The exploration of moderately dense networks is used in various challenges of visual data analysis. Frequently, the solutions lay in graph drawing, based on automatic forcedirected layout, which results in a spontaneous and irreproducible node-link diagram. Currently available approaches to improve its readability are generally oriented to finite rendering without providing to the analyst handy tools for post-layout manipulations. Enabling indirect manual control on visualizations through multi-step menus may appear difficult to learn and use. Thus, this problem requires a more intuitive way of solving. This paper presents an original toolset for userguided refinement of the force-directed graph layout, with a bias on pen-centric sketching techniques.
{"title":"Sketch-Based Interactions for Untangling of Force-Directed Graphs","authors":"V. Guchev, Cristina Gena","doi":"10.1109/iV.2017.64","DOIUrl":"https://doi.org/10.1109/iV.2017.64","url":null,"abstract":"The exploration of moderately dense networks is used in various challenges of visual data analysis. Frequently, the solutions lay in graph drawing, based on automatic forcedirected layout, which results in a spontaneous and irreproducible node-link diagram. Currently available approaches to improve its readability are generally oriented to finite rendering without providing to the analyst handy tools for post-layout manipulations. Enabling indirect manual control on visualizations through multi-step menus may appear difficult to learn and use. Thus, this problem requires a more intuitive way of solving. This paper presents an original toolset for userguided refinement of the force-directed graph layout, with a bias on pen-centric sketching techniques.","PeriodicalId":410876,"journal":{"name":"2017 21st International Conference Information Visualisation (IV)","volume":"18 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116093298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Timeseries line charts are a popular visualization technique but traditionally do not show many lines. We borrow concepts of tiny microtext and path dependent cartographic text to embed labels and additional text directly into lines on line charts, thereby making it easier to identify individual lines in a congested line chart, enabling more lines to be displayed and enabling additional data to be added to the lines as well.
{"title":"Microtext Line Charts","authors":"R. Brath, E. Banissi","doi":"10.1109/iV.2017.82","DOIUrl":"https://doi.org/10.1109/iV.2017.82","url":null,"abstract":"Timeseries line charts are a popular visualization technique but traditionally do not show many lines. We borrow concepts of tiny microtext and path dependent cartographic text to embed labels and additional text directly into lines on line charts, thereby making it easier to identify individual lines in a congested line chart, enabling more lines to be displayed and enabling additional data to be added to the lines as well.","PeriodicalId":410876,"journal":{"name":"2017 21st International Conference Information Visualisation (IV)","volume":"287 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122829693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper describes the design and development of an interactive tool for explorative visualization of influence networks between artists. Developed in an interdisciplinary collaboration of computer scientists and art historians, the tool aims at supporting art historians and other interested parties in the interactive discovery and analysis of creative influences between a group of artists and their works. The influences are based on the judgements of art historians for pairs of works and an aggregation formula. The tool consists of multiple visualizations, each representing a different level of detail. In addition to metadata, e.g. the date of a work of art, and images of the works of art, influences between works or (if aggregated) between artists are displayed in graph form. A preliminary evaluation of the prototype with a non-expert audience as well as domain experts points to opportunities and areas of potential improvement in applying this approach to support novel research and exploration practices in digital art history.
{"title":"InfluViz — A Visualization Tool for Exploring and Analyzing Creative Influence Between Artists and their Works","authors":"Christine Schikora, Daniel Isemann","doi":"10.1109/iV.2017.66","DOIUrl":"https://doi.org/10.1109/iV.2017.66","url":null,"abstract":"This paper describes the design and development of an interactive tool for explorative visualization of influence networks between artists. Developed in an interdisciplinary collaboration of computer scientists and art historians, the tool aims at supporting art historians and other interested parties in the interactive discovery and analysis of creative influences between a group of artists and their works. The influences are based on the judgements of art historians for pairs of works and an aggregation formula. The tool consists of multiple visualizations, each representing a different level of detail. In addition to metadata, e.g. the date of a work of art, and images of the works of art, influences between works or (if aggregated) between artists are displayed in graph form. A preliminary evaluation of the prototype with a non-expert audience as well as domain experts points to opportunities and areas of potential improvement in applying this approach to support novel research and exploration practices in digital art history.","PeriodicalId":410876,"journal":{"name":"2017 21st International Conference Information Visualisation (IV)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127261770","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Humans are vulnerable to cognitive biases such as neglect of probability, framing effect, confirmation bias, conservatism (belief revision) and anchoring. Argument Mapper addresses these biases in intelligence analysis by providing an easy-to-use, theoretically sound, web-based interactive software tool that enables the application of evidence-based reasoning to analytic questions. Designed in collaboration with analytic methodologists, this tool combines structured argument mapping methodology with visualization techniques to help analysts make sense of complex problems and overcome cognitive biases. The tool uses Baconian probability and conjunctive logic to automatically calculate the inferential force on the upper level hypothesis. Evaluations with 16 analysts showed the tool was easy to use and easy to understand.
{"title":"Argument Mapper: Countering Cognitive Biases in Analysis with Critical (Visual) Thinking","authors":"William Wright, D. Sheffield, Stephanie Santosa","doi":"10.1109/iV.2017.69","DOIUrl":"https://doi.org/10.1109/iV.2017.69","url":null,"abstract":"Humans are vulnerable to cognitive biases such as neglect of probability, framing effect, confirmation bias, conservatism (belief revision) and anchoring. Argument Mapper addresses these biases in intelligence analysis by providing an easy-to-use, theoretically sound, web-based interactive software tool that enables the application of evidence-based reasoning to analytic questions. Designed in collaboration with analytic methodologists, this tool combines structured argument mapping methodology with visualization techniques to help analysts make sense of complex problems and overcome cognitive biases. The tool uses Baconian probability and conjunctive logic to automatically calculate the inferential force on the upper level hypothesis. Evaluations with 16 analysts showed the tool was easy to use and easy to understand.","PeriodicalId":410876,"journal":{"name":"2017 21st International Conference Information Visualisation (IV)","volume":"277 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120923777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Biometric authentication systems verify the identity of individuals based on what they are. As they are error prone, they can reject genuine individuals or accept impostors. Researchers of the field quantify the quality of their algorithm by benchmarking it on several databases. However, although the standard evaluation metrics state the performance of their system, they are unable to explain the reasons of their errors. This paper presents a novel way to visualize the evaluation results of a biometric authentication system which helps to find which individuals or samples are sources of errors. This knowledge could help to fix the algorithms. A biometric database of scores is modeled as a partitioned power-graph with nodes representing biometric samples and power-nodes representing individuals. A novel recursive edge bundling method is also applied to reduce clutter. This proposal has been successfully applied on several biometric databases and has proved its efficiency.
{"title":"Evaluation of Biometric Authentication Systems through Visualisation of Partitioned and Bundled Power-Graphs","authors":"R. Giot","doi":"10.1109/iV.2017.17","DOIUrl":"https://doi.org/10.1109/iV.2017.17","url":null,"abstract":"Biometric authentication systems verify the identity of individuals based on what they are. As they are error prone, they can reject genuine individuals or accept impostors. Researchers of the field quantify the quality of their algorithm by benchmarking it on several databases. However, although the standard evaluation metrics state the performance of their system, they are unable to explain the reasons of their errors. This paper presents a novel way to visualize the evaluation results of a biometric authentication system which helps to find which individuals or samples are sources of errors. This knowledge could help to fix the algorithms. A biometric database of scores is modeled as a partitioned power-graph with nodes representing biometric samples and power-nodes representing individuals. A novel recursive edge bundling method is also applied to reduce clutter. This proposal has been successfully applied on several biometric databases and has proved its efficiency.","PeriodicalId":410876,"journal":{"name":"2017 21st International Conference Information Visualisation (IV)","volume":"152 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114169621","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Principal Component Analysis (PCA) is an established and efficient method for finding structure in a multidimensional data set. PCA is based on orthogonal transformations that convert a set of multidimensional values into linearly uncorrelated variables called principal components.The main disadvantage to the PCA approach is that the procedure and outcome are often difficult to understand. The connection between input and output can be puzzling, a small change in input can yield a completely different output, and the user may often wonder if the PCA is doing the right thing.We introduce a user interface that makes the procedure and result easier to understand. We have implemented an interactive PCA view in our text visualization tool called Text Variation Explorer. It allows the user to interactively study the result of PCA, and provides a better understanding of the process.We believe that although we are addressing the problem of interactive principal component analysis in the context of text visualization, these ideas should be useful in other contexts as well.
{"title":"Interactive Principal Component Analysis","authors":"H. Siirtola, Tanja Säily, T. Nevalainen","doi":"10.1109/iV.2017.39","DOIUrl":"https://doi.org/10.1109/iV.2017.39","url":null,"abstract":"Principal Component Analysis (PCA) is an established and efficient method for finding structure in a multidimensional data set. PCA is based on orthogonal transformations that convert a set of multidimensional values into linearly uncorrelated variables called principal components.The main disadvantage to the PCA approach is that the procedure and outcome are often difficult to understand. The connection between input and output can be puzzling, a small change in input can yield a completely different output, and the user may often wonder if the PCA is doing the right thing.We introduce a user interface that makes the procedure and result easier to understand. We have implemented an interactive PCA view in our text visualization tool called Text Variation Explorer. It allows the user to interactively study the result of PCA, and provides a better understanding of the process.We believe that although we are addressing the problem of interactive principal component analysis in the context of text visualization, these ideas should be useful in other contexts as well.","PeriodicalId":410876,"journal":{"name":"2017 21st International Conference Information Visualisation (IV)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116213779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Speech and language researchers often rely on large, naturalistic, audio-visual corpora to identify and measure patterns of language structure, variation, change and use. There are, however, few visualization tools designed for this need. This paper proposes a novel visual analytic method to process large linguistic corpora by employing Bayes' Theorem and interactive visualization. We adopt a simple and meaningful design in our visualization for linguists to understand. Instead of offering a fixed visualization, this project enables greater interaction through filtering, grouping and dragging. Multiple phases are included in the system, from processing the metadata exported from popular standalone linguistic software, to creating the visualization, and enabling interaction and filtering.
{"title":"CorpusViz: Child and Adult Speech Visualisation","authors":"Jesse Tran, Quang Vinh Nguyen, Caroline Jones, Rachel Hendery, S. Simoff","doi":"10.1109/iV.2017.19","DOIUrl":"https://doi.org/10.1109/iV.2017.19","url":null,"abstract":"Speech and language researchers often rely on large, naturalistic, audio-visual corpora to identify and measure patterns of language structure, variation, change and use. There are, however, few visualization tools designed for this need. This paper proposes a novel visual analytic method to process large linguistic corpora by employing Bayes' Theorem and interactive visualization. We adopt a simple and meaningful design in our visualization for linguists to understand. Instead of offering a fixed visualization, this project enables greater interaction through filtering, grouping and dragging. Multiple phases are included in the system, from processing the metadata exported from popular standalone linguistic software, to creating the visualization, and enabling interaction and filtering.","PeriodicalId":410876,"journal":{"name":"2017 21st International Conference Information Visualisation (IV)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116296961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The paper introduces an approach that allows for detecting interaction with a graphical display in a rule-based declarative approach. It also introduces the possibility of connecting the interaction to a specific animation step to be performed. The two approaches were embedded into an animation system to aid in teaching algorithms.
{"title":"A Rule-Based Approach for Automatic Interaction Detection and Annotation","authors":"Nada Sharaf, Slim Abdennadher, Thom W. Frühwirth","doi":"10.1109/iV.2017.59","DOIUrl":"https://doi.org/10.1109/iV.2017.59","url":null,"abstract":"The paper introduces an approach that allows for detecting interaction with a graphical display in a rule-based declarative approach. It also introduces the possibility of connecting the interaction to a specific animation step to be performed. The two approaches were embedded into an animation system to aid in teaching algorithms.","PeriodicalId":410876,"journal":{"name":"2017 21st International Conference Information Visualisation (IV)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126666174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We have proposed an introductory C programming exercise based on contest style using execution test series. We have developed a contest management server tProgrEss and have carried out educational practices since 2009. We developed an Instruction support tool vRoundEd in classroom round during a contest. The tool is for teaching assistants with each tablet PC. It shows a seat map in classroom and indicates progress information of the contest in each student. When an assistant notices a signal from a student in the seat map, he goes to the desk to help or uses a chat system. We revised GUI and extended several functions in the tool. We carried out questionnaires for more than 10 assistants. We consider the replies and opinions for improvement.
{"title":"A Proposal of Assistant Support Tool in Classroom Round and Personal Tutoring with a Seating Chart for Introductory C Programming Exercises","authors":"H. Tominaga, Shoya Ota","doi":"10.1109/iV.2017.81","DOIUrl":"https://doi.org/10.1109/iV.2017.81","url":null,"abstract":"We have proposed an introductory C programming exercise based on contest style using execution test series. We have developed a contest management server tProgrEss and have carried out educational practices since 2009. We developed an Instruction support tool vRoundEd in classroom round during a contest. The tool is for teaching assistants with each tablet PC. It shows a seat map in classroom and indicates progress information of the contest in each student. When an assistant notices a signal from a student in the seat map, he goes to the desk to help or uses a chat system. We revised GUI and extended several functions in the tool. We carried out questionnaires for more than 10 assistants. We consider the replies and opinions for improvement.","PeriodicalId":410876,"journal":{"name":"2017 21st International Conference Information Visualisation (IV)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121181121","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Many real world data sets have data items with missing values. Values can be missing for many different reasons, such as sensor failure, respondents forgetting or refusing to answer a question in a survey, or a certain feature not being applicable to certain subsets of data. When visualizing data, some visualizations can easily handle missing values, while for others it is not obvious how to represent them without the resulting visualization being misleading. We give examples of different ways our system for interactive visual exploration of data handles missing data. These examples come from real world big data projects we took part in. Different ways to visualize missing values work well with different visualizations. Coordinated multiple views is a powerful way to visualize data with missing values, and having several views of the data helps explore the properties of the items with missing values.
{"title":"Visualizing Missing Values","authors":"Jonas Sjöbergh, Yuzuru Tanaka","doi":"10.1109/iV.2017.12","DOIUrl":"https://doi.org/10.1109/iV.2017.12","url":null,"abstract":"Many real world data sets have data items with missing values. Values can be missing for many different reasons, such as sensor failure, respondents forgetting or refusing to answer a question in a survey, or a certain feature not being applicable to certain subsets of data. When visualizing data, some visualizations can easily handle missing values, while for others it is not obvious how to represent them without the resulting visualization being misleading. We give examples of different ways our system for interactive visual exploration of data handles missing data. These examples come from real world big data projects we took part in. Different ways to visualize missing values work well with different visualizations. Coordinated multiple views is a powerful way to visualize data with missing values, and having several views of the data helps explore the properties of the items with missing values.","PeriodicalId":410876,"journal":{"name":"2017 21st International Conference Information Visualisation (IV)","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133925090","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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