensive--77%) involving 20 infants subject to heterogeneous cry stimuli, and had substantial agreement with an expert's annotation. Our workflow is a cost-effective solution, particularly suited for a sub-intensive care environment, scalable to monitor from one to many infants. It allows a hospital to build and populate an extensive high-quality infant-cry database with a minimal investment.Source: Neural computing & applications (Print) (2023). doi:10.1007/s00521-022-08129-w
DOI: 10.1007/s00521-022-08129-w
Project(s): EcoScope
Metrics:
See at:
link.springer.com | ISTI Repository | CNR ExploRA
2023
Journal article
Open Access
Global-scale parameters for ecological models
Coro G., Bove P., Kesner-Reyes K.
This paper presents a collection of environmental, geophysical, and other marine-related data for marine ecological models and ecological-niche models. It consists of 2132 raster data for 58 distinct parameters at regional and global scales in the ESRI-GRID ASCII format. Most data originally belonged to open data owned by the authors of this article but residing on heterogeneous repositories with different formats and resolutions. Other data were specifically created for the present publication. The collection includes 565 data with global scale range; 154 at 0.5° resolution and 411 at 0.1° resolution; 196 data with annual temporal aggregation over ~10 key years between 1950 and 2100; 369 data with monthly aggregation at 0.1° resolution from January 2017 to ~May 2021 continuously. Data were also cut out on 8 European marine regions. The collection also includes forecasts for different future scenarios such as the Representative Concentration Pathways 2.6 (63 data), 4.5 (162 data), and 8.5 (162 data), and the A2 scenario of the Intergovernmental Panel on Climate Change (180 data).Source: Scientific data 10 (2023). doi:10.1038/s41597-022-01904-3
DOI: 10.1038/s41597-022-01904-3
Project(s): EcoScope
Metrics:
Coro G., Bove P., Kesner-Reyes K.
This paper presents a collection of environmental, geophysical, and other marine-related data for marine ecological models and ecological-niche models. It consists of 2132 raster data for 58 distinct parameters at regional and global scales in the ESRI-GRID ASCII format. Most data originally belonged to open data owned by the authors of this article but residing on heterogeneous repositories with different formats and resolutions. Other data were specifically created for the present publication. The collection includes 565 data with global scale range; 154 at 0.5° resolution and 411 at 0.1° resolution; 196 data with annual temporal aggregation over ~10 key years between 1950 and 2100; 369 data with monthly aggregation at 0.1° resolution from January 2017 to ~May 2021 continuously. Data were also cut out on 8 European marine regions. The collection also includes forecasts for different future scenarios such as the Representative Concentration Pathways 2.6 (63 data), 4.5 (162 data), and 8.5 (162 data), and the A2 scenario of the Intergovernmental Panel on Climate Change (180 data).Source: Scientific data 10 (2023). doi:10.1038/s41597-022-01904-3
DOI: 10.1038/s41597-022-01904-3
Project(s): EcoScope
Metrics:
See at:
ISTI Repository | www.nature.com | 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
2023
Report
Open Access
Implementation of a drug discovery pipeline on the D4Science platform
Orro A., D'Ursi P., Fossa P., Candela L., Panichi G.
This report documents the implementation of drug discovery pipeline in the D4Science platform realised in the context of the EOSC-Pillar project. In particular, it documents the pipeline and its constituents. Moreover, it describes how this pipeline has been integrated into the D4Science platform and exploited to create a dedicated Virtual Research Environment facilitating its exploitation and promoting a collaborative oriented approach for screening activities.Source: ISTI Technical Report, ISTI-2023-TR/001, 2023
DOI: 10.32079/isti-tr-2023/001
Project(s): EOSC-Pillar
Metrics:
Orro A., D'Ursi P., Fossa P., Candela L., Panichi G.
This report documents the implementation of drug discovery pipeline in the D4Science platform realised in the context of the EOSC-Pillar project. In particular, it documents the pipeline and its constituents. Moreover, it describes how this pipeline has been integrated into the D4Science platform and exploited to create a dedicated Virtual Research Environment facilitating its exploitation and promoting a collaborative oriented approach for screening activities.Source: ISTI Technical Report, ISTI-2023-TR/001, 2023
DOI: 10.32079/isti-tr-2023/001
Project(s): EOSC-Pillar
Metrics:
See at:
ISTI Repository | CNR ExploRA
2023
Report
Open Access
Definition of a new model of communication: Secure Application Email (SAE)
Gennai F., Sinibaldi F., Buzzi M., Martusciello L.
In this technical report, we define a Secure Application Email model and protocol that works on top of existing Internet email architecture that can be used in the development of new services with enanched security. The new Secure Application Email model could represent an evolution of the current Internet email model while keeping a deep level of interoperability between the two models.Source: ISTI Technical Report, ISTI-2023-TR/002, 2023
DOI: 10.32079/isti-tr-2023/002
Metrics:
Gennai F., Sinibaldi F., Buzzi M., Martusciello L.
In this technical report, we define a Secure Application Email model and protocol that works on top of existing Internet email architecture that can be used in the development of new services with enanched security. The new Secure Application Email model could represent an evolution of the current Internet email model while keeping a deep level of interoperability between the two models.Source: ISTI Technical Report, ISTI-2023-TR/002, 2023
DOI: 10.32079/isti-tr-2023/002
Metrics:
See at:
ISTI Repository | CNR ExploRA
2023
Journal article
Open Access
A simple framework for the exploration of functional biodiversity
Froese R., Coro G., Palomares M. L. D., Bailly N., Scotti M., Froese T., Garilao C., Pauly D.
Key traits of functional biodiversity are examined for 31,134 species of fishes. These traits are maximum body weight, productivity, and trophic level. A new, simple framework is presented that shows the combined usage of these traits, in ordinal categories, for close to 90% of extant species of fishes. Most species are clustered tightly along an evolutionary axis in size-productivity-trophic space (SPT-space) from few large, evolutionary old species with very low productivity to many medium-sized newly evolved species with high productivity, superseding Cope's rule of a within-lineages trend towards larger size and lower productivity. The across-lineages evolutionary axis is also found in the subsets of marine, freshwater, and Arctic species. Another notable prediction is the five-fold increase in top predators in Arctic waters in 2100, which could cause the extinction of endemic species. The main purpose of this study is to demonstrate the usefulness of the SPT-framework for comparing functional biodiversity patterns in ecosystems by salinity, geography or time. Also, the SPT-framework was used to explore correlations with other traits such as body shape, and to display the position of individual species, represented by pictograms of body shape and habitat, within SPT-space.Source: Cybium (2023): 1–16. doi:10.26028/cybium/2023-003
DOI: 10.26028/cybium/2023-003
Metrics:
Froese R., Coro G., Palomares M. L. D., Bailly N., Scotti M., Froese T., Garilao C., Pauly D.
Key traits of functional biodiversity are examined for 31,134 species of fishes. These traits are maximum body weight, productivity, and trophic level. A new, simple framework is presented that shows the combined usage of these traits, in ordinal categories, for close to 90% of extant species of fishes. Most species are clustered tightly along an evolutionary axis in size-productivity-trophic space (SPT-space) from few large, evolutionary old species with very low productivity to many medium-sized newly evolved species with high productivity, superseding Cope's rule of a within-lineages trend towards larger size and lower productivity. The across-lineages evolutionary axis is also found in the subsets of marine, freshwater, and Arctic species. Another notable prediction is the five-fold increase in top predators in Arctic waters in 2100, which could cause the extinction of endemic species. The main purpose of this study is to demonstrate the usefulness of the SPT-framework for comparing functional biodiversity patterns in ecosystems by salinity, geography or time. Also, the SPT-framework was used to explore correlations with other traits such as body shape, and to display the position of individual species, represented by pictograms of body shape and habitat, within SPT-space.Source: Cybium (2023): 1–16. doi:10.26028/cybium/2023-003
DOI: 10.26028/cybium/2023-003
Metrics:
See at:
ISTI Repository | sfi-cybium.fr | CNR ExploRA
2023
Journal article
Open Access
What are researchers' needs in data discovery? Analysis and ranking of a large-scale collection of crowdsourced use cases
Mathiak B., Juty N., Bardi A., Colomb J., Kraker P.
Data discovery is important to facilitate data re-use. In order to help frame the development and improvement of data discovery tools, we collected a list of requirements and users' wishes. This paper presents the analysis of these 101 use cases to examine data discovery requirements; these cases were collected between 2019 and 2020. We categorized the information across 12 'topics' and eight types of users. While the availability of metadata was an expected topic of importance, users were also keen on receiving more information on data citation and a better overview of their field. We conducted and analysed a survey among data infrastructure specialists in a first attempt at ranking the requirements. Between these data professionals, these rankings were very different, excepting the availability of metadata and data quality assessment.Source: Data science journal 22 (2023). doi:10.5334/dsj-2023-003
DOI: 10.5334/dsj-2023-003
Project(s): OpenAIRE-Advance
Metrics:
Mathiak B., Juty N., Bardi A., Colomb J., Kraker P.
Data discovery is important to facilitate data re-use. In order to help frame the development and improvement of data discovery tools, we collected a list of requirements and users' wishes. This paper presents the analysis of these 101 use cases to examine data discovery requirements; these cases were collected between 2019 and 2020. We categorized the information across 12 'topics' and eight types of users. While the availability of metadata was an expected topic of importance, users were also keen on receiving more information on data citation and a better overview of their field. We conducted and analysed a survey among data infrastructure specialists in a first attempt at ranking the requirements. Between these data professionals, these rankings were very different, excepting the availability of metadata and data quality assessment.Source: Data science journal 22 (2023). doi:10.5334/dsj-2023-003
DOI: 10.5334/dsj-2023-003
Project(s): OpenAIRE-Advance
Metrics:
See at:
datascience.codata.org | ISTI Repository | CNR ExploRA
2023
Journal article
Open Access
Exploiting the haptic and audio channels to improve orientation and mobility apps for the visually impaired
Paratore M. T., Leporini B.
Orientation and mobility apps for visually impaired people are well known to be effective in improving the quality of life for this target group. A mobile application that guides a visually impaired person step-by-step through a physical space is a valuable aid, but it does not provide an overview of a complex environment "at a glance," as a traditional hard-copy tactile map does. The aim of this study is to investigate whether a smartphone GPS map, enriched with haptic and audio hints, can facilitate cognitive mapping for visually impaired users. Encouraged by a preliminary study conducted in co-operation with two visually impaired volunteers, we designed and developed an Android prototype for exploration of an urban area. Our goal was to provide an affordable, portable and versatile solution to help users increase awareness of an environment through the positions of its landmarks and points of interest. Vibro-tactile and audio hints were linked to the coordinates on the map via the GeoJSON data format and were issued exploiting the text-to-speech and vibration features of the mobile device, as they were displayed through the operating system's APIs. Test sessions and interviews with visually impaired users produced encouraging results. Results, to be verified by more extensive testing, overall confirm the validity of our approach and are in line with results found in the literature.Source: Universal access in the information society (Print) (2023). doi:10.1007/s10209-023-00973-4
DOI: 10.1007/s10209-023-00973-4
Metrics:
Paratore M. T., Leporini B.
Orientation and mobility apps for visually impaired people are well known to be effective in improving the quality of life for this target group. A mobile application that guides a visually impaired person step-by-step through a physical space is a valuable aid, but it does not provide an overview of a complex environment "at a glance," as a traditional hard-copy tactile map does. The aim of this study is to investigate whether a smartphone GPS map, enriched with haptic and audio hints, can facilitate cognitive mapping for visually impaired users. Encouraged by a preliminary study conducted in co-operation with two visually impaired volunteers, we designed and developed an Android prototype for exploration of an urban area. Our goal was to provide an affordable, portable and versatile solution to help users increase awareness of an environment through the positions of its landmarks and points of interest. Vibro-tactile and audio hints were linked to the coordinates on the map via the GeoJSON data format and were issued exploiting the text-to-speech and vibration features of the mobile device, as they were displayed through the operating system's APIs. Test sessions and interviews with visually impaired users produced encouraging results. Results, to be verified by more extensive testing, overall confirm the validity of our approach and are in line with results found in the literature.Source: Universal access in the information society (Print) (2023). doi:10.1007/s10209-023-00973-4
DOI: 10.1007/s10209-023-00973-4
Metrics:
See at:
ISTI Repository | link.springer.com | CNR ExploRA
2023
Journal article
Open Access
An exploratory approach to data driven knowledge creation
Thanos C., Meghini C., Bartalesi V., Coro G.
This paper describes a new approach to knowledge creation that is instrumental for the emerging paradigm of data-intensive science. The proposed approach enables the acquisition of new insights from the data by exploiting existing relationships between diverse types of datasets acquired through various modalities. The value of data consistently improves when it can be linked to other data because linking multiple types of datasets allows creating novel data patterns within a scientific data space. These patterns enable the exploratory data analysis, an analysis strategy that emphasizes incremental and adaptive access to the datasets constituting a scientific data space while maintaining an open mind to alternative possibilities of data interconnectivity. A technology, the Linked Open data (LOD), was developed to enable the linking of datasets. We argue that the LOD technology presents several limitations that prevent the full exploitation of this technology to acquire new insights. In this paper, we outline a new approach that enables researchers to dynamically create data patterns in a research data space by exploiting explicit and implicit/hidden relationships between distributed research datasets. This dynamic creation of data patterns enables the exploratory data analysis strategy.Source: Journal of big data 10 (2023). doi:10.1186/s40537-023-00702-x
DOI: 10.1186/s40537-023-00702-x
Metrics:
Thanos C., Meghini C., Bartalesi V., Coro G.
This paper describes a new approach to knowledge creation that is instrumental for the emerging paradigm of data-intensive science. The proposed approach enables the acquisition of new insights from the data by exploiting existing relationships between diverse types of datasets acquired through various modalities. The value of data consistently improves when it can be linked to other data because linking multiple types of datasets allows creating novel data patterns within a scientific data space. These patterns enable the exploratory data analysis, an analysis strategy that emphasizes incremental and adaptive access to the datasets constituting a scientific data space while maintaining an open mind to alternative possibilities of data interconnectivity. A technology, the Linked Open data (LOD), was developed to enable the linking of datasets. We argue that the LOD technology presents several limitations that prevent the full exploitation of this technology to acquire new insights. In this paper, we outline a new approach that enables researchers to dynamically create data patterns in a research data space by exploiting explicit and implicit/hidden relationships between distributed research datasets. This dynamic creation of data patterns enables the exploratory data analysis strategy.Source: Journal of big data 10 (2023). doi:10.1186/s40537-023-00702-x
DOI: 10.1186/s40537-023-00702-x
Metrics:
See at:
journalofbigdata.springeropen.com | ISTI Repository | CNR ExploRA
2023
Journal article
Open Access
D4SCIENCE: a unique infrastructure delivering virtual research environments as a service
Candela L., Castelli D., Pagano P.
Nowadays, research challenges - often based on the collaborative analysis of a large amount of data - require suitable infrastructures and user-facing solutions promoting multidisciplinary collaboration and appropriate communication and sharing of data, processes, and outcomes. The D4Science infrastructure and its virtual research environments proved to be a viable and effective solution for many communities of practice and use cases.Source: ERCIM news 133 (2023): 6–7.
Project(s): Blue Cloud, SoBigData-PlusPlus
Candela L., Castelli D., Pagano P.
Nowadays, research challenges - often based on the collaborative analysis of a large amount of data - require suitable infrastructures and user-facing solutions promoting multidisciplinary collaboration and appropriate communication and sharing of data, processes, and outcomes. The D4Science infrastructure and its virtual research environments proved to be a viable and effective solution for many communities of practice and use cases.Source: ERCIM news 133 (2023): 6–7.
Project(s): Blue Cloud
, SoBigData-PlusPlus
See at:
ercim-news.ercim.eu | ISTI Repository | CNR ExploRA
2023
Journal article
Open Access
Estimating hidden fishing activity hotspots from vessel transmitted data
Coro G., Sana L., Ferrà C., Bove P., Scarcella G.
Monitoring fishery activity is essential for resource planning and guaranteeing fisheries sustainability. Large fishing vessels constantly and continuously communicate their positions via Automatic Identification System (AIS) or Vessel Monitoring Systems (VMSs). These systems can use radio or Global Positioning System (GPS) devices to transmit data. Processing and integrating these big data with other fisheries data allows for exploring the relations between socio-economic and ecosystem assets in marine areas, which is fundamental in fishery monitoring. In this context, estimating actual fishing activity from time series of AIS and VMS data would enhance the correct identification of fishing activity patterns and help assess regulations' effectiveness. However, these data might contain gaps because of technical issues such as limited coverage of the terrestrial receivers or saturated transmission bands. Other sources of data gaps are adverse meteorological conditions and voluntary switch-offs. Gaps may also include hidden (unreported) fishing activity whose quantification would improve actual fishing activity estimation. This paper presents a workflow for AIS/VMS big-data analysis that estimates potential unreported fishing activity hotspots in a marine area. The workflow uses a statistical spatial analysis over vessel speeds and coordinates and a multi-source data integration approach that can work on multiple areas and multiple analysis scales. Specifically, it (i) estimates fishing activity locations and rebuilds data gaps, (ii) estimates the potential unreported fishing hour distribution and the unreported-over-total ratio of fishing hours at a 0.01° spatial resolution, (iii) identifies potential unreported fishing activity hotspots, (iv) extracts the stocks involved in these hotspots (using global-scale repositories of stock and species observation data) and raises an alert about their possible endangered, threatened, and protected (ETP) status. The workflow is also a free-to-use Web Service running on an open science-compliant cloud computing platform with a Web Processing Service (WPS) standard interface, allowing efficient big data processing. As a study case, we focussed on the Adriatic Sea. We reconstructed the monthly reported and potential unreported trawling activity in 2019, using terrestrial AIS data with a 5-min sampling period, containing ~50 million records transmitted by ~1,600 vessels. The results highlight that the unreported fishing activity hotspots especially impacted Italian coasts and some forbidden and protected areas. The potential unreported activity involved 33 stocks, four of which were ETP species in the basin. The extracted information agreed with expert studies, and the estimated trawling patterns agreed with those produced by the Global Fishing Watch.Source: Frontiers in sustainable food systems On line 7 (2023). doi:10.3389/fsufs.2023.1152226
DOI: 10.3389/fsufs.2023.1152226
Project(s): EcoScope
Metrics:
Coro G., Sana L., Ferrà C., Bove P., Scarcella G.
Monitoring fishery activity is essential for resource planning and guaranteeing fisheries sustainability. Large fishing vessels constantly and continuously communicate their positions via Automatic Identification System (AIS) or Vessel Monitoring Systems (VMSs). These systems can use radio or Global Positioning System (GPS) devices to transmit data. Processing and integrating these big data with other fisheries data allows for exploring the relations between socio-economic and ecosystem assets in marine areas, which is fundamental in fishery monitoring. In this context, estimating actual fishing activity from time series of AIS and VMS data would enhance the correct identification of fishing activity patterns and help assess regulations' effectiveness. However, these data might contain gaps because of technical issues such as limited coverage of the terrestrial receivers or saturated transmission bands. Other sources of data gaps are adverse meteorological conditions and voluntary switch-offs. Gaps may also include hidden (unreported) fishing activity whose quantification would improve actual fishing activity estimation. This paper presents a workflow for AIS/VMS big-data analysis that estimates potential unreported fishing activity hotspots in a marine area. The workflow uses a statistical spatial analysis over vessel speeds and coordinates and a multi-source data integration approach that can work on multiple areas and multiple analysis scales. Specifically, it (i) estimates fishing activity locations and rebuilds data gaps, (ii) estimates the potential unreported fishing hour distribution and the unreported-over-total ratio of fishing hours at a 0.01° spatial resolution, (iii) identifies potential unreported fishing activity hotspots, (iv) extracts the stocks involved in these hotspots (using global-scale repositories of stock and species observation data) and raises an alert about their possible endangered, threatened, and protected (ETP) status. The workflow is also a free-to-use Web Service running on an open science-compliant cloud computing platform with a Web Processing Service (WPS) standard interface, allowing efficient big data processing. As a study case, we focussed on the Adriatic Sea. We reconstructed the monthly reported and potential unreported trawling activity in 2019, using terrestrial AIS data with a 5-min sampling period, containing ~50 million records transmitted by ~1,600 vessels. The results highlight that the unreported fishing activity hotspots especially impacted Italian coasts and some forbidden and protected areas. The potential unreported activity involved 33 stocks, four of which were ETP species in the basin. The extracted information agreed with expert studies, and the estimated trawling patterns agreed with those produced by the Global Fishing Watch.Source: Frontiers in sustainable food systems On line 7 (2023). doi:10.3389/fsufs.2023.1152226
DOI: 10.3389/fsufs.2023.1152226
Project(s): EcoScope
Metrics:
See at:
ISTI Repository | www.frontiersin.org | CNR ExploRA
2023
Journal article
Open Access
Situated conditional reasoning
Casini G., Meyer T., Varzinczak I.
Conditionals are useful for modelling many forms of everyday human reasoning but are not always sufficiently expressive to represent the information we want to reason about. In this paper, we make a case for a form of situated conditional. By 'situated', we mean that there is a context, based on an agent's beliefs and expectations, that works as background information in evaluating a conditional, and we allow such a context to vary. These conditionals are able to distinguish, for example, between expectations and counterfactuals. Formally, they are shown to generalise the conditional setting in the style of Kraus, Lehmann, and Magidor. We show that situated conditionals can be described in terms of a set of rationality postulates. We then propose an intuitive semantics for these conditionals and present a representation result which shows that our semantic construction corresponds exactly to the description in terms of postulates. With the semantics in place, we define a form of entailment for situated conditional knowledge bases, which we refer to as minimal closure. Finally, we proceed to show that it is possible to reduce the computation of minimal closure to a series of propositional entailment and satisfiability checks. While this is also the case for rational closure, it is somewhat surprising that the result carries over to minimal closure.Source: Artificial intelligence (Gen. ed.) 319 (2023). doi:10.1016/j.artint.2023.103917
DOI: 10.1016/j.artint.2023.103917
DOI: 10.48550/arxiv.2109.01552
Project(s): TAILOR
Metrics:
Casini G., Meyer T., Varzinczak I.
Conditionals are useful for modelling many forms of everyday human reasoning but are not always sufficiently expressive to represent the information we want to reason about. In this paper, we make a case for a form of situated conditional. By 'situated', we mean that there is a context, based on an agent's beliefs and expectations, that works as background information in evaluating a conditional, and we allow such a context to vary. These conditionals are able to distinguish, for example, between expectations and counterfactuals. Formally, they are shown to generalise the conditional setting in the style of Kraus, Lehmann, and Magidor. We show that situated conditionals can be described in terms of a set of rationality postulates. We then propose an intuitive semantics for these conditionals and present a representation result which shows that our semantic construction corresponds exactly to the description in terms of postulates. With the semantics in place, we define a form of entailment for situated conditional knowledge bases, which we refer to as minimal closure. Finally, we proceed to show that it is possible to reduce the computation of minimal closure to a series of propositional entailment and satisfiability checks. While this is also the case for rational closure, it is somewhat surprising that the result carries over to minimal closure.Source: Artificial intelligence (Gen. ed.) 319 (2023). doi:10.1016/j.artint.2023.103917
DOI: 10.1016/j.artint.2023.103917
DOI: 10.48550/arxiv.2109.01552
Project(s): TAILOR
Metrics:
See at:
arXiv.org e-Print Archive | ISTI Repository | Artificial Intelligence | doi.org | www.sciencedirect.com | CNR ExploRA
2023
Conference article
Open Access
(Semi)automated disambiguation of scholarly repositories
Baglioni M., Mannocci A., Pavone G., De Bonis M., Manghi P.
The full exploitation of scholarly repositories is pivotal in modern Open Science, and scholarly repository registries are kingpins in enabling researchers and research infrastructures to list and search for suitable repositories. However, since multiple registries exist, repository managers are keen on registering multiple times the repositories they manage to maximise their traction and visibility across different research communities, disciplines, and applications. These multiple registrations ultimately lead to information fragmentation and redundancy on the one hand and, on the other, force registries' users to juggle multiple registries, profiles and identifiers describing the same repository. Such problems are known to registries, which claim equivalence between repository profiles whenever possible by cross-referencing their identifiers across different registries. However, as we will see, this "claim set" is far from complete and, therefore, many replicas slip under the radar, possibly creating problems downstream. In this work, we combine such claims to create duplicate sets and extend them with the results of an automated clustering algorithm run over repository metadata descriptions. Then we manually validate our results to produce an "as accurate as possible" de-duplicated dataset of scholarly repositories.Source: IRCDL 2023 - 19th conference on Information and Research Science Connecting to Digital and Library Science, pp. 47–59, Bari, Italy, 23-24/02/2023
Project(s): OpenAIRE Nexus
Baglioni M., Mannocci A., Pavone G., De Bonis M., Manghi P.
The full exploitation of scholarly repositories is pivotal in modern Open Science, and scholarly repository registries are kingpins in enabling researchers and research infrastructures to list and search for suitable repositories. However, since multiple registries exist, repository managers are keen on registering multiple times the repositories they manage to maximise their traction and visibility across different research communities, disciplines, and applications. These multiple registrations ultimately lead to information fragmentation and redundancy on the one hand and, on the other, force registries' users to juggle multiple registries, profiles and identifiers describing the same repository. Such problems are known to registries, which claim equivalence between repository profiles whenever possible by cross-referencing their identifiers across different registries. However, as we will see, this "claim set" is far from complete and, therefore, many replicas slip under the radar, possibly creating problems downstream. In this work, we combine such claims to create duplicate sets and extend them with the results of an automated clustering algorithm run over repository metadata descriptions. Then we manually validate our results to produce an "as accurate as possible" de-duplicated dataset of scholarly repositories.Source: IRCDL 2023 - 19th conference on Information and Research Science Connecting to Digital and Library Science, pp. 47–59, Bari, Italy, 23-24/02/2023
Project(s): OpenAIRE Nexus
See at:
ceur-ws.org | ISTI Repository | CNR ExploRA
2023
Conference article
Open Access
Digital publishing, Open Access, and Grey Literature: the war in Ukraine 2022 as a use case
Farace D., Smith P. L., Biagioni S., Carlesi C.
The underlying strategy in this study focuses on digital persistent identifiers and other linked open data as they become connected and interrelated in the course of research and whose outcome is published as grey literature. On January 31st 2022, GreyNet published its 2nd edition of the International Directory of Organizations in Grey Literature (IDGL). This edition includes record entries from 45 countries worldwide with a listing of 224 organizations. Each entry contains the organization's URL and ROR ID, which further provides access to other linked open data such as GRID, ISNI, CrossRef Funder ID, and Wikidata. GreyNet will use this information resource as a lead into the project dealing with digital publishing, open access, and grey literature, whereby the War in Ukraine will serve as a use case. The population of the study relies for the greater part on IDGL, a digital publication that contains access to persistent identifiers, specifically the ROR ID. An online survey is then further designed, the questions are formulated in such a way that a number of the responses provide other linked open data and digital persistent identifiers namely ORCiDs and DOIs. Survey data together with the linked metadata gathered and compiled in this study will then be analyzed. The results are expected to demonstrate the currentness of grey literature, its diverseness in formats and document types, the organizations that stand behind these publications, and how actionable persistent identifiers opens research in grey literature to a new level playing field situated in a FAIR environment. An environment where data is not only findable and openly accessible but also interoperable and reusable by means of digital publishing. Records harvested via the online survey will be included in the RGL Collection (Resources in Grey Literature) housed in the GreyGuide Repository.Source: GL 2022 - 24th International Conference on Grey Literature: Publishing Grey Literature in the Digital Century, pp. 122–127, Online conference, 05/12/2022
Farace D., Smith P. L., Biagioni S., Carlesi C.
The underlying strategy in this study focuses on digital persistent identifiers and other linked open data as they become connected and interrelated in the course of research and whose outcome is published as grey literature. On January 31st 2022, GreyNet published its 2nd edition of the International Directory of Organizations in Grey Literature (IDGL). This edition includes record entries from 45 countries worldwide with a listing of 224 organizations. Each entry contains the organization's URL and ROR ID, which further provides access to other linked open data such as GRID, ISNI, CrossRef Funder ID, and Wikidata. GreyNet will use this information resource as a lead into the project dealing with digital publishing, open access, and grey literature, whereby the War in Ukraine will serve as a use case. The population of the study relies for the greater part on IDGL, a digital publication that contains access to persistent identifiers, specifically the ROR ID. An online survey is then further designed, the questions are formulated in such a way that a number of the responses provide other linked open data and digital persistent identifiers namely ORCiDs and DOIs. Survey data together with the linked metadata gathered and compiled in this study will then be analyzed. The results are expected to demonstrate the currentness of grey literature, its diverseness in formats and document types, the organizations that stand behind these publications, and how actionable persistent identifiers opens research in grey literature to a new level playing field situated in a FAIR environment. An environment where data is not only findable and openly accessible but also interoperable and reusable by means of digital publishing. Records harvested via the online survey will be included in the RGL Collection (Resources in Grey Literature) housed in the GreyGuide Repository.Source: GL 2022 - 24th International Conference on Grey Literature: Publishing Grey Literature in the Digital Century, pp. 122–127, Online conference, 05/12/2022
See at:
ISTI Repository | greyguide.isti.cnr.it | CNR ExploRA
2023
Report
Open Access
Roadmap Scienza Aperta
Castelli D., De Simone G., Cancedda F., Candela L., Colcelli V., Conte R., Di Donato F., Giannini S., Lazzeri E., Mangiaracina S., Puccinelli R., Ranchino M. A.
La scienza aperta è un paradigma che influenza le pratiche di produzione e condivisione di conoscenza. Obiettivo di questa roadmap è delineare un percorso per la realizzazione e diffusione di pratiche e politiche di scienza aperta all'interno del Consiglio Nazionale delle Ricerche.Source: DOI - 10.57665/BICE_ROADMAP2023, 2023
Castelli D., De Simone G., Cancedda F., Candela L., Colcelli V., Conte R., Di Donato F., Giannini S., Lazzeri E., Mangiaracina S., Puccinelli R., Ranchino M. A.
La scienza aperta è un paradigma che influenza le pratiche di produzione e condivisione di conoscenza. Obiettivo di questa roadmap è delineare un percorso per la realizzazione e diffusione di pratiche e politiche di scienza aperta all'interno del Consiglio Nazionale delle Ricerche.Source: DOI - 10.57665/BICE_ROADMAP2023, 2023
See at:
ISTI Repository | CNR ExploRA
2023
Journal article
Open Access
Defeasible RDFS via rational closure
Casini G., Straccia U.
In the field of non-monotonic logics, the notion of Rational Closure (RC) is acknowledged as a notable approach. In recent years, RC has gained popularity in the context of Description Logics (DLs), the logic underpinning the standard semantic Web Ontology Language OWL 2, whose main ingredients are classes, the relationship among classes and roles, which are used to describe the properties of classes. In this work, we show instead how to integrate RC within the triple language RDFS (Resource Description Framework Schema), which together with OWL 2 is a major standard semantic web ontology language. To do so, we start from rdf, a minimal, but significant RDFS fragment that covers the essential features of RDFS, and then extend it to rdf_\bot, allowing to state that two entities are incompatible/disjoint with each other. Eventually, we propose defeasible rdf_\bot via a typical RC construction allowing to state default class/property inclusions. Furthermore, to overcome the main weaknesses of RC in our context, i.e., the "drowning problem" (viz. the "inheritance blocking problem"), we further extend our construction by leveraging Defeasible Inheritance Networks (DIN) defining a new non-monotonic inference relation that combines the advantages of both (RC and DIN). To the best of our knowledge this is the first time of such an attempt. In summary, the main features of our approach are: (i) the defeasible rdf_\bot we propose here remains syntactically a triple language by extending it with new predicate symbols with specific semantics; (ii) the logic is defined in such a way that any RDFS reasoner/store may handle the new predicates as ordinary terms if it does not want to take account of the extra non-monotonic capabilities; (iii) the defeasible entailment decision procedure is built on top of the rdf_\bot entailment decision procedure, which in turn is an extension of the one for rdf via some additional inference rules favouring a potential implementation; (iv) the computational complexity of deciding entailment in rdf and rdf_\bot are the same; and (v) defeasible entailment can be decided via a polynomial number of calls to an oracle deciding ground triple entailment in rdf_\bot and, in particular, deciding defeasible entailment can be done in polynomial time.Source: Information sciences 643 (2023). doi:10.1016/j.ins.2022.11.165
DOI: 10.1016/j.ins.2022.11.165
DOI: 10.48550/arxiv.2007.07573
Project(s): TAILOR
Metrics:
Casini G., Straccia U.
In the field of non-monotonic logics, the notion of Rational Closure (RC) is acknowledged as a notable approach. In recent years, RC has gained popularity in the context of Description Logics (DLs), the logic underpinning the standard semantic Web Ontology Language OWL 2, whose main ingredients are classes, the relationship among classes and roles, which are used to describe the properties of classes. In this work, we show instead how to integrate RC within the triple language RDFS (Resource Description Framework Schema), which together with OWL 2 is a major standard semantic web ontology language. To do so, we start from rdf, a minimal, but significant RDFS fragment that covers the essential features of RDFS, and then extend it to rdf_\bot, allowing to state that two entities are incompatible/disjoint with each other. Eventually, we propose defeasible rdf_\bot via a typical RC construction allowing to state default class/property inclusions. Furthermore, to overcome the main weaknesses of RC in our context, i.e., the "drowning problem" (viz. the "inheritance blocking problem"), we further extend our construction by leveraging Defeasible Inheritance Networks (DIN) defining a new non-monotonic inference relation that combines the advantages of both (RC and DIN). To the best of our knowledge this is the first time of such an attempt. In summary, the main features of our approach are: (i) the defeasible rdf_\bot we propose here remains syntactically a triple language by extending it with new predicate symbols with specific semantics; (ii) the logic is defined in such a way that any RDFS reasoner/store may handle the new predicates as ordinary terms if it does not want to take account of the extra non-monotonic capabilities; (iii) the defeasible entailment decision procedure is built on top of the rdf_\bot entailment decision procedure, which in turn is an extension of the one for rdf via some additional inference rules favouring a potential implementation; (iv) the computational complexity of deciding entailment in rdf and rdf_\bot are the same; and (v) defeasible entailment can be decided via a polynomial number of calls to an oracle deciding ground triple entailment in rdf_\bot and, in particular, deciding defeasible entailment can be done in polynomial time.Source: Information sciences 643 (2023). doi:10.1016/j.ins.2022.11.165
DOI: 10.1016/j.ins.2022.11.165
DOI: 10.48550/arxiv.2007.07573
Project(s): TAILOR
Metrics:
See at:
arXiv.org e-Print Archive | Information Sciences | doi.org | www.sciencedirect.com | CNR ExploRA
2023
Journal article
Open Access
Missing plant detection in vineyards using UAV angled RGB imagery acquired in dormant period
Di Gennaro S. F., Vannini G. L., Berton A., Dainelli R., Toscano P., Matese A.
Since 2010, more and more farmers have been using remote sensing data from unmanned aerial vehicles, which have a high spatial-temporal resolution, to determine the status of their crops and how their fields change. Imaging sensors, such as multispectral and RGB cameras, are the most widely used tool in vineyards to characterize the vegetative development of the canopy and detect the presence of missing vines along the rows. In this study, the authors propose different approaches to identify and locate each vine within a commercial vineyard using angled RGB images acquired during winter in the dormant period (without canopy leaves), thus minimizing any disturbance to the agronomic practices commonly conducted in the vegetative period. Using a combination of photogrammetric techniques and spatial analysis tools, a workflow was developed to extract each post and vine trunk from a dense point cloud and then assess the number and position of missing vines with high precision. In order to correctly identify the vines and missing vines, the performance of four methods was evaluated, and the best performing one achieved 95.10% precision and 92.72% overall accuracy. The results confirm that the methodology developed represents an effective support in the decision-making processes for the correct management of missing vines, which is essential for preserving a vineyard's productive capacity and, more importantly, to ensure the farmer's economic return.Source: Drones 7 (2023). doi:10.3390/drones7060349
DOI: 10.3390/drones7060349
Metrics:
Di Gennaro S. F., Vannini G. L., Berton A., Dainelli R., Toscano P., Matese A.
Since 2010, more and more farmers have been using remote sensing data from unmanned aerial vehicles, which have a high spatial-temporal resolution, to determine the status of their crops and how their fields change. Imaging sensors, such as multispectral and RGB cameras, are the most widely used tool in vineyards to characterize the vegetative development of the canopy and detect the presence of missing vines along the rows. In this study, the authors propose different approaches to identify and locate each vine within a commercial vineyard using angled RGB images acquired during winter in the dormant period (without canopy leaves), thus minimizing any disturbance to the agronomic practices commonly conducted in the vegetative period. Using a combination of photogrammetric techniques and spatial analysis tools, a workflow was developed to extract each post and vine trunk from a dense point cloud and then assess the number and position of missing vines with high precision. In order to correctly identify the vines and missing vines, the performance of four methods was evaluated, and the best performing one achieved 95.10% precision and 92.72% overall accuracy. The results confirm that the methodology developed represents an effective support in the decision-making processes for the correct management of missing vines, which is essential for preserving a vineyard's productive capacity and, more importantly, to ensure the farmer's economic return.Source: Drones 7 (2023). doi:10.3390/drones7060349
DOI: 10.3390/drones7060349
Metrics:
See at:
ISTI Repository | www.mdpi.com | CNR ExploRA