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Radiation dose tracking is becoming very important due to the popularity of computerized tomography (CT) scans. One of the challenges of radiation dose tracking is that there are several variables that affect the dose from the patient side, machine side, and procedures side. Although some tracking software programs exists, they are based on static analysis and cause integration errors due to the heterogeneity of Hospital Information Systems (HISs) and prevent users from obtaining accurate answers to their questions. In this paper, a visual analytic approach is utilized to track radiation dose data from computed tomography (CT) through the use of Tableau data visualization software. The web solution is evaluated in real-life scenarios by domain experts. The results show that the visual analytics approach improves the tracking process, as users completed the tasks with a 100% success rate. The process increased user satisfaction and also provided invaluable insight into the analytical process. [ABSTRACT FROM AUTHOR]

Background: As the number of tumor cases significantly increases, so does the quantity of tumor data. The mining and application of large-scale data have promoted the development of tumor big data. Among them, the visualization methods of tumor big data can well show the key information in a large volume of data and facilitate the human brain to receive information. Therefore, tumor big data visualization methods are a key part of the development of tumor big data. Process: This paper first summarizes the connotation, sources, characteristics, and applications of tumor big data, and expounds the current research status of tumor big data visualization at home and abroad. Then, this paper focuses on four mainstream visualization presentation methods of tumor big data, namely the visualization of tumor spatiotemporal data, the visualization of tumor hierarchy and network data, the visualization of tumor text data, and the visualization of multidimensional tumor data, and gives specific application scenarios. After this, the paper introduces the advantages, disadvantages, and scope of the use of five data visualization websites and software that can be easily obtained by readers. Finally, this paper analyzes the problems existing in tumor big data visualization, summarizes the visualization methods, and proposes the future of tumor big data visualization. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Forensic Medicine / Fayixue Zazhi is the property of Journal of Forensic Medicine Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The article discusses the implementation of the Spartan Experience Record (SER) at Michigan State University (MSU), which provides undergraduate students with a formal record of their co-curricular learning accomplishments. The SER aims to create a comprehensive dataset on what students learn in these co-curricular opportunities. To make the data more accessible, data visualization dashboards were created. The article offers key considerations for building data visualizations that support student learning outcomes and assessment goals. The challenges of customization in creating the dashboards are also discussed. Overall, the SER and data visualizations contribute to tracking and understanding the impact of co-curricular engagement on student success. [Extracted from the article]

Since 2006, the Bonneville Power Administration (BPA) Technology Innovation (TI) Office has applied roadmapping processes to help articulate the federal wholesale electric utility's technology research agenda. The TI Office team has evolved its tools, templates, and process steps considerably over the years in response to implementation challenges, shortcomings in deliverables derived from the process, and maturation opportunities enabled by data management and visualization software. Practioners within the TI Office have sustained their commitment to roadmapping during an era of significant evolution of the practice within industry and academia. The practice came out of product manufacturing environments in the 1960s, 1970s, and 1980s. Increasingly since the early 2000s, roadmapping has been applied outside this “traditional” realm, requiring trial, iteration, and customization of processes, tools, and deliverables to meet different requirements. The TI Office's use of roadmapping is one “nontraditional” variant because the agency is not in the business of generating profits by creating products in response to market demands. Instead, the TI Office has used roadmapping to communicate the agency's technology research, development, and demonstration agenda to the broader community—national laboratories, universities, manufacturers, etc.—so these external organizations can respond with proposals delivering products with the desired technology characteristics. These products, in turn, enable BPA to continue to fulfill its public service mission as an electric utility and government entity in providing safe, cost-effective, and reliable electricity throughout the Pacific Northwest region of the United States. [ABSTRACT FROM AUTHOR]

The paper present visualization techniques of properties of plant protection products via Tableau Data Visualization software for the purposes of safe and effective selection of pesticides towards different abiotic, biotic and antropogenic conditions. Although one plant protection product has many and different properties which determine its application, via Tableau was able all of these properties to be presented (showed) in the only one visualization, which make the process of selection of the right plant protection product extremely fast, easy and effective. Tableau Desktop is interactive data visualization software which is based on spreadsheets and relational databases. During the recent years this software founded in 2003 from Christian Chabot, Pat Hanrahan and Chris Stolte, researchers at the Department of Computer Science at Stanford University, became one of the most popular solution in the world from this type, used widely in all human areas for creation of high level graph-type data visualizations via easy to be used graphical user interface. In 2008 Tableau received award for "Best Business Intelligence Solution" by the Software and Information Industry Association. [ABSTRACT FROM AUTHOR]

Interactive visualization has become a powerful insight-revealing medium. However, the close dependency of interactive visualization on its data inhibits its shareability. Users have to choose between the two extremes of (i) sharing non-interactive dataless formats such as images and videos, or (ii) giving access to their data and software to others with no control over how the data will be used. In this work, we fill the gap between the two extremes and present a new system, called Loom. Loom captures interactive visualizations as standalone dataless objects. Users can interact with Loom objects as if they still have the original software and data that created those visualizations. Yet, Loom objects are completely independent and can therefore be shared online without requiring the data or the visualization software. Loom objects are efficient to store and use, and provide privacy preserving mechanisms. We demonstrate Loom's efficacy with examples of scientific visualization using Paraview, information visualization using Tableau, and journalistic visualization from New York Times. [ABSTRACT FROM AUTHOR]

"Doing economics" is an important theme of undergraduate economics programs. Capstone courses increasingly include instruction in "data literacy" and the STEM-related skills of quantitative and empirical methods. Because the professional discipline has moved in this direction and because of greater employer demand for these skills, data visualization is a key component of data literacy. Tableau is a free data visualization software widely used in the data analytics industry. In this article, the authors introduce an exercise that teaches the fundamental Tableau concepts and commands needed to create charts, assemble them in a dashboard, and tell a story of patterns observed in the data. The exercise assumes no prior experience in Tableau and is appropriate for undergraduate upper-level economics courses or an empirical methods course. [ABSTRACT FROM AUTHOR]

• During COVID-19 lockdown, the number of radiotherapy treatments had to be reduced. • Given number of delayed treatments, the post-crisis period should be anticipated. • Data visualization software allowed to predict when peak activity would happen. [ABSTRACT FROM AUTHOR]

Abstract: 3D representations are potentially useful under many circumstances, but suffer from long known perception and interaction challenges. Current immersive technologies, which combine stereoscopic displays and natural interaction, are being progressively seen as an opportunity to tackle this issue, but new guidelines and studies are still needed, especially regarding information visualization. Many proposed approaches are impractical for actual usage, resulting in user discomfort or requiring too much time or space. In this work, we implement and evaluate an alternative data exploration metaphor where the user remains seated and viewpoint change is only realisable through physical movements. All manipulation is done directly by natural mid‐air gestures, with the data being rendered at arm's reach. The virtual reproduction of the analyst's desk aims to increase immersion and enable tangible interaction with controls and two dimensional associated information. A comparative user study was carried out against a desktop‐based equivalent, exploring a set of 9 perception and interaction tasks based on previous literature and a multidimensional projection use case. We demonstrate that our prototype setup, named VirtualDesk, presents excellent results regarding user comfort and immersion, and performs equally or better in all analytical tasks, while adding minimal or no time overhead and amplifying user subjective perceptions of efficiency and engagement. Results are also contrasted to a previous experiment employing artificial flying navigation, with significant observed improvements. [ABSTRACT FROM AUTHOR]

With funding from the Sloan Foundation and Harvard Dataverse, the Harvard Center for Geographic Analysis (CGA) has developed a prototype spatio-temporal visualization platform called the Billion Object Platform or BOP. The goal of the project is to lower barriers for scholars who wish to access large, streaming, spatio-temporal datasets. The BOP is now loaded with the latest billion geo-tweets, and is fed a real-time stream of about 1 million tweets per day. The geo-tweets are enriched with sentiment and census/admin boundary codes when they enter the system. The system is open source and is currently hosted on Massachusetts Open Cloud (MOC), an OpenStack environment with all components deployed in Docker orchestrated by Kontena. This paper will provide an overview of the BOP architecture, which is built on an open source stack consisting of Apache Lucene, Solr, Kafka, Zookeeper, Swagger, scikit-learn, OpenLayers, and AngularJS. The paper will further discuss the approach used for harvesting, enriching, streaming, storing, indexing, visualizing and querying a billion streaming geo-tweets. [ABSTRACT FROM AUTHOR]

Rapid analytics and visualization software such as Tableau provide an opportunity for Access Services staff to utilize quantitative data on a routine basis to support decision-making about services and staffing. Data visualization tools make analyzing, updating, and sharing data analysis easier and faster than ever before. However, fullest utilization of these tools requires consistent, on demand access to data. This article discusses a strategic initiative at NYU Libraries to support data-driven decision-making by establishing a robust data warehouse paired with front-end access for library staff via Tableau Desktop. Specific application of this model to reporting, usage visualization, and workflow analysis in Access Services is discussed. [ABSTRACT FROM AUTHOR]

Geospatial data visualization systems have been predominantly through applications that are installed and run in a desktop environment. Over the last decade, with the advent of web technologies and its adoption by Geospatial community, the server-client model for data handling, data rendering and visualization respectively has been the most prevalent approach in Web-GIS. While the client devices have become functionally more powerful over the recent years, the above model has largely ignored it and is still in a mode of serverdominant computing paradigm. In this paper, an attempt has been made to develop and demonstrate LSIViewer - a simple, easy-to-use and robust online geospatial data visualisation system for the user's own data that harness the client's capabilities for data rendering and user-interactive styling, with a reduced load on the server. The developed system can support multiple geospatial vector formats and can be integrated with other web-based systems like WMS, WFS, etc. The technology stack used to build this system is Node.js on the server side and HTML5 Canvas and JavaScript on the client side. Various tests run on a range of vector datasets, upto 35MB, showed that the time taken to render the vector data using LSIViewer is comparable to a desktop GIS application, QGIS, over an identical system. [ABSTRACT FROM AUTHOR]

The article talks about two data visualization tools that are linked to large databases of American first names and demonstrate how they can be used as an interactive introduction in an undergraduate class in sociolinguistics and/or dialectology. Topics discussed include the databases forming a versatile teaching aid that doesn't need to be confined to classrooms teaching variationist sociolinguistics specifically.

Due to their trans-modal affordances, techniques mainly used for the production of glitch art such as pixel sorting and data-bending are potential data visualization tools that can be effectively adapted to the representation of abstract relations. To demonstrate this assertion, we present a method intended for the visualization of data through these techniques. The method presented here consists in sorting the composite pixels of greyscale images to make evident relationships between pixels that otherwise would be impossible to perceive. Here, we use this method to arrange an array of images in a very specific order, but this is only one of the potential applications that this method could have. [ABSTRACT FROM AUTHOR]

Copyright of Scientific Papers of Silesian University of Technology. Organization & Management / Zeszyty Naukowe Politechniki Slaskiej. Seria Organizacji i Zarzadzanie is the property of Silesian Technical University, Organisation & Management Faculty and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The Large Helical Device (LHD) at the National Institute for Fusion Science (NIFS) is the world’s largest superconducting helical fusion device, providing a scientific research center to elucidate important physics research such as plasma transport, turbulence dynamics, and other topics. Furthermore, many types of advanced diagnostic devices are used to measure the confinement plasma characteristics, and these valuable physical data are registered over the 131,000 discharges in the LHD database. However, it is difficult to investigate the experimental data even though much physical data has been registered. In order to improve the efficiency for investigating plasma physics in LHD, we have developed a new data visualization software, MyView2, which consists of Python-based modules that can be easily set up and updated. MyView2 provides immediate access to experimental results, cross-shot analysis, and a collaboration point for scientific research. In particular, the MyView2 software is a portable structure for making viewable LHD experimental data in on- and off-site web servers, which is a capability not previously available in any general use tool. We will also discuss the benefits of using the MyView2 software for in-depth analysis of LHD experimental data. [ABSTRACT FROM AUTHOR]

Data visualization has a critical role in the advancement of modern data analytics. Visualization lends assurances to data validity and completeness, as well as to the effectiveness of cleaning and aggregation tactics. It provides the means by which to explore and discover relationships otherwise hidden from default assumptions in statistical modeling. Strong visualization is also fundamental to end-result conveyance and audience interpretation. But how can one ensure that strength? How can one avoid developing representations that are marginal in value, or worse misleading? In this paper, I will discuss theory, evidence, and practical approaches to managing data visualization development, viewing data visualization not simply as an outcome but as a continuous process and facet of organizational culture. [ABSTRACT FROM AUTHOR]

Although there are many systems that have implemented customer behavior analytics, it's still an upcoming and unexplored market that has greater potential for better advancements. Big data is one of the most rising technology trends that have the capability for significantly changing the way business organizations use customer behavior to analyze and transform it into valuable insights. Even decision trees can be used efficiently for analyzing data. At the end of this paper, a proposed Map Reduce implementation of well-known statistical classifier, C4.5 decision tree algorithm has been proposed. Apart from this, the system aims to implement Customer data visualization using Data Driven Documents (d3.js) which allows us to build well customized graphics. [ABSTRACT FROM AUTHOR]

This application is about Event Management Using Data Visualization Tool provides a simple interface for the overview of various Event Management companies. Event Management means managing different types of events such as festivals, weddings, conferences, ceremonies, formal parties, concerts. A proper event plan is required to make any event a grand success. The event management companies are developed to fulfill all needs such as budgeting, scheduling, coordinating transportation and parking, arranging for speakers or entertainers, arranging decor, event security, catering. Since each and every event will be different from each other event management companies are required for effective event management. This application provides a list of event management companies which are available in Vijayawada, rajmundry and vizag. All the required details like Type of services they provide, address (location), time of availability, contact and ratings of different companies are provided in this application. [ABSTRACT FROM AUTHOR]

This article outlines the use of a collection mapping model of collection assessment in which data visualization tools were utilized in order to provide a unified portrait of a complicated multi-disciplinary collection located in several different physical locations across the Libraries of the University of California Riverside. Through the use of freely-available data visualization software, the massive amount of data generated by collection-centered inventory of the Libraries' Latin American Studies collection can be assessed in a number of different dimensions, clearly illustrating the collection's strengths to stakeholders both within and outside of the libraries. [ABSTRACT FROM AUTHOR]

The widespread adoption of computers and Internet in our life has reached the classrooms, where computer-supported collaborative learning (CSCL) based on wikis offers new ways of collaboration and encourages student participation. When the number of contributions from students increases, traditional assessment procedures of e-learning settings suffer from scalability problems. In a wiki-based learning experience, automatic tools are required to support the assessment of such huge amounts of data. In this work, we present StatMediaWiki, a tool that collects and aggregates information that helps to analyze a MediaWiki installation. It generates charts, tables and different statistics enabling easy analysis of wiki evolution. We have used StatMediaWiki in a Higher Education course and present the results obtained in this case study. [ABSTRACT FROM PUBLISHER]

For irregularly measured time-series data, the measurement frequency or interval is as crucial information as measurements are. A well-known time-series visualization such as the line graph is good at showing an overall temporal pattern of change; however, it is not so effective in revealing the measurement frequency/interval while likely giving illusory confidence in values between measurements. In contrast, the bar graph is more effective in showing the frequency/interval, but less effective in showing an overall pattern than the line graph. We integrate the line graph and bar graph in a unified visualization model, called a ripple graph, to take the benefits of both of them with enhanced graphical integrity. Based on the ripple graph, we implemented an interactive time-series data visualization tool, called Stroscope, which facilitates multi-scale visualizations by providing users with a graphical widget to interactively control the integrated visualization model. We evaluated the visualization model (i.e., the ripple graph) through a controlled user study and Stroscope through long-term case studies with neurologists exploring large blood pressure measurement data of stroke patients. Results from our evaluations demonstrate that the ripple graph outperforms existing time-series visualizations, and that Stroscope has the efficacy and potential as an effective visual analysis tool for (irregularly) measured time-series data. [ABSTRACT FROM AUTHOR]

The Allen Brain Atlas-Driven Visualizations (ABADV) is a publicly accessible web-based tool created to retrieve and visualize expression energy data from the Allen Brain Atlas (ABA) across multiple genes and brain structures. Though the ABA offers their own search engine and software for researchers to view their growing collection of online public data sets, including extensive gene expression and neuroanatomical data from human and mouse brain, many of their tools limit the amount of genes and brain structures researchers can view at once. To complement their work, ABADV generates multiple pie charts, bar charts and heat maps of expression energy values for any given set of genes and brain structures. Such a suite of free and easy-to-understand visualizations allows for easy comparison of gene expression across multiple brain areas. In addition, each visualization links back to the ABA so researchers may view a summary of the experimental detail. ABADV is currently supported on modern web browsers and is compatible with expression energy data from the Allen Mouse Brain Atlas in situ hybridization data. By creating this web application, researchers can immediately obtain and survey numerous amounts of expression energy data from the ABA, which they can then use to supplement their work or perform meta-analysis. In the future, we hope to enable ABADV across multiple data resources. [ABSTRACT FROM AUTHOR]

High-dimensional data visualization has been attracting much attention. To fully test related software and algorithms, researchers require a diverse pool of data with known and desired features. Test data do not always provide this, or only partially. Here we propose the paradigm WYDIWYGS (What You Draw Is What You Get). Its embodiment, SketchPadND, is a tool that allows users to generate high-dimensional data in the same interface they also use for visualization. This provides for an immersive and direct data generation activity, and furthermore it also enables users to interactively edit and clean existing high-dimensional data from possible artifacts. SketchPadND offers two visualization paradigms, one based on parallel coordinates and the other based on a relatively new framework using an N-D polygon to navigate in high-dimensional space. The first interface allows users to draw arbitrary profiles of probability density functions along each dimension axis and sketch shapes for data density and connections between adjacent dimensions. The second interface embraces the idea of sculpting. Users can carve data at arbitrary orientations and refine them wherever necessary. This guarantees that the data generated is truly high-dimensional. We demonstrate our tool's usefulness in real data visualization scenarios. [ABSTRACT FROM AUTHOR]

We present MotionExplorer, an exploratory search and analysis system for sequences of human motion in large motion capture data collections. This special type of multivariate time series data is relevant in many research fields including medicine, sports and animation. Key tasks in working with motion data include analysis of motion states and transitions, and synthesis of motion vectors by interpolation and combination. In the practice of research and application of human motion data, challenges exist in providing visual summaries and drill-down functionality for handling large motion data collections. We find that this domain can benefit from appropriate visual retrieval and analysis support to handle these tasks in presence of large motion data. To address this need, we developed MotionExplorer together with domain experts as an exploratory search system based on interactive aggregation and visualization of motion states as a basis for data navigation, exploration, and search. Based on an overview-first type visualization, users are able to search for interesting sub-sequences of motion based on a query-by-example metaphor, and explore search results by details on demand. We developed MotionExplorer in close collaboration with the targeted users who are researchers working on human motion synthesis and analysis, including a summative field study. Additionally, we conducted a laboratory design study to substantially improve MotionExplorer towards an intuitive, usable and robust design. MotionExplorer enables the search in human motion capture data with only a few mouse clicks. The researchers unanimously confirm that the system can efficiently support their work. [ABSTRACT FROM AUTHOR]

To analyze data such as the US Federal Budget or characteristics of the student population of a University it is common to look for changes over time. This task can be made easier and more fruitful if the analysis is performed by grouping by attributes, such as by Agencies, Bureaus and Accounts for the Budget, or Ethnicity, Gender and Major in a University. We present TreeVersity2, a web based interactive data visualization tool that allows users to analyze change in datasets by creating dynamic hierarchies based on the data attributes. TreeVersity2 introduces a novel space filling visualization (StemView) to represent change in trees at multiple levels - not just at the leaf level. With this visualization users can explore absolute and relative changes, created and removed nodes, and each node's actual values, while maintaining the context of the tree. In addition, TreeVersity2 provides overviews of change over the entire time period, and a reporting tool that lists outliers in textual form, which helps users identify the major changes in the data without having to manually setup filters. We validated TreeVersity2 with 12 case studies with organizations as diverse as the National Cancer Institute, Federal Drug Administration, Department of Transportation, Office of the Bursar of the University of Maryland, or eBay. Our case studies demonstrated that TreeVersity2 is flexible enough to be used in different domains and provide useful insights for the data owners. A TreeVersity2 demo can be found at https://treeversity.cattlab.umd.edu. [ABSTRACT FROM AUTHOR]

The VisTrails system supports the creation of reproducible experiments. VisTrails integrates data acquisition, derivation, analysis, and visualization as executable components throughout the scientific exploration process, and through systematic provenance capture, it makes it easier to generate and share reproducible results. Using VisTrails, authors can link results to their provenance, reviewers can assess the experiment's validity, and readers can repeat and utilize the computations. [ABSTRACT FROM AUTHOR]

In research on American politics, the use of geographic information systems (GIS) is most often thought of in connection with redistricting and the study of election results. In the past ten years, political scientists have realized that GIS can help them address many research questions and data analysis tasks quite apart from these traditional applications. These include the analysis of point patterns and the detection of clustering; the study of diffusion of influence; and the measurement of spatial relationships involving key constructs such as proximity and distance, flow, and interaction. GIS tools also prove to be the exploratory complements to the suite of tools being used in spatial econometrics to test explicit hypotheses about the impact of geography and spatial arrangement on political outcomes. [ABSTRACT FROM AUTHOR]

Mondrian is state-of-the-art statistical data visualization software featuring modern interactive visualization techniques for a wide range of data types. This article reviews the capabilities, functionality, and interactive properties of this software package. Key features of Mondrian are illustrated with data from the Programme for International Student Assessment (PISA) and for item analysis applications. [ABSTRACT FROM AUTHOR]

• Import of measured and simulated dosimetry data to a single open-source environment • Simultaneous data visualization from multiple sources • Automatic percentage depth dose and beam profile quality parameter determination • Gamma index, distance to agreement and dose difference analysis • Additional tools for filtering, scaling This article presents Profeel, a Matlab (MathWorks Inc., MA) based open source dosimetry data visualization and analysis software. Profeel aims to support quality assurance, dosimetry and research in the field of radiotherapy by providing an environment to visualize, process and analyse measured and simulated dosimetry data from several data sources used in radiotherapy practice and research. The processing and analysis tools are based on routinely used dosimetry analysis methods, such as gamma analysis, different data normalizations and data filtering. Additionally the Profeel performs an automatic 1 dimensional profile and percentage depth dose analysis in accordance with International Electrotechnical Commission definitions. All data can be operated by user created custom functions and lower dimensionality data can be extracted from volume doses and dose planes. Profeel supports data import in all 3 dimensions and offers an intuitive user interface to perform data visualization, processing and analysis between simulated and measured data. Profeel and its source code are distributed free of charge under the General Public Licence (GPL). Profeel has shown to be an agile tool for fulfilling various needs of several researchers and since Profeel is under constant development and is an open source project, community needs, issues and bug reports are taken into account in the development. [ABSTRACT FROM AUTHOR]

The intrinsic characteristics of humanities research require technological support and software assistance that also necessarily goes through the analysis of textual narratives. When these narratives become increasingly complex, pragmatics analysis (i.e., at discourse or argumentation levels) assisted by software is a great ally in the digital humanities. In recent years, solutions have been developed from the information visualization domain to support discourse analysis or argumentation analysis of textual sources via software, with applications in political speeches, debates, online forums, but also in written narratives, literature or historical sources. This paper presents a wide and interdisciplinary systematic literature review (SLR), both in software-related areas and humanities areas, on the information visualization and the software solutions adopted to support pragmatics textual analysis. As a result of this review, this paper detects weaknesses in existing works on the field, especially related to solutions' availability, pragmatic framework dependence and lack of information sharing and reuse software mechanisms. The paper also provides some software guidelines for improving the detected weaknesses, exemplifying some guidelines in practice through their implementation in a new web tool, Viscourse. Viscourse is conceived as a complementary tool to assist textual analysis and to facilitate the reuse of informational pieces from discourse and argumentation text analysis tasks. [ABSTRACT FROM AUTHOR]

The article reviews the mapping and data visualization program Social Explorer, published by Social Explorer, located at www.socialexplorer.com.

The SuperCDMS experiment (Super Cryogenic Dark Matter Search) searches for low-mass dark matter and will be located approximately 2 km deep underground in the Sudbury Neutrino Observatory (SNOLAB, Canada). The planned kilogram scale detector payload is a mix of germanium and silicon detectors placed in four towers. The data acquisition (DAQ) will contain Detector Control and Readout Cards (DCRCs) connected to detectors and a flexible triggering scheme containing hardware and software triggers. Slow control, environmental monitoring and data quality checking will be integrated into the experimental framework. The near-to-live data quality system enables high experimental efficiency. Data visualization software is being developed for the data quality system. The SuperCDMS experiment, its detector payload and data acquisition system, will be discussed in the presentation. [ABSTRACT FROM AUTHOR]

El artículo discurre sobre el proceso de visualizar datos y el desarrollo del periodismo digital. El autor comenta sobre el uso de Internet en la visualización de datos, incluyendo la proliferación de aplicaciones como iCharts, Google Charts y GetBulbs, las cuales ayudan a construir data visual.

The article offers information on the importance of genetic data visualization. It reports that the process of data visualization aimed at providing facility to users for exploring and explaining data by using interactive software which can be helpful in recognizing genetic patterns. It informs that the process helps the user to easily understanddata as it possesses a well-designed graphical depictions of information with simple perceptual inferences.

Mobile phones and devices, with their constant presence, data connectivity, and multiple intrinsic sensors, can support around-the-clock chronic disease prevention and management that is integrated with daily life. These mobile health (mHealth) devices can produce tremendous amounts of location-rich, real-time, high-frequency data. Unfortunately, these data are often full of bias, noise, variability, and gaps. Robust tools and techniques have not yet been developed to make mHealth data more meaningful to patients and clinicians. To be most useful, health data should be sharable across multiple mHealth applications and connected to electronic health records. The lack of data sharing and dearth of tools and techniques for making sense of health data are critical bottlenecks limiting the impact of mHealth to improve health outcomes. We describe Open mHealth, a nonprofit organization that is building an open software architecture to address these data sharing and "sense-making" bottlenecks. Our architecture consists of open source software modules with well-defined interfaces using a minimal set of common metadata. An initial set of modules, called InfoVis, has been developed for data analysis and visualization. A second set of modules, our Personal Evidence Architecture, will support scientific inferences from mHealth data. These Personal Evidence Architecture modules will include standardized, validated clinical measures to support novel evaluation methods, such as n-of-1 studies. All of Open mHealth's modules are designed to be reusable across multiple applications, disease conditions, and user populations to maximize impact and flexibility. We are also building an open community of developers and health innovators, modeled after the open approach taken in the initial growth of the Internet, to foster meaningful cross-disciplinary collaboration around new tools and techniques. An open mHealth community and architecture will catalyze increased mHealth efficiency, effectiveness, and innovation. [ABSTRACT FROM AUTHOR]