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

Author(s):  
Abhinav Kumar ◽  
Jillian Aurisano ◽  
Barbara Di Eugenio ◽  
Andrew Johnson ◽  
Abeer Alsaiari ◽  
...  
2018 ◽  
Vol 39 (2) ◽  
pp. 3-18 ◽  
Author(s):  
Martin Engebretsen ◽  
Helen Kennedy ◽  
Wibke Weber

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.


2014 ◽  
Author(s):  
Holly M Bik ◽  

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).


Information ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 69
Author(s):  
Anna Bernasconi ◽  
Silvia Grandi

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.


2017 ◽  
Author(s):  
Jordan K Matelsky ◽  
Joseph Downs ◽  
Hannah Cowley ◽  
Brock Wester ◽  
William Gray-Roncal

AbstractAs the scope of scientific questions increase and datasets grow larger, the visualization of relevant information correspondingly becomes more difficult and complex. Sharing visualizations amongst collaborators and with the public can be especially onerous, as it is challenging to reconcile software dependencies, data formats, and specific user needs in an easily accessible package. We presentsubstrate, a data-visualization framework designed to simplify communication and code reuse across diverse research teams. Our platform provides a simple, powerful, browser-based interface for scientists to rapidly build effective three-dimensional scenes and visualizations. We aim to reduce the gap of existing systems, which commonly prescribe a limited set of high-level components, that are rarely optimized for arbitrarily large data visualization or for custom data types. To further engage the broader scientific community and enable seamless integration with existing scientific workflows, we also presentpytri, a Python library that bridges the use ofsubstratewith the ubiquitous scientific computing platform,Jupyter. Our intention is to reduce the activation energy required to transition between exploratory data analysis, data visualization, and publication-quality interactive scenes.


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