Moussab/ORKG-training-evaluation-set huggingface dataset:
Research field: Graphics
Title: Visualizing Populated Ontologies with OntoTrix
Abstract: Research on visualizing Semantic Web data has yielded many tools that rely on information visualization techniques to better support the user in understanding and editing these data. Most tools structure the visualization according to the concept definitions and interrelations that constitute the ontology's vocabulary. Instances are often treated as somewhat peripheral information, when considered at all. These instances, that populate ontologies, represent an essential part of any knowledge base. Understanding instance-level data might be easier for users because of their higher concreteness, but instances will often be orders of magnitude more numerous than the concept definitions that give them machine-processable meaning. As such, the visualization of instance-level data poses different but real challenges. The authors present a visualization technique designed to enable users to visualize large instance sets and the relations that connect them. This visualization uses both node-link and adjacency matrix representations of graphs to visualize different parts of the data depending on their semantic and local structural properties. The technique was originally devised for simple social network visualization. The authors extend it to handle the richer and more complex graph structures of populated ontologies, exploiting ontological knowledge to drive the layout of, and navigation in, the representation embedded in a smooth zoomable environment.
Extracted statement — Domain: ontology
Research field: Graphics
Title: Facets and Pivoting for Flexible and Usable Linked Data Exploration
Abstract: The success of Open Data initiatives has increased the amount of data available on the Web. Unfortunately, most of this data is only available in raw tabular form, what makes analysis and reuse quite difficult for non-experts. Linked Data principles allow for a more sophisticated approach by making explicit both the structure and semantics of the data. However, from the end-user viewpoint, they continue to be monolithic files completely opaque or difficult to explore by making tedious semantic queries. Our objective is to facilitate the user to grasp what kind of entities are in the dataset, how they are interrelated, which are their main properties and values, etc. Rhizomer is a tool for data publishing whose interface provides a set of components borrowed from Information Architecture (IA) that facilitate awareness of the dataset at hand. It automatically generates navigation menus and facets based on the kinds of things in the dataset and how they are described through metadata properties and values. Moreover, motivated by recent tests with end-users, it also provides the possibility to pivot among the faceted views created for each class of resources in the dataset.
Extracted statement — implementation: Rhizomer
Research field: Graphics
Title: Facets and Pivoting for Flexible and Usable Linked Data Exploration
Abstract: The success of Open Data initiatives has increased the amount of data available on the Web. Unfortunately, most of this data is only available in raw tabular form, what makes analysis and reuse quite difficult for non-experts. Linked Data principles allow for a more sophisticated approach by making explicit both the structure and semantics of the data. However, from the end-user viewpoint, they continue to be monolithic files completely opaque or difficult to explore by making tedious semantic queries. Our objective is to facilitate the user to grasp what kind of entities are in the dataset, how they are interrelated, which are their main properties and values, etc. Rhizomer is a tool for data publishing whose interface provides a set of components borrowed from Information Architecture (IA) that facilitate awareness of the dataset at hand. It automatically generates navigation menus and facets based on the kinds of things in the dataset and how they are described through metadata properties and values. Moreover, motivated by recent tests with end-users, it also provides the possibility to pivot among the faceted views created for each class of resources in the dataset.
Extracted statement — System: Rhizomer
Research field: Graphics
Title: SemLens: visual analysis of semantic data with scatter plots and semantic lenses
Abstract: Querying the Semantic Web and analyzing the query results are often complex tasks that can be greatly facilitated by visual interfaces. A major challenge in the design of these interfaces is to provide intuitive and efficient interaction support without limiting too much the analytical degrees of freedom. This paper introduces SemLens, a visual tool that combines scatter plots and semantic lenses to overcome this challenge and to allow for a simple yet powerful analysis of RDF data. The scatter plots provide a global overview on an object collection and support the visual discovery of correlations and patterns in the data. The semantic lenses add dimensions for local analysis of subsets of the objects. A demo accessing DBpedia data is used for illustration.
Extracted statement — implementation: SemLens
Research field: Graphics
Title: Using Clusters in RDF Visualization
Abstract: Clustered graph visualization techniques are an easy to understand way of hiding complex parts of a visualized graph when they are not needed by the user. When visualizing RDF, there are several situations where such clusters are defined in a very natural way. Using this techniques, we can give the user optional access to some detailed information without unnecessarily occupying space in the basic view of the data. This paper describes algorithms for clustered visualization used in the Trisolda RDF visualizer. Most notable is the newly added clustered navigation technique.
Extracted statement — implementation: Trisolda
Research field: Graphics
Title: Using Clusters in RDF Visualization
Abstract: Clustered graph visualization techniques are an easy to understand way of hiding complex parts of a visualized graph when they are not needed by the user. When visualizing RDF, there are several situations where such clusters are defined in a very natural way. Using this techniques, we can give the user optional access to some detailed information without unnecessarily occupying space in the basic view of the data. This paper describes algorithms for clustered visualization used in the Trisolda RDF visualizer. Most notable is the newly added clustered navigation technique.
Extracted statement — System: Trisolda
Research field: Graphics
Title: Facets and Pivoting for Flexible and Usable Linked Data Exploration
Abstract: The success of Open Data initiatives has increased the amount of data available on the Web. Unfortunately, most of this data is only available in raw tabular form, what makes analysis and reuse quite difficult for non-experts. Linked Data principles allow for a more sophisticated approach by making explicit both the structure and semantics of the data. However, from the end-user viewpoint, they continue to be monolithic files completely opaque or difficult to explore by making tedious semantic queries. Our objective is to facilitate the user to grasp what kind of entities are in the dataset, how they are interrelated, which are their main properties and values, etc. Rhizomer is a tool for data publishing whose interface provides a set of components borrowed from Information Architecture (IA) that facilitate awareness of the dataset at hand. It automatically generates navigation menus and facets based on the kinds of things in the dataset and how they are described through metadata properties and values. Moreover, motivated by recent tests with end-users, it also provides the possibility to pivot among the faceted views created for each class of resources in the dataset.
Extracted statement — App. Type: Web
Research field: Graphics
Title: SemLens: visual analysis of semantic data with scatter plots and semantic lenses
Abstract: Querying the Semantic Web and analyzing the query results are often complex tasks that can be greatly facilitated by visual interfaces. A major challenge in the design of these interfaces is to provide intuitive and efficient interaction support without limiting too much the analytical degrees of freedom. This paper introduces SemLens, a visual tool that combines scatter plots and semantic lenses to overcome this challenge and to allow for a simple yet powerful analysis of RDF data. The scatter plots provide a global overview on an object collection and support the visual discovery of correlations and patterns in the data. The semantic lenses add dimensions for local analysis of subsets of the objects. A demo accessing DBpedia data is used for illustration.
Extracted statement — App. Type: Web
Research field: Graphics
Title: Formal Linked Data Visualization Model
Abstract: Recently, the amount of semantic data available in the Web has increased dramatically. The potential of this vast amount of data is enormous but in most cases it is difficult for users to explore and use this data, especially for those without experience with Semantic Web technologies. Applying information visualization techniques to the Semantic Web helps users to easily explore large amounts of data and interact with them. In this article we devise a formal Linked Data Visualization Model (LDVM), which allows to dynamically connect data with visualizations. We report about our implementation of the LDVM comprising a library of generic visualizations that enable both users and data analysts to get an overview on, visualize and explore the Data Web and perform detailed analyzes on Linked Data.
Extracted statement — App. Type: Web
Research field: Graphics
Title: Using Semantics for Interactive Visual Analysis of Linked Open Data
Abstract: Providing easy to use methods for visual analysis of Linked Data is often hindered by the complexity of semantic technologies. On the other hand, semantic information inherent to Linked Data provides opportunities to support the user in interactively analysing the data. This paper provides a demonstration of an interactive, Web-based visualisation tool, the "Vis Wizard", which makes use of semantics to simplify the process of setting up visualisations, transforming the data and, most importantly, interactively analysing multiple datasets using brushing and linking methods.
Extracted statement — App. Type: Web
Research field: Graphics
Title: ZoomRDF: semantic fisheye zooming on RDF data.
Abstract: With the development of Semantic Web in recent years, an increasing amount of semantic data has been created in form of Resource Description Framework (RDF). Current visualization techniques help users quickly understand the underlying RDF data by displaying its structure in an overview. However, detailed information can only be accessed by further navigation. An alternative approach is to display the global context as well as the local details simultaneously in a unified view. This view supports the visualization and navigation on RDF data in an integrated way. In this demonstration, we present ZoomRDF, a framework that: i) adapts a space-optimized visualization algorithm for RDF, which allows more resources to be displayed, thus maximizes the utilization of display space, ii) combines the visualization with a fisheye zooming concept, which assigns more space to some individual nodes while still preserving the overview structure of the data, iii) considers both the importance of resources and the user interaction on them, which offers more display space to those elements the user may be interested in. We implement the framework based on the Gene Ontology and demonstrate that it facilitates tasks like RDF data exploration and editing.
Extracted statement — implementation: ZoomRDF
Research field: Graphics
Title: A tool for visualization and editing of OWL ontologies
Abstract: In an effort to optimize visualization and editing of OWL ontologies we have developed GrOWL: a browser and visual editor for OWL that accurately visualizes the underlying DL semantics of OWL ontologies while avoiding the difficulties of the verbose OWL syntax. In this paper, we discuss GrOWL visualization model and the essential visualization techniques implemented in GrOWL.
Extracted statement — implementation: GrOWL
Research field: Graphics
Title: SemLens: visual analysis of semantic data with scatter plots and semantic lenses
Abstract: Querying the Semantic Web and analyzing the query results are often complex tasks that can be greatly facilitated by visual interfaces. A major challenge in the design of these interfaces is to provide intuitive and efficient interaction support without limiting too much the analytical degrees of freedom. This paper introduces SemLens, a visual tool that combines scatter plots and semantic lenses to overcome this challenge and to allow for a simple yet powerful analysis of RDF data. The scatter plots provide a global overview on an object collection and support the visual discovery of correlations and patterns in the data. The semantic lenses add dimensions for local analysis of subsets of the objects. A demo accessing DBpedia data is used for illustration.
Extracted statement — Vis. Types: Scatter
Research field: Immunology and Infectious Disease
Title: Safety and Immunogenicity of Two RNA-Based Covid-19 Vaccine Candidates
Abstract: Abstract Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections and the resulting disease, coronavirus disease 2019 (Covid-19), have spread to millions of persons worldwide. Multiple vaccine candidates are under development, but no vaccine is currently available. Interim safety and immunogenicity data about the vaccine candidate BNT162b1 in younger adults have been reported previously from trials in Germany and the United States. Methods In an ongoing, placebo-controlled, observer-blinded, dose-escalation, phase 1 trial conducted in the United States, we randomly assigned healthy adults 18 to 55 years of age and those 65 to 85 years of age to receive either placebo or one of two lipid nanoparticle–formulated, nucleoside-modified RNA vaccine candidates: BNT162b1, which encodes a secreted trimerized SARS-CoV-2 receptor–binding domain; or BNT162b2, which encodes a membrane-anchored SARS-CoV-2 full-length spike, stabilized in the prefusion conformation. The primary outcome was safety (e.g., local and systemic reactions and adverse events); immunogenicity was a secondary outcome. Trial groups were defined according to vaccine candidate, age of the participants, and vaccine dose level (10 μg, 20 μg, 30 μg, and 100 μg). In all groups but one, participants received two doses, with a 21-day interval between doses; in one group (100 μg of BNT162b1), participants received one dose. Results A total of 195 participants underwent randomization. In each of 13 groups of 15 participants, 12 participants received vaccine and 3 received placebo. BNT162b2 was associated with a lower incidence and severity of systemic reactions than BNT162b1, particularly in older adults. In both younger and older adults, the two vaccine candidates elicited similar dose-dependent SARS-CoV-2–neutralizing geometric mean titers, which were similar to or higher than the geometric mean titer of a panel of SARS-CoV-2 convalescent serum samples. Conclusions The safety and immunogenicity data from this U.S. phase 1 trial of two vaccine candidates in younger and older adults, added to earlier interim safety and immunogenicity data regarding BNT162b1 in younger adults from trials in Germany and the United States, support the selection of BNT162b2 for advancement to a pivotal phase 2–3 safety and efficacy evaluation. (Funded by BioNTech and Pfizer; ClinicalTrials.gov number, NCT04368728.)
Extracted statement — Organisations: BioNTech
Research field: Immunology and Infectious Disease
Title: Safety and Immunogenicity of Two RNA-Based Covid-19 Vaccine Candidates
Abstract: Abstract Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections and the resulting disease, coronavirus disease 2019 (Covid-19), have spread to millions of persons worldwide. Multiple vaccine candidates are under development, but no vaccine is currently available. Interim safety and immunogenicity data about the vaccine candidate BNT162b1 in younger adults have been reported previously from trials in Germany and the United States. Methods In an ongoing, placebo-controlled, observer-blinded, dose-escalation, phase 1 trial conducted in the United States, we randomly assigned healthy adults 18 to 55 years of age and those 65 to 85 years of age to receive either placebo or one of two lipid nanoparticle–formulated, nucleoside-modified RNA vaccine candidates: BNT162b1, which encodes a secreted trimerized SARS-CoV-2 receptor–binding domain; or BNT162b2, which encodes a membrane-anchored SARS-CoV-2 full-length spike, stabilized in the prefusion conformation. The primary outcome was safety (e.g., local and systemic reactions and adverse events); immunogenicity was a secondary outcome. Trial groups were defined according to vaccine candidate, age of the participants, and vaccine dose level (10 μg, 20 μg, 30 μg, and 100 μg). In all groups but one, participants received two doses, with a 21-day interval between doses; in one group (100 μg of BNT162b1), participants received one dose. Results A total of 195 participants underwent randomization. In each of 13 groups of 15 participants, 12 participants received vaccine and 3 received placebo. BNT162b2 was associated with a lower incidence and severity of systemic reactions than BNT162b1, particularly in older adults. In both younger and older adults, the two vaccine candidates elicited similar dose-dependent SARS-CoV-2–neutralizing geometric mean titers, which were similar to or higher than the geometric mean titer of a panel of SARS-CoV-2 convalescent serum samples. Conclusions The safety and immunogenicity data from this U.S. phase 1 trial of two vaccine candidates in younger and older adults, added to earlier interim safety and immunogenicity data regarding BNT162b1 in younger adults from trials in Germany and the United States, support the selection of BNT162b2 for advancement to a pivotal phase 2–3 safety and efficacy evaluation. (Funded by BioNTech and Pfizer; ClinicalTrials.gov number, NCT04368728.)
Extracted statement — Organisations: Pfizer
Research field: Immunopathology
Title: A new coronavirus associated with human respiratory disease in China
Abstract: Abstract Emerging infectious diseases, such as severe acute respiratory syndrome (SARS) and Zika virus disease, present a major threat to public health 1–3 . Despite intense research efforts, how, when and where new diseases appear are still a source of considerable uncertainty. A severe respiratory disease was recently reported in Wuhan, Hubei province, China. As of 25 January 2020, at least 1,975 cases had been reported since the first patient was hospitalized on 12 December 2019. Epidemiological investigations have suggested that the outbreak was associated with a seafood market in Wuhan. Here we study a single patient who was a worker at the market and who was admitted to the Central Hospital of Wuhan on 26 December 2019 while experiencing a severe respiratory syndrome that included fever, dizziness and a cough. Metagenomic RNA sequencing 4 of a sample of bronchoalveolar lavage fluid from the patient identified a new RNA virus strain from the family Coronaviridae , which is designated here ‘WH-Human 1’ coronavirus (and has also been referred to as ‘2019-nCoV’). Phylogenetic analysis of the complete viral genome (29,903 nucleotides) revealed that the virus was most closely related (89.1% nucleotide similarity) to a group of SARS-like coronaviruses (genus Betacoronavirus, subgenus Sarbecovirus) that had previously been found in bats in China 5 . This outbreak highlights the ongoing ability of viral spill-over from animals to cause severe disease in humans.
Extracted statement — patient characteristics: patient
Research field: Immunopathology
Title: A new coronavirus associated with human respiratory disease in China
Abstract: Abstract Emerging infectious diseases, such as severe acute respiratory syndrome (SARS) and Zika virus disease, present a major threat to public health 1–3 . Despite intense research efforts, how, when and where new diseases appear are still a source of considerable uncertainty. A severe respiratory disease was recently reported in Wuhan, Hubei province, China. As of 25 January 2020, at least 1,975 cases had been reported since the first patient was hospitalized on 12 December 2019. Epidemiological investigations have suggested that the outbreak was associated with a seafood market in Wuhan. Here we study a single patient who was a worker at the market and who was admitted to the Central Hospital of Wuhan on 26 December 2019 while experiencing a severe respiratory syndrome that included fever, dizziness and a cough. Metagenomic RNA sequencing 4 of a sample of bronchoalveolar lavage fluid from the patient identified a new RNA virus strain from the family Coronaviridae , which is designated here ‘WH-Human 1’ coronavirus (and has also been referred to as ‘2019-nCoV’). Phylogenetic analysis of the complete viral genome (29,903 nucleotides) revealed that the virus was most closely related (89.1% nucleotide similarity) to a group of SARS-like coronaviruses (genus Betacoronavirus, subgenus Sarbecovirus) that had previously been found in bats in China 5 . This outbreak highlights the ongoing ability of viral spill-over from animals to cause severe disease in humans.
Extracted statement — Has method: sequencing
Research field: Industrial and Organizational Psychology
Title: Individual differences and changes in subjective wellbeing during the early stages of the COVID-19 pandemic.
Abstract: The COVID-19 pandemic has considerably impacted many people's lives. This study examined changes in subjective wellbeing between December 2019 and May 2020 and how stress appraisals and coping strategies relate to individual differences and changes in subjective wellbeing during the early stages of the pandemic. Data were collected at 4 time points from 979 individuals in Germany. Results showed that, on average, life satisfaction, positive affect, and negative affect did not change significantly between December 2019 and March 2020 but decreased between March and May 2020. Across the latter timespan, individual differences in life satisfaction were positively related to controllability appraisals, active coping, and positive reframing, and negatively related to threat and centrality appraisals and planning. Positive affect was positively related to challenge and controllable-by-self appraisals, active coping, using emotional support, and religion, and negatively related to threat appraisal and humor. Negative affect was positively related to threat and centrality appraisals, denial, substance use, and self-blame, and negatively related to controllability appraisals and emotional support. Contrary to expectations, the effects of stress appraisals and coping strategies on changes in subjective wellbeing were small and mostly nonsignificant. These findings imply that the COVID-19 pandemic represents not only a major medical and economic crisis, but also has a psychological dimension, as it can be associated with declines in key facets of people's subjective wellbeing. Psychological practitioners should address potential declines in subjective wellbeing with their clients and attempt to enhance clients' general capability to use functional stress appraisals and effective coping strategies. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
Extracted statement — Control variables: Age