scholarly journals LiveStories

2018 ◽  
Vol 106 (2) ◽  
Author(s):  
Kelli Yakabu ◽  
Andrea Ball
Keyword(s):  
Data Visualization ◽  
Web Based ◽  
Public Data ◽  
Visualization Tools ◽  
Interactive Data ◽  
Data Library ◽  
Drag And Drop

LiveStories is a web-based storytelling platform that is equipped with interactive data visualization tools, drag-and-drop publishing, and its own public data library.

scholarly journals An Interactive Data Visualization Framework for Exploring Geospatial Environmental Datasets and Model Predictions

Water ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2928
Author(s):  
Jeffrey D. Walker ◽  
Benjamin H. Letcher ◽  
Kirk D. Rodgers ◽  
Clint C. Muhlfeld ◽  
Vincent S. D’Angelo
Keyword(s):  
Decision Making ◽  
Case Studies ◽  
Data Visualization ◽  
Large Scale ◽  
Research Management ◽  
Web Based ◽  
Environmental Models ◽  
Potential Benefits ◽  
Interactive Data ◽  
Data Visualizations

With the rise of large-scale environmental models comes new challenges for how we best utilize this information in research, management and decision making. Interactive data visualizations can make large and complex datasets easier to access and explore, which can lead to knowledge discovery, hypothesis formation and improved understanding. Here, we present a web-based interactive data visualization framework, the Interactive Catchment Explorer (ICE), for exploring environmental datasets and model outputs. Using a client-based architecture, the ICE framework provides a highly interactive user experience for discovering spatial patterns, evaluating relationships between variables and identifying specific locations using multivariate criteria. Through a series of case studies, we demonstrate the application of the ICE framework to datasets and models associated with three separate research projects covering different regions in North America. From these case studies, we provide specific examples of the broader impacts that tools like these can have, including fostering discussion and collaboration among stakeholders and playing a central role in the iterative process of data collection, analysis and decision making. Overall, the ICE framework demonstrates the potential benefits and impacts of using web-based interactive data visualization tools to place environmental datasets and model outputs directly into the hands of stakeholders, managers, decision makers and other researchers.

scholarly journals Phoenix Enhancer: proteomics data mining using clustered spectra

2019 ◽  
Author(s):  
Mingze Bai ◽  
Chunyuan Qin ◽  
Kunxian Shu ◽  
Johannes Griss ◽  
Yasset Perez-Riverol ◽  
...  
Keyword(s):  
Supplementary Information ◽  
Proteomics Data ◽  
Web Based ◽  
Tandem Mass Spectra ◽  
Link Type ◽  
False Discovery ◽  
Cluster Data ◽  
Public Data ◽  
Visualization Tools ◽  
Individual Dataset

AbstractMotivationSpectrum clustering has been used to enhance proteomics data analysis: some originally unidentified spectra can potentially be identified and individual peptides can be evaluated to find potential mis-identifications by using clusters of identified spectra. The Phoenix Enhancer provides an infrastructure to analyze tandem mass spectra and the corresponding peptides in the context of previously identified public data. Based on PRIDE Cluster data and a newly developed pipeline, four functionalities are provided: i) evaluate the original peptide identifications in an individual dataset, to find low confidence peptide spectrum matches (PSMs) which could correspond to mis-identifications; ii) provide confidence scores for all originally identified PSMs, to help users evaluate their quality (complementary to getting a global false discovery rate); iii) identify potential new PSMs for originally unidentified spectra; and iv) provide a collection of browsing and visualization tools to analyze and export the results. In addition to the web based service, the code is open-source and easy to re-deploy on local computers using Docker containers.AvailabilityThe service of Phoenix Enhancer is available at http://enhancer.ncpsb.org. All source code is freely available in GitHub (https://github.com/phoenix-cluster/) and can be deployed in the Cloud and HPC [email protected] informationSupplementary data are available online.

scholarly journals Developing an Interactive Data Visualization Platform to Present the Adaption of Electrical Vehicles in Washington, California and New York

2020 ◽  
Author(s):  
Hiba Anis Ayad ◽  
Muna Abdulrahman Al-Obadi ◽  
Lana Ala' Al-Kilani ◽  
Haneen Tawfiq Hussein ◽  
Raiha Arshad ◽  
...  
Keyword(s):  
New York ◽  
Data Visualization ◽  
End User ◽  
Microsoft Excel ◽  
Clear Vision ◽  
Electrical Vehicles ◽  
The Usa ◽  
Visualization Tools ◽  
Interactive Data ◽  
Using Data

This paper is an overview of using data visualization tools to provide a better insight into a large amount of data and represent the data in a visualized form. The used data is related to electric vehicles (EV) usage in three different states in the USA, which are California, New York, and Washington. The data was collected from reliable resources to assure the reliability and accuracy of the results, then compiled as a Microsoft Excel workbook, which was then used as a data recourse in Microsoft Power BI. By visualizing the data we will end up with rich visuals which will clarify the data for the end-user. After analyzing the data, a clear vision created and recommendations have been suggested.

scholarly journals Going standalone and platform-independent, an example from recent work on the ATLAS Detector Description and interactive data visualization

2019 ◽  
Vol 214 ◽  
pp. 02035
Author(s):  
Sebastian Andreas Merkt ◽  
Riccardo Maria Bianchi ◽  
Joseph Boudreau ◽  
Paul Gessinger-Befurt ◽  
Edward Moyse ◽  
...  
Keyword(s):  
Data Visualization ◽  
Lessons Learned ◽  
Easy Access ◽  
Software Framework ◽  
Great Effort ◽  
Atlas Experiment ◽  
Platform Independence ◽  
Visualization Tools ◽  
Interactive Data ◽  
User Friendly

Until recently, the direct visualization of the complete ATLAS experiment geometry and physics objects was confined within the software framework of the experiment. To provide a detailed interactive data visualization capability to users, as well as easy access to geometry data, and to ensure platform independence and portability, great effort has been recently put into the modernization of both the core kernel of the detector description and the visualization tools. In this proceedings we will present the new tools, as well as the lessons learned while modernizing the experiment’s code for an efficient use of the detector description and for user-friendly data visualization.

eMap: A Web Application for Identifying and Visualizing Electron or Hole Hopping Pathways in Proteins

2019 ◽  
Author(s):  
Ruslan N. Tazhigulov ◽  
James R. Gayvert ◽  
Melissa Wei ◽  
Ksenia B. Bravaya
Keyword(s):  
Web Application ◽  
Shortest Paths ◽  
Coarse Grained ◽  
Decay Parameter ◽  
Electron Hole ◽  
Web Based ◽  
Aromatic Amino Acid Residue ◽  
Pathways Model ◽  
Visualization Tools ◽  
Effective Decay

<p>eMap is a web-based platform for identifying and visualizing electron or hole transfer pathways in proteins based on their crystal structures. The underlying model can be viewed as a coarse-grained version of the Pathways model, where each tunneling step between hopping sites represented by electron transfer active (ETA) moieties is described with one effective decay parameter that describes protein-mediated tunneling. ETA moieties include aromatic amino acid residue side chains and aromatic fragments of cofactors that are automatically detected, and, in addition, electron/hole residing sites that can be specified by the users. The software searches for the shortest paths connecting the user-specified electron/hole source to either all surface-exposed ETA residues or to the user-specified target. The identified pathways are ranked based on their length. The pathways are visualized in 2D as a graph, in which each node represents an ETA site, and in 3D using available protein visualization tools. Here, we present the capability and user interface of eMap 1.0, which is available at https://emap.bu.edu.</p>

scholarly journals metaXplor: an interactive viral and microbial metagenomic data manager

GigaScience ◽  
2021 ◽  
Vol 10 (2) ◽  
Author(s):  
Guilhem Sempéré ◽  
Adrien Pétel ◽  
Magsen Abbé ◽  
Pierre Lefeuvre ◽  
Philippe Roumagnac ◽  
...  
Keyword(s):  
Heterogeneous Data ◽  
Metagenomic Data ◽  
Online Data ◽  
Data Repositories ◽  
Ongoing Research ◽  
Efficient Management ◽  
Public Data ◽  
Reference Databases ◽  
Interactive Data ◽  
User Friendly

Abstract Background Efficiently managing large, heterogeneous data in a structured yet flexible way is a challenge to research laboratories working with genomic data. Specifically regarding both shotgun- and metabarcoding-based metagenomics, while online reference databases and user-friendly tools exist for running various types of analyses (e.g., Qiime, Mothur, Megan, IMG/VR, Anvi'o, Qiita, MetaVir), scientists lack comprehensive software for easily building scalable, searchable, online data repositories on which they can rely during their ongoing research. Results metaXplor is a scalable, distributable, fully web-interfaced application for managing, sharing, and exploring metagenomic data. Being based on a flexible NoSQL data model, it has few constraints regarding dataset contents and thus proves useful for handling outputs from both shotgun and metabarcoding techniques. By supporting incremental data feeding and providing means to combine filters on all imported fields, it allows for exhaustive content browsing, as well as rapid narrowing to find specific records. The application also features various interactive data visualization tools, ways to query contents by BLASTing external sequences, and an integrated pipeline to enrich assignments with phylogenetic placements. The project home page provides the URL of a live instance allowing users to test the system on public data. Conclusion metaXplor allows efficient management and exploration of metagenomic data. Its availability as a set of Docker containers, making it easy to deploy on academic servers, on the cloud, or even on personal computers, will facilitate its adoption.

Interactive Data Visualization in Jupyter Notebooks

2021 ◽  
Vol 23 (2) ◽  
pp. 99-106
Author(s):  
Jorge Piazentin Ono ◽  
Juliana Freire ◽  
Claudio T. Silva ◽  
Joao Comba ◽  
Kelly Gaither
Keyword(s):  
Data Visualization ◽  
Interactive Data

A Web-Based Tool for Visualization of Biomolecular Network Comparison

2014 ◽  
Vol 556-562 ◽  
pp. 5482-5487
Author(s):  
Hui Ran Zhang ◽  
Xiao Long Shen ◽  
Jiang Xie ◽  
Dong Bo Dai
Keyword(s):  
Open Source ◽  
Undirected Graphs ◽  
Web Based ◽  
Network Comparison ◽  
Biomolecular Networks ◽  
Biomolecular Network ◽  
Visualization Tools ◽  
Similarities And Differences ◽  
Adaptive Visualization

Analyzing similarities and differences between biomolecular networks comparison through website intuitively could be a convenient and effective way for researchers. Although several network comparison visualization tools have been developed, none of them can be integrated into websites. In this paper, a web-based tool kit named dynamically adaptive Visualization of Biomolecular Network Comparison (Bio-NCV) is designed and developed. The proposed tool is based on Cytyoscape.js – a popular open-source library for analyzing and visualizing networks. Bio-NCV integrates arjor.js which including the Barnes-Hut algorithm and the Traer Physics library for processing in order to express the dynamically adaptive initialization. In addition, in order to maintain consistency, the counterparts in other networks will change while the nodes and edges in one of the compared networks change. Furthermore, Bio-NCV can deal with both directed and undirected graphs.

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