The HTML5 JavaScript Model (Visualizing the Web)

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The graph queries are translated into Cypher and run on the database. JS : the JavaScript port of the Processing visual programming language. It allows web browsers to display animations, visual applications, games and other graphical rich content without any plug-ins. Protovis : a JavaScript library released under the BSD License, to compose custom views of data with simple marks such as bars and dots.

Protovis is no longer under active development. Py3Plex : a Python library released under the BSD License, providing algorithms for decomposition, visualization and analysis of graph data. PyGraphistry : a Python visual graph analytics library to extract, transform, and load big graphs into Graphistry's cloud-based graph explorer.

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Rappid is the commercial extension to the JointJS Core library. It lets developers publish networks on Web pages and integrate network exploration in rich Web applications. Soba is a 2D plotting library integrated with Sushi written in JavaScript. Statnet : an integrated set of R tools for the representation, visualization, analysis, and simulation of network data. It is released under GPL Tom Sawyer Perspectives : a commercial graph SDK with a graphics-based design and preview environment. The platform integrates enterprise data sources with a graph visualization, layout, and analysis technology.

Tulip : a information visualization framework dedicated to the analysis and visualization of relational data. JS : is a JavaScript browser-based visualization library released under the Apache 2. The library enable manipulation of and interaction with large amounts of dynamic data. VivaGraphJS : a graph drawing library for JavaScript designed to support different rendering engines and layout algorithms.

Bio : Elise Devaux is a tech-enthusiast and marketing project manager. She currently works with Linkurious' team and partners to cover the emerging graph technology use cases. By subscribing you accept KDnuggets Privacy Policy. Tags: D3. Previous post. So I sought data on who is. Latest News Webinar: Build auto-adaptive machine learning models wi What is Hierarchical Clustering?

What Challenges Shou Recently some web-based CIVS have been implemented that attempt to achieve real-time synchronization by rendering the image volumes on the server side and sending a representation of the visualization to each collaborator's web browser as a series of 2D images or streaming video mainly JPEG, PNG, or MPEG formats Kaspar et al. However, this server-side rendering technique is not suitable for the so-called Fully-Shared-Control real-time CIVS in which all the collaborators have control over the parameters associated with a given interactive visualization e.

The main reason for this is that it requires continuously sending relatively heavy data over the network after each single user-data interaction that modifies the visualization parameters. This makes the application not only highly sensitive to user-specific network latency but doesn't scale well when the number of concurrent users increases.

Therefore, a distributed client-side rendering approach would be preferable for fast real-time all-users interactivity. New advances in core web application technologies such as the modern web browsers' universal support of ECMAScript 5 and 6 , CSS3 and HTML5 APIs have made it much more feasible to implement efficient graphical image volume rendering and visualization as well as real-time communication purely in client-side JavaScript Mwalongo et al.

Indeed a few powerful client-side JavaScript libraries that can perform in-browser rendering and visualization of 3D neuroimage volumes have already emerged and are freely available as open-source projects Sherif et al. In particular, in this paper we make use of the popular XTK toolkit which was developed by our team at the Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Childrens Hospital 1 and can be freely downloaded from the web 2 Haehn et al.

Despite the ready availability of client-side JavaScript rendering libraries we only know of a single attempt at implementing a web-based real-time CIVS based on a client-side rendering and visualization approach.

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However, Slice:Drop was developed mostly as a prototypical concept showcase and is less modular and difficult to reuse in other applications. In addition, Slice:Drop uses third party services provided by Dropbox and early implementations required data to be publicly shared without any restrictions which may lead to undesirable data leaking to non-intended Internet users.

In this article we propose a new web-based technological solution in many ways a logical successor to Slice:Drop to the problem of implementing efficient real-time collaborative neuroimage visualization. As with Slice:Drop, here we adopt a client-side rendering and visualization approach based on the XTK toolkit. We propose a portable viewing application that can easily be embedded into larger systems, such as ChRIS [also developed at Boston Children's Hospital Pienaar et al.

Real-time synchronization and communication among remote visualization instances is then managed through the Google Drive Realtime API.

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We provide a small set of reusable client-side object-oriented JavaScript modules named viewerjs 4 , fmjs 5 , and gcjs 6 that are freely accessible as open source software from our Github organization repositories 7. These JavaScript modules have already been instantiated in the implementation of a distributed collaborative neuroimage visualization application called MedView that is delivered to the users over the web without requiring the installation of any extra software or browser plugin.

The source code of this application and a built and deployed version are also hosted in our Github repositories. It allows multiple physically distant physicians or researchers to cooperate in real-time to reach a diagnosis or scientific conclusion. The MedView application described in this paper provides a web-based viewer for common medical image formats.

When clients visit the MedView website 8 , the required functionality is downloaded into, and executed by, the browser. All data remains local—only the viewer source code in the form of Javascript programming is fetched remotely. In addition to image rendering, MedView provides for real-time collaboration and sharing of a common image cursor between all participants in a collaborative session.

From an application programming perspective, an application like MedView is rather lightweight and most of the application visualization logic and behavior is provided by the viewerjs. This library is in turn reliant on several subcomponents—a low level visualization component XTK , a collaboration component gcjs , and a unified file management system fmjs , see Figure 1. Figure 1. The main logical components of Medview.

The viewerjs library provides most of the services that an application such as MedView might require. Multiple viewers can quickly be constructed on viewerjs for example a FreeSurfer surface viewer, a tractography viewer, etc. Internally, viewerjs uses low level graphical libraries XTK and AMI , a real time collaboration library gcjs and a file management library fmjs.

Note that the colors in the boxes are for ease of illustration and similarly colored boxes are not functionally related. Currently, the popular open-source XTK toolkit is used by viewerjs for low level graphic services. XTK is a fully client-side JavaScript library, which means it runs entirely in the web browser without requiring any special back-end infrastructure. This API is well documented with an extensive set of demos, lessons and practical code examples 9. AMI features a highly efficient visualization pipeline and is built on top of the powerful threejs 11 JavaScript library.

Subsequent versions of viewerjs will transition to AMI for more powerful visualization operations. Importantly, the final application like MedView ideally does not need to call primitives at the rendering library directly. The viewerjs library exposes a viewerjs. Viewer class. The viewerjs. The following code shows the simplicity of the method calls:.

Viewer divId ;. The VObj can asynchronously load more than one neuroimage volume specified by the imgFileArr variable passed to the addData method. The imgFileArr is an array of custom file objects where each object entry has the following properties:. Using the fmjs library, the VObj can load image data from diverse sources such as a remote service using the provided url , a local filesystem using the file property or the Google Drive storage service using the cloudId property. Using viewerjs , MedView constructs a graphical user interface GUI comprising the main functional components as shown in Figure 2.

It contains a tool bar at top with action buttons using toolbarjs 12 , a central neuroimage visualization square provided by rboxjs 13 that contains individual interactive visualizers, rendererjs 14 , and on each side, two floating thumbnail bars thbarjs 15 with an automatically generated snapshot image of the middle slice for each neuroimage volume. Currently the visualization objects rendererjs only provide cross-sectional slice rendering of the 3D datasets. These just use two types of XTK 's objects that are closely associated, the X.

Volume that contains the 3D volume data and the X. Figure 2. At the top is a toolbar in blue provided by toolbarjs , and on the left and right are floating pink colored thumbnail bars containing the center image of a volume, provided by thbarjs. In the center is a yellow rboxjs container that houses one or more green rendererjs objects that provide image interactivity. An app such as MedView assembles these building blocks as it sees fit. Up to four thumbnail images can be dragged and dropped from the thumbnail bar into the visualization square for simultaneous visualization of their corresponding volumes.

The four-volume display limit is not programmatically imposed, but reflects a design choice to show multiple volumes without visually overwhelming the display. Only those volumes being visualized in the visualization square are kept in memory to reduce the possibility of out-of-memory crashes.

Exploring the HTML5 Web Audio: Visualizing Sound

Therefore, every time a thumbnail is dropped into the visualization square a new data loading is triggered from either the local filesystem or a remote service according to the location of the volume file. Once data is loaded locally in memory the rendering performs very rapidly as there is no network upload involved. For remote data, the speed of access is unavoidably limited by the network latency.

Finally a volume can then be unloaded from the visualization square by dragging and dropping it back into the thumbnail bar. This modern and simple GUI allows users to quickly explore several 3D neuroimage volumes in a very intuitive manner. The client-side rendering approach adopted in MedView allows for a very responsive desktop-application-like visualization experience. Once a neuroimage volume has been loaded in the visualization square the user can interact with the data by manipulating the visualization through peripheral device controls and immediately sees the results of that interaction e.

The goal of the real-time collaboration is then to provide a way for simultaneous visualization of the same data by several collaborators working on remote computational entities and propagate the results of any user-data interaction to all the collaborators in real time. This requires a mechanism for sharing both the neuroimage data and the visualization state among collaborators.

The data sharing mechanism we provide here is based on two reusable JavaScript modules called fmjs and gcjs see Figure 1 for library organization.

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The fmjs module is a file manager designed to provide a unified interface to common file operations on abstract filesystems such as the HTML5 sandboxed filesystem currently available only in Chrome and the Google Drive cloud storage service GDrive. In particular, the exposed fmjs. The gcjs module on the other hand, exposes the gcjs. GDriveCollab class that reuses the fmjs.

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  • There are several advantages of choosing GDrive services and APIs for this client-side distributed application. First, they can be accessed directly from the client-side JavaScript code without requiring any back-end infrastructure.

    Second, there is no need for the heavy work of running our own data storage and real-time synchronization servers but instead we simply leverage the high availability and latency of the powerful GDrive servers. Third, conflict resolution is automatically handled when many collaborators are concurrently changing the visualization parameters. Last but not least, an OAuth 2. The real-time collaboration is actually implemented by synchronizing the application data visualization parameters among collaborators using the GDrive Realtime Collaborative Data Model RT-CDM which is basically a hierarchy of collaborative objects with built-in synchronization among collaborators.

    When any data is modified in the RT-CDM or new application data is included they are automatically persisted and shared with all the collaborators The gcjs. GDriveCollab class provides methods to get and set the RT-CDM and five event listeners that can be dynamically overwritten on its object instances:. A gcjs. GDriveCollab instance can allow any client-side JavasScript application the ability to participate in a real-time collaboration session through these methods and custom event listeners. Indeed the viewerjs. Viewer constructor of the previous section can accept a gcjs.

    This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. This article has been cited by other articles in PMC. Abstract Background Many software packages have been developed to address the need for generating phylogenetic trees intended for print. Introduction Constructing phylogenetic trees is a fundamental task in multiple fields of biology, including evolutionary, genetic, molecular and conservational biology.

    Methods jsPhyloSVG is designed to be a flexible, lightweight javascript library for building interactive and complex phylogenetic trees in a web-based environment with the broadest range of accessibility. Table 1 Comparison of common, scalable and interactive phylogenetic tree viewers that are intended for the web. Open in a separate window. It is important to note, that jsPhyloSVG is the only solution that is capable of rendering phylogenetic trees directly from the calculated inference within the browser without the need for plugins.

    Figure 1. The two rendering formats: rectangular and circular phylograms. Charting The library integrates charting analytics within the tree visualization. Figure 2. Integrated charting capabilities. Limitations The limitations of the library are primarily related to the authors' choice of using SVG to render the visualizations. Conclusions jsPhyloSVG is a comprehensive open-source solution for rendering dynamic phylogenetic trees.

    Supporting Information Table S1 Rendering performance across different browsers and devices. Acknowledgments Thanks to Jorge Dinas for the many fruitful discussions and critiques of tree-building. Footnotes Competing Interests: The authors have declared that no competing interests exist. References 1. Felsenstein J. Page RDM. Visualizing phylogenetic trees using TreeView. Curr Protoc Bioinformatics Chapter. ATV: display and manipulation of annotated phylogenetic trees. Letunic I, Bork P. PhyloWidget: web-based visualizations for the tree of life. Taxonomic colouring of phylogenetic trees of protein sequences.

    BMC Bioinformatics. Accessed 7 May YUI 3 — Yahoo! User Interface Library n. Han M, Zmasek C. Public Library of Science n. Accessed 5 May Accessed 16 May PubMed n. Support Center Support Center. External link.