scholarly journals Phinch: An interactive, exploratory data visualization framework for –Omic datasets

2014 ◽  
Author(s):  
Holly M Bik ◽  
Keyword(s):  
Data Visualization ◽  
New Technologies ◽  
Deep Level ◽  
Biogeographic Patterns ◽  
Innovative Method ◽  
File Formats ◽  
Unique Approach ◽  
Exploratory Data ◽  
Sequencing Platforms ◽  
Biological Patterns

Using environmental sequencing approaches, we now have the ability to deeply characterize biodiversity and biogeographic patterns in understudied, uncultured microbial taxa (investigations of bacteria, archaea, and microscopic eukaryotes using 454/Illumina sequencing platforms). However, the sheer volume of data produced from these new technologies requires fundamentally different approaches and new paradigms for effective data analysis. Scientific visualization represents an innovative method towards tackling the current bottleneck in bioinformatic workflows. In addition to giving researchers a unique approach for exploring large datasets, it stands to empower biologists with the ability to conduct powerful analyses without requiring a deep level of computational knowledge. Here we present Phinch, an interactive, browser-based visualization framework that can be used to explore and analyze biological patterns in high-throughput -Omic datasets. This project takes advantage of standard file formats from computational pipelines in order to bridge the gap between biological software (e.g. microbial ecology pipelines) and existing data visualization capabilities (harnessing the flexibility and scalability of technologies such as HTML5).

Multimodal Coreference Resolution for Exploratory Data Visualization Dialogue: Context-Based Annotation and Gesture Identification

2017 ◽  
Author(s):  
Abhinav Kumar ◽  
Jillian Aurisano ◽  
Barbara Di Eugenio ◽  
Andrew Johnson ◽  
Abeer Alsaiari ◽  
...  
Keyword(s):  
Data Visualization ◽  
Coreference Resolution ◽  
Exploratory Data

scholarly journals Out-of-Control Multivariate Patterns Recognition Using D2 and SVM: A Study Case for GMAW

Mathematics ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 467
Author(s):  
Pamela Chiñas-Sanchez ◽  
Ismael Lopez-Juarez ◽  
Jose Antonio Vazquez-Lopez ◽  
Jose Luis Navarro-Gonzalez ◽  
Aidee Hernandez-Lopez
Keyword(s):  
Arc Welding ◽  
New Technologies ◽  
Gas Metal Arc Welding ◽  
Industrial Processes ◽  
Support Vector ◽  
Innovative Method ◽  
Metal Arc Welding ◽  
Vector Machines ◽  
Study Case ◽  
Multivariate Pattern

Industrial processes seek to improve their quality control, including new technologies and satisfying requirements for globalised markets. In this paper, we present an innovative method based on Multivariate Pattern Recognition (MVPR) and process monitoring in a real-world study case. By identifying a distinctive out-of-control multivariate pattern using the Support Vector Machines (SVM) and the Mahalanobis Distance D2 it is possible to infer the variables that disturbed the process; hence, possible faults can be predicted knowing the state of the process. The method is based on our previous work, and in this paper we present the method application for an automated process, namely, the robotic Gas Metal Arc Welding (GMAW). Results from the application indicate an overall accuracy up to 88.8%, which demonstrates the effectiveness of the method, which can also be used in other MVPR tasks.

scholarly journals Mesophotic Ecosystems: The Link between Shallow and Deep-Sea Habitats

Diversity ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 411
Author(s):  
Gal Eyal ◽  
Hudson T. Pinheiro
Keyword(s):  
Coral Reef ◽  
Deep Sea ◽  
New Technologies ◽  
Mesophotic Coral Ecosystems ◽  
Tropical Regions ◽  
Biogeographic Patterns ◽  
Global Diversity ◽  
Coral Reef Ecosystems ◽  
Threatened Habitats ◽  
Management And Conservation

Mesophotic ecosystems (MEs) are characterized by the presence of light-dependent organisms, found at depths ranging from ~30 to 150 m in temperate, subtropical and tropical regions. These communities occasionally create massive reef structures with diverse but characteristic morphologies, which serve as the framework builders of those ecosystems. In many localities, MEs are physically linked with shallow and deep-sea habitats, and while taxa from both environments share this space, a unique and endemic biodiversity is also found. The main MEs studied to date are the mesophotic coral ecosystems (MCEs) and the temperate mesophotic ecosystems (TMEs), which have received increased attention during the last decade. As shallow coral reef ecosystems are among the most threatened habitats on Earth, the potential of MEs to act as refugia and contribute to the resilience of the whole ecosystem has been a subject of scrutiny. New technologies and methods have become more available to study these deeper parts of the reef ecosystems, yielding many new discoveries. However, basic gaps in knowledge remain in our scientific understanding of the global diversity of MEs, limiting our ability to recognize biogeographic patterns and to make educated decisions for the management and conservation of these ecosystems.

scholarly journals Big Data in Bioinformatics

2017 ◽  
Vol 12 (1) ◽  
pp. 102-119 ◽  
Author(s):  
Н.Н. Назипова ◽  
N.N. Nazipova
Keyword(s):  
Big Data ◽  
High Performance ◽  
New Technologies ◽  
Collaborative Work ◽  
Heterogeneous Data ◽  
Visual Programming ◽  
Generic Programming ◽  
Data Formats ◽  
Huge Data ◽  
Sequencing Platforms

Sequencing of the human genome began in 1994. It took 10 years of collaborative work of many research groups from different countries in order to provide a draft of the human DNA. Modern technologies allow sequencing of a whole genome in a few days. We discuss here the advances in modern bioinformatics related to the emergence of high-performance sequencing platforms, which not only contributed to the expansion of capabilities of biology and related sciences, but also gave rise to the phenomenon of Big Data in biology. The necessity for development of new technologies and methods for organization of storage, management, analysis and visualization of big data is substantiated. Modern bioinformatics is facing not only the problem of processing enormous volumes of heterogeneous data, but also a variety of methods of interpretation and presentation of the results, the simultaneous existence of various software tools and data formats. The ways of solving the arising challenges are discussed, in particular by using experiences from other areas of modern life, such as web and business intelligence. The former is the area of scientific research and development that explores the roles and makes use of artificial intelligence and information technology (IT) for new products, services and frameworks that are empowered by the World Wide Web; the latter is the domain of IT, which addresses the issues of decision-making. New database management systems, other than relational ones, will help solve the problem of storing huge data and providing an acceptable timescale for performing search queries. New programming technologies, such as generic programming and visual programming, are designed to solve the problem of the diversity of genomic data formats and to provide the ability to quickly create one's own scripts for data processing.

scholarly journals Modern facilities in astronomy education

2006 ◽  
Vol 2 (SPS5) ◽  
pp. 263-264
Author(s):  
Hayk Harutyunian ◽  
Areg Mickaelian
Keyword(s):  
Observational Data ◽  
Data Visualization ◽  
New Technologies ◽  
Virtual Observatory ◽  
Space Telescopes ◽  
Astronomy Education ◽  
Astronomical Observations ◽  
Stage Of Development ◽  
Modern Context ◽  
Short Time

AbstractAstronomical education is entering a new stage of development which is closely connected with the development of new technologies for communication, computing and data visualization. We discuss this evolution in the context of astronomy education in Armenia. As students spend only a short time in Byurakan Observatory for training in observations, they are not able to carry out systematic astronomical observations. Hence their training places emphasis on the use of astronomical archives and analysis of observational data obtained previously with the Byurakan telescopes and other ground-based and space telescopes. Thus, one of the aims of the Armenian Virtual Observatory is to support the training of students in this modern context.

scholarly journals SeqPlots - Interactive software for exploratory data analyses, pattern discovery and visualization in genomics

2016 ◽  
Vol 1 ◽  
pp. 14 ◽  
Author(s):  
Przemyslaw Stempor ◽  
Julie Ahringer
Keyword(s):  
Gene Expression ◽  
Chromatin Immunoprecipitation ◽  
High Throughput Sequencing ◽  
Ease Of Use ◽  
Data Exploration ◽  
Interactive Software ◽  
File Formats ◽  
Visualization Software ◽  
Exploratory Data ◽  
User Friendly

Experiments involving high-throughput sequencing are widely used for analyses of chromatin function and gene expression. Common examples are the use of chromatin immunoprecipitation for the analysis of chromatin modifications or factor binding, enzymatic digestions for chromatin structure assays, and RNA sequencing to assess gene expression changes after biological perturbations. To investigate the pattern and abundance of coverage signals across regions of interest, data are often visualized as profile plots of average signal or stacked rows of signal in the form of heatmaps. We found that available plotting software was either slow and laborious or difficult to use by investigators with little computational training, which inhibited wide data exploration. To address this need, we developed SeqPlots, a user-friendly exploratory data analysis (EDA) and visualization software for genomics. After choosing groups of signal and feature files and defining plotting parameters, users can generate profile plots of average signal or heatmaps clustered using different algorithms in a matter of seconds through the graphical user interface (GUI) controls. SeqPlots accepts all major genomic file formats as input and can also generate and plot user defined motif densities. Profile plots and heatmaps are highly configurable and batch operations can be used to generate a large number of plots at once. SeqPlots is available as a GUI application for Mac or Windows and Linux, or as an R/Bioconductor package. It can also be deployed on a server for remote and collaborative usage. The analysis features and ease of use of SeqPlots encourages wide data exploration, which should aid the discovery of novel genomic associations.

scholarly journals Data Visualization in Scandinavian Newsrooms

2018 ◽  
Vol 39 (2) ◽  
pp. 3-18 ◽  
Author(s):  
Martin Engebretsen ◽  
Helen Kennedy ◽  
Wibke Weber
Keyword(s):  
Data Visualization ◽  
Interview Study ◽  
News Organizations ◽  
Exploratory Data ◽  
Numeric Data ◽  
Specialist Groups ◽  
Data Visualizations

Abstract The visualization of numeric data is becoming an important element in journalism. In this article, we present an interview study investigating data visualization practices in Scandinavian newsrooms. Editorial leaders, data journalists, developers and graphic designers in 10 major news organizations in Norway, Sweden and Denmark provide information for the study on a range of issues concerning visualization practices and experiences. The emergence of multi-skilled specialist groups as well as innovation in technology and the ‘mobile first mantra’ are identified as important factors in the fast-developing practices of journalistic data visualization. Elements of tension and negotiation are revealed for issues concerning the role and effect of complex exploratory data visualizations and concerning the role of ordinary journalists in the production of charts and graphs.

scholarly journals A Conceptual Model for Geo-Online Exploratory Data Visualization: The Case of the COVID-19 Pandemic

Information ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 69
Author(s):  
Anna Bernasconi ◽  
Silvia Grandi
Keyword(s):  
Data Visualization ◽  
Spatial Information ◽  
Online Communication ◽  
Spatial Dimension ◽  
Data Types ◽  
Related Data ◽  
Exploratory Data ◽  
Visualization Tools ◽  
Communication Needs ◽  
Entity Relationship

Responding to the recent COVID-19 outbreak, several organizations and private citizens considered the opportunity to design and publish online explanatory data visualization tools for the communication of disease data supported by a spatial dimension. They responded to the need of receiving instant information arising from the broad research community, the public health authorities, and the general public. In addition, the growing maturity of information and mapping technologies, as well as of social networks, has greatly supported the diffusion of web-based dashboards and infographics, blending geographical, graphical, and statistical representation approaches. We propose a broad conceptualization of Web visualization tools for geo-spatial information, exceptionally employed to communicate the current pandemic; to this end, we study a significant number of publicly available platforms that track, visualize, and communicate indicators related to COVID-19. Our methodology is based on (i) a preliminary systematization of actors, data types, providers, and visualization tools, and on (ii) the creation of a rich collection of relevant sites clustered according to significant parameters. Ultimately, the contribution of this work includes a critical analysis of collected evidence and an extensive modeling effort of Geo-Online Exploratory Data Visualization (Geo-OEDV) tools, synthesized in terms of an Entity-Relationship schema. The COVID-19 pandemic outbreak has offered a significant case to study how and how much modern public communication needs spatially related data and effective implementation of tools whose inspection can impact decision-making at different levels. Our resulting model will allow several stakeholders (general users, policy-makers, and researchers/analysts) to gain awareness on the assets of structured online communication and resource owners to direct future development of these important tools.

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