Our ability to visualize scientific data has evolved significantly over the last 40 years. However, this advancement does not necessarily alleviate many common pitfalls in visualization for scientific journals, which ...
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Our ability to visualize scientific data has evolved significantly over the last 40 years. However, this advancement does not necessarily alleviate many common pitfalls in visualization for scientific journals, which can inhibit the ability of readers to effectively understand the information presented. To address this issue within the context of visualizing environmental data, we list ten guidelines for effective data visualization in scientific publications. These guidelines support the primary objective of data visualization, i.e. to effectively convey information. We believe that this small set of guidelines based on a review of key visualization literature can help researchers improve the communication of their results using effective visualization. Enhancement of environmental data visualization will further improve research presentation and communication within and across disciplines. (C) 2011 Elsevier Ltd. All rights reserved.
The purpose of this study was to show the data visualization of environmental factor in poultry farm. In poultry farm sector, the environmental factors around the cages is important to support the success of poultry f...
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data visualization makes data mean more through storytelling. Any data will have an inside story when it is addressed with relevant query. In this paper, GitHub data is collected, cleansed and visualized for its repos...
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Despite the rising popularity of automated visualization tools, existing systems tend to provide direct results which do not always fit the input data or meet visualization requirements. Therefore, additional specific...
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Despite the rising popularity of automated visualization tools, existing systems tend to provide direct results which do not always fit the input data or meet visualization requirements. Therefore, additional specification adjustments are still required in real-world use cases. However, manual adjustments are difficult since most users do not necessarily possess adequate skills or visualization knowledge. Even experienced users might create imperfect visualizations that involve chart construction errors. We present a framework, VizLinter, to help users detect flaws and rectify already-built but defective visualizations. The framework consists of two components, (1) a visualization linter, which applies well-recognized principles to inspect the legitimacy of rendered visualizations, and (2) a visualization fixer, which automatically corrects the detected violations according to the linter. We implement the framework into an online editor prototype based on Vega-Lite specifications. To further evaluate the system, we conduct an in-lab user study. The results prove its effectiveness and efficiency in identifying and fixing errors for data visualizations.
Here, the utility of Generative Topographic Maps (GTM) for data visualization, structure-activity modeling and database comparison is evaluated, on hand of subsets of the database of Useful Decoys (DUD). Unlike other ...
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Here, the utility of Generative Topographic Maps (GTM) for data visualization, structure-activity modeling and database comparison is evaluated, on hand of subsets of the database of Useful Decoys (DUD). Unlike other popular dimensionality reduction approaches like Principal Component Analysis, Sammon Mapping or Self-Organizing Maps, the great advantage of GTMs is providing data probability distribution functions (PDF), both in the high-dimensional space defined by molecular descriptors and in 2D latent space. PDFs for the molecules of different activity classes were successfully used to build classification models in the framework of the Bayesian approach. Because PDFs are represented by a mixture of Gaussian functions, the Bhattacharyya kernel has been proposed as a measure of the overlap of datasets, which leads to an elegant method of global comparison of chemical libraries.
Understanding how helpful a visualization is from experimental results is difficult because the observed performance is confounded with aspects of the study design, such as how useful the information that is visualize...
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Understanding how helpful a visualization is from experimental results is difficult because the observed performance is confounded with aspects of the study design, such as how useful the information that is visualized is for the task. We develop a rational agent framework for designing and interpreting visualization experiments. Our framework conceives two experiments with the same setup: one with behavioral agents (human subjects), and the other one with a hypothetical rational agent. A visualization is evaluated by comparing the expected performance of behavioral agents to that of a rational agent under different assumptions. Using recent visualization decision studies from the literature, we demonstrate how the framework can be used to pre-experimentally evaluate the experiment design by bounding the expected improvement in performance from having access to visualizations, and post-experimentally to deconfound errors of information extraction from errors of optimization, among other analyses.
Focusing on the intersection of visual data mapping and virtual globe software, this application is part digital library and part analytical tool. It combines data sets into a collaborative database and visualizes the...
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ISBN:
(纸本)9781595939982
Focusing on the intersection of visual data mapping and virtual globe software, this application is part digital library and part analytical tool. It combines data sets into a collaborative database and visualizes the information through Google Earth overlays. This user-centered interface makes previously hard-to-use public information (e.g. census data) accessible and easily interpretable. We are presenting an interactive application named GeoDatum that allows users to upload their databases and display this information through a number of visualization tools, either individually or comparatively. The software is an open source web application with multiple goals. Primarily, it is a central repository for both geographic boundaries and the data related to those boundaries. In addition, it gives users the ability to create dynamic visualizations viewable in Google Earth's extensible KML environment, complete with full 3D renderings and animations. The trade-off is that anyone who wants to use the application to generate visualizations will leave their data for public use. The software's core functionality is to allow users to import their own Shapefiles as well as CSVs containing data about the geographic areas. Shapefiles are an industry standard GIS format supported by numerous software applications including ArcGIS. This software will convert this information into KML files and Google Earth overlays. While it can display publicly available data sets, it also allows a user to include their own information, We will present a case study done with the Brooklyn Public Library that utilizes this tool in the service of a project on urban planning and analysis. thus making it a useful internal analytic tool for private interests as well. We will present a case study done with the Brooklyn Public Library that utilizes this tool in the service of a project on urban planning and analysis.
Kansei data are multi-dimensional data. It is difficult for an analyzer to interpret data whose dimensionality is higher than three because his/her vision is used only to one - three dimensions. visualization by reduc...
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Kansei data are multi-dimensional data. It is difficult for an analyzer to interpret data whose dimensionality is higher than three because his/her vision is used only to one - three dimensions. visualization by reducing the dimensionality of Kansei data to less than or equal to three dimensions could help the analyzer to understand the data.
Visual exploration has proven to be a powerful tool for multivariate data mining and knowledge discovery, Most visualization algorithms aim to find a projection from the data space down to a visually perceivable rende...
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Visual exploration has proven to be a powerful tool for multivariate data mining and knowledge discovery, Most visualization algorithms aim to find a projection from the data space down to a visually perceivable rendering space, To reveal all of the interesting aspects of multimodal data sets living in a high-dimensional space, a hierarchical visualization algorithm is introduced which allows the complete data set to be visualized at the top level, with clusters and subclusters of data points visualized at deeper levels, The methods involve hierarchical use of standard finite normal mixtures and probabilistic principal component projections, whose parameters are estimated using the expectation-maximization and principal component neural networks under the information theoretic criteria, We demonstrate the principle of the approach on several multimodal numerical data sets, and we then apply the method to the visual explanation in computer-aided diagnosis for breast cancer detection from digital mammograms.
Applications as diverse as home automation and agriculture depend on weather monitoring. The design and deployment of a low-cost weather station that uses IoT technology to gather, transmit, and visualize local weathe...
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