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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.
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.
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.
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.
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.
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.
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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 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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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.
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.