The Experts below are selected from a list of 24258 Experts worldwide ranked by ideXlab platform
Nils Gehlenborg - One of the best experts on this subject based on the ideXlab platform.
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interactive visual exploration and refinement of cluster assignments
BMC Bioinformatics, 2017Co-Authors: Nils Gehlenborg, Michael Kern, Chris R JohnsonAbstract:With ever-increasing amounts of data produced in biology research, scientists are in need of efficient data analysis methods. Cluster analysis, combined with visualization of the results, is one such method that can be used to make sense of large data volumes. At the same time, cluster analysis is known to be imperfect and depends on the choice of algorithms, parameters, and distance measures. Most clustering algorithms don’t properly account for ambiguity in the source data, as records are often assigned to discrete clusters, even if an assignment is unclear. While there are metrics and visualization techniques that allow analysts to compare clusterings or to judge cluster quality, there is no comprehensive method that allows analysts to evaluate, compare, and refine cluster assignments based on the source data, derived scores, and contextual data. In this paper, we introduce a method that explicitly visualizes the quality of cluster assignments, allows comparisons of clustering results and enables analysts to manually curate and refine cluster assignments. Our methods are applicable to matrix data clustered with partitional, hierarchical, and fuzzy clustering algorithms. Furthermore, we enable analysts to explore clustering results in context of other data, for example, to observe whether a clustering of genomic data results in a meaningful differentiation in phenotypes. Our methods are integrated into Caleydo StratomeX, a popular, web-based, disease subtype analysis tool. We show in a Usage Scenario that our approach can reveal ambiguities in cluster assignments and produce improved clusterings that better differentiate genotypes and phenotypes.
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interactive visual exploration and refinement of cluster assignments
bioRxiv, 2017Co-Authors: Michael Kern, Nils Gehlenborg, Chris R JohnsonAbstract:Background: With ever-increasing amounts of data produced in biology research, scientists are in need of efficient data analysis methods. Cluster analysis, combined with visualization of the results, is one such method that can be used to make sense of large data volumes. At the same time, cluster analysis is known to be imperfect and depends on the choice of algorithms, parameters, and distance measures. Most clustering algorithms don9t properly account for ambiguity in the source data, as records are often assigned to discrete clusters, even if an assignment is unclear. While there are metrics and visualization techniques that allow analysts to compare clusterings or to judge cluster quality, there is no comprehensive method that allows analysts to evaluate, compare, and refine cluster assignments based on the source data, derived scores, and contextual data. Results: In this paper, we introduce a method that explicitly visualizes the quality of cluster assignments, allows comparisons of clustering results and enables analysts to manually curate and refine cluster assignments. Our methods are applicable to matrix data clustered with partitional, hierarchical, and fuzzy clustering algorithms. Furthermore, we enable analysts to explore clustering results in context of other data, for example, to observe whether a clustering of genomic data results in a meaningful differentiation in phenotypes. Conclusions: Our methods are integrated into Caleydo StratomeX, a popular, web-based, disease subtype analysis tool. We show in a Usage Scenario that our approach can reveal ambiguities in cluster assignments and produce improved clusterings that better differentiate genotypes and phenotypes.
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avocado visualization of workflow derived data provenance for reproducible biomedical research
IEEE VGTC Conference on Visualization, 2016Co-Authors: Holger Stitz, Stefan Luger, Marc Streit, Nils GehlenborgAbstract:A major challenge in data-driven biomedical research lies in the collection and representation of data provenance information to ensure that findings are reproducibile. In order to communicate and reproduce multi-step analysis workflows executed on datasets that contain data for dozens or hundreds of samples, it is crucial to be able to visualize the provenance graph at different levels of aggregation. Most existing approaches are based on node-link diagrams, which do not scale to the complexity of typical data provenance graphs. In our proposed approach, we reduce the complexity of the graph using hierarchical and motif-based aggregation. Based on user action and graph attributes, a modular degree-of-interest (DoI) function is applied to expand parts of the graph that are relevant to the user. This interest-driven adaptive approach to provenance visualization allows users to review and communicate complex multi-step analyses, which can be based on hundreds of files that are processed by numerous workflows. We have integrated our approach into an analysis platform that captures extensive data provenance information, and demonstrate its effectiveness by means of a biomedical Usage Scenario.
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avocado visualization of workflow derived data provenance for reproducible biomedical research
bioRxiv, 2016Co-Authors: Holger Stitz, Stefan Luger, Marc Streit, Nils GehlenborgAbstract:A major challenge of data-driven biomedical research lies in the collection and representation of data provenance information to ensure reproducibility of findings. In order to communicate and reproduce multi-step analysis workflows executed on datasets that contain data for dozens or hundreds of samples, it is crucial to be able to visualize the provenance graph at different levels of aggregation. Most existing approaches are based on node-link diagrams, which do not scale to the complexity of typical data provenance graphs. In our proposed approach we reduce the complexity of the graph using hierarchical and motif-based aggregation. Based on user action and graph attributes a modular degree-of-interest (DoI) function is applied to expand parts of the graph that are relevant to the user. This interest-driven adaptive provenance visualization approach allows users to review and communicate complex multi-step analyses, which can be based on hundreds of files that are processed by numerous workflows. We integrate our approach into an analysis platform that captures extensive data provenance information and demonstrate its effectiveness by means of a biomedical Usage Scenario.
Constantine Stephanidis - One of the best experts on this subject based on the ideXlab platform.
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usability inspection of the wardinhand prototype
Lecture Notes in Computer Science, 2005Co-Authors: Panagiotis Karampelas, Demosthenes Akoumianakis, Constantine StephanidisAbstract:This Chapter describes the process and outcomes of the evaluation of a user interface prototype running on a Personal Digital Assistant (PDA). The prototype was developed in the context of the IST-funded project WardInHand and implements a PDA version of a ward information system. The evaluation was based on a Usage Scenario comprising mock-ups and textual descriptions of the typical tasks of the system. Although the evaluation revealed a broad range of usability problems, in this Chapter we consider only those which feature prominently in the vast majority of PDA-based applications, such as adaptability, individualisation, user profiling, alternative dialogue styles, localisation, etc., and propose design solutions of general purpose, as a basis for improved design practice.
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chapter 16 usability inspection of the wardinhand prototype
2005Co-Authors: Panagiotis Karampelas, Constantine Stephanidis, Demosthenes AkoumianakisAbstract:This Chapter describes the process and outcomes of the evaluation of a user interface prototype running on a Personal Digital Assistant (PDA). The prototype was developed in the context of the IST-funded project WardInHand and implements a PDA version of a ward information system. The evaluation was based on a Usage Scenario comprising mock-ups and textual descriptions of the typical tasks of the system. Although the evaluation revealed a broad range of usability problems, in this Chapter we consider only those which feature prominently in the vast majority of PDA-based applications, such as adaptability, individualisation, user profiling, alternative dialogue styles, localisation, etc., and propose design solutions of general purpose, as a basis for improved design practice.
Lu Zhang - One of the best experts on this subject based on the ideXlab platform.
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mapo mining and recommending api Usage patterns
European Conference on Object-Oriented Programming, 2009Co-Authors: Hao Zhong, Lu ZhangAbstract:To improve software productivity, when constructing new software systems, programmers often reuse existing libraries or frameworks by invoking methods provided in their APIs. Those API methods, however, are often complex and not well documented. To get familiar with how those API methods are used, programmers often exploit a source code search tool to search for code snippets that use the API methods of interest. However, the returned code snippets are often large in number, and the huge number of snippets places a barrier for programmers to locate useful ones. In order to help programmers overcome this barrier, we have developed an API Usage mining framework and its supporting tool called MAPO (Mining API Usage Pattern from Open source repositories) for mining API Usage patterns automatically. A mined pattern describes that in a certain Usage Scenario, some API methods are frequently called together and their Usages follow some sequential rules. MAPO further recommends the mined API Usage patterns and their associated code snippets upon programmers' requests. Our experimental results show that with these patterns MAPO helps programmers locate useful code snippets more effectively than two state-of-the-art code search tools. To investigate whether MAPO can assist programmers in programming tasks, we further conducted an empirical study. The results show that using MAPO, programmers produce code with fewer bugs when facing relatively complex API Usages, comparing with using the two state-of-the-art code search tools.
Alex Endert - One of the best experts on this subject based on the ideXlab platform.
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a user based visual analytics workflow for exploratory model analysis
arXiv: Human-Computer Interaction, 2018Co-Authors: Dylan Cashman, Shah Rukh Humayoun, Florian Heimerl, Kendall Park, Subhajit Das, John F Thompson, Bahador Saket, Abigail Mosca, John T Stasko, Alex EndertAbstract:Many visual analytics systems allow users to interact with machine learning models towards the goals of data exploration and insight generation on a given dataset. However, in some situations, insights may be less important than the production of an accurate predictive model for future use. In that case, users are more interested in generating of diverse and robust predictive models, verifying their performance on holdout data, and selecting the most suitable model for their Usage Scenario. In this paper, we consider the concept of Exploratory Model Analysis (EMA), which is defined as the process of discovering and selecting relevant models that can be used to make predictions on a data source. We delineate the differences between EMA and the well-known term exploratory data analysis in terms of the desired outcome of the analytic process: insights into the data or a set of deployable models. The contributions of this work are a visual analytics system workflow for EMA, a user study, and two use cases validating the effectiveness of the workflow. We found that our system workflow enabled users to generate complex models, to assess them for various qualities, and to select the most relevant model for their task.
Panagiotis Karampelas - One of the best experts on this subject based on the ideXlab platform.
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usability inspection of the wardinhand prototype
Lecture Notes in Computer Science, 2005Co-Authors: Panagiotis Karampelas, Demosthenes Akoumianakis, Constantine StephanidisAbstract:This Chapter describes the process and outcomes of the evaluation of a user interface prototype running on a Personal Digital Assistant (PDA). The prototype was developed in the context of the IST-funded project WardInHand and implements a PDA version of a ward information system. The evaluation was based on a Usage Scenario comprising mock-ups and textual descriptions of the typical tasks of the system. Although the evaluation revealed a broad range of usability problems, in this Chapter we consider only those which feature prominently in the vast majority of PDA-based applications, such as adaptability, individualisation, user profiling, alternative dialogue styles, localisation, etc., and propose design solutions of general purpose, as a basis for improved design practice.
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chapter 16 usability inspection of the wardinhand prototype
2005Co-Authors: Panagiotis Karampelas, Constantine Stephanidis, Demosthenes AkoumianakisAbstract:This Chapter describes the process and outcomes of the evaluation of a user interface prototype running on a Personal Digital Assistant (PDA). The prototype was developed in the context of the IST-funded project WardInHand and implements a PDA version of a ward information system. The evaluation was based on a Usage Scenario comprising mock-ups and textual descriptions of the typical tasks of the system. Although the evaluation revealed a broad range of usability problems, in this Chapter we consider only those which feature prominently in the vast majority of PDA-based applications, such as adaptability, individualisation, user profiling, alternative dialogue styles, localisation, etc., and propose design solutions of general purpose, as a basis for improved design practice.
