This document discusses using the Shiny framework to build interactive web applications for data visualization in corpus linguistics. It provides an introduction to visual analytics and reactive web frameworks. It then describes the Shiny application framework, including its reactive architecture and benefits. The document demonstrates building a basic Shiny app, adding inputs and outputs, and linking them. It also provides resources and steps for installing R and RStudio, and developing a Shiny app to visualize and summarize a corpus linguistics data set.
Introduction to Interactive Shiny Web ApplicationOlga Scrivner
2 hour hands-on workshop on how to create, deploy and use Shiny in research and teaching. The materials for the workshop are https://languagevariationsuite.wordpress.com/2018/11/27/introduction-to-interactive-shiny-web-applications
Data Visualization: Introduction to Shiny Web ApplicationsOlga Scrivner
In this workshop, I will introduce you to the concept of Declarative Reactive Web Frameworks, allowing for interactive user-friendly data visualization and data analytics, particularly Shiny. Shiny is an R package that creates interactive applications for data visualization. You will learn some Shiny basics: how to build your reactive app and deploy it to the server
This session looks at the new features and general improvements slated for this release, including the new default theme for 2015. Starting out with a brief overview of how releases work in general, it touches the wide set of improvements in 4.1, and closes with a look at marquee features that are scheduled for upcoming releases.
All the Laravel Things – Up & Running to Making $$Joe Ferguson
Come learn about all the tools in the Laravel ecosystem designed to save you time and prevent you from writing the boring cruft needed for every application. We’ll cover getting started with local development, building basic apps, and deploying. We’ll cover how Laravel easily handles vagrant, testing, oauth login services, billing and subscription services through Laravel Spark, and deploying your application with services such as Laravel Envoyer and Forge to manage your servers.
Доклад Сергея Калинца, Software Architect, для Съесть собаку #9, 15/06/2017.
Тезисы:
- Проблемы стандартного процесса разработки
- Понятие CI pipeline
- Решения для автоматизации сборки, тестирования и развертывания
- Инструменты для эффективной разработки
- Использование тестовых двойников в .NET
- Концепция "живого кода"
- Демонстрация применения современных библиотек и инструментов для эффективного написания кода.
Introduction to Interactive Shiny Web ApplicationOlga Scrivner
2 hour hands-on workshop on how to create, deploy and use Shiny in research and teaching. The materials for the workshop are https://languagevariationsuite.wordpress.com/2018/11/27/introduction-to-interactive-shiny-web-applications
Data Visualization: Introduction to Shiny Web ApplicationsOlga Scrivner
In this workshop, I will introduce you to the concept of Declarative Reactive Web Frameworks, allowing for interactive user-friendly data visualization and data analytics, particularly Shiny. Shiny is an R package that creates interactive applications for data visualization. You will learn some Shiny basics: how to build your reactive app and deploy it to the server
This session looks at the new features and general improvements slated for this release, including the new default theme for 2015. Starting out with a brief overview of how releases work in general, it touches the wide set of improvements in 4.1, and closes with a look at marquee features that are scheduled for upcoming releases.
All the Laravel Things – Up & Running to Making $$Joe Ferguson
Come learn about all the tools in the Laravel ecosystem designed to save you time and prevent you from writing the boring cruft needed for every application. We’ll cover getting started with local development, building basic apps, and deploying. We’ll cover how Laravel easily handles vagrant, testing, oauth login services, billing and subscription services through Laravel Spark, and deploying your application with services such as Laravel Envoyer and Forge to manage your servers.
Доклад Сергея Калинца, Software Architect, для Съесть собаку #9, 15/06/2017.
Тезисы:
- Проблемы стандартного процесса разработки
- Понятие CI pipeline
- Решения для автоматизации сборки, тестирования и развертывания
- Инструменты для эффективной разработки
- Использование тестовых двойников в .NET
- Концепция "живого кода"
- Демонстрация применения современных библиотек и инструментов для эффективного написания кода.
Maintainable UI Tests with Selenium and C#Jacinto Limjap
In this session I describe how to create UI Tests using Selenium, MSTest, and C# on Visual Studio 2017. I also describe PageObjects, which allow me to create more readable tests.
Making a new Rails app, using the example dog adoption app created for RailsBridge Chicago 2015. Works through databases, migrations, models, controllers, and more basics.
Publishing API documentation -- WorkshopTom Johnson
These slides are from the REST API documentation workshop that I gave at the STC Summit 2015. For more details, see http://idratherbewriting.com/publishingapidocs.
Blog post: http://WakeUpAndCode.com/asp-net-core-testing
Learn all about automated unit testing in ASP.NET Core 1.0 (formerly known as ASP.NET 5) and how you can set up Visual Studio so that you can quickly test your apps in the real world.
Gear4music has become one of the largest retailers of musical instruments and equipment in the United Kingdom. I joined the business back in October 2018 as they required a tester with API testing experience for upcoming projects. In this talk, I'll be covering how we went from 0 to 1000+ API tests and how Postman has helped throughout the project's life cycle.I'll also be talking about how I've evolved throughout the years as a Postman user and I'll cover things I wish I knew when I first started.
Laravel is a great framework to use for web applications but what if you need to do more? Come learn how to harness the power of the console in your Laravel applications to do various tasks such as caching data from 3rd party APIs, Expire old content from S3 or other data store, and batch process huge data sets without users having to wait for results. You can even automate tasks such as backing up your remote databases before you run migrations with artisan commands.
This is a presentation by Google Developer Advocate Chris Schalk given to a Software Developer workshop hosted by CyWorld, a new OpenSocial container. This was presented to about 200 software developers in Seoul, Korea, Sept. 2009.
Building State-of-the-art Natural Language Processing Projects with Free Soft...David Talby
Building Complete State-of-the-art Natural Language Processing Projects with Free Software covers free AI-assisted text annotation tools & no-code model building, a Python library with one-line access to 10,000+ pre-trained models in 250+ languages, and an NLP Server to server NLP models & pipelines as REST API's.
Building Customized Text Mining Tools via Shiny Framework: The Future of Data...Olga Scrivner
With the increasing volume of data, there is a growing need for dynamic data visualization to help reveal instant changes in data patterns. There exist many commercial visualization tools, but traditional scholars are often disengaged from the tool development process; thus, the choice of functionalities is contingent upon tool developers whose choice may not fit the end-users. This collaboration, however, has a potential in bridging the gap between traditional scholars, who are more interested in sense-making of the text than in the tools, and the data scientists, who are more interested in the tools than in the substance, but must still contextualize the outcomes. Until recently, this collaborative process was hindered by the complexity of customization procedures and technological hurdles imposed on users with new installations. With the advent of reactive web frameworks, such as Shiny, the user-driven customization becomes not only feasible, but also essential to advance scientific research. In this paper, we demonstrate a collaborative effort between learned scholars and tool developers, allowing for a computational and humanistic fusion.
Maintainable UI Tests with Selenium and C#Jacinto Limjap
In this session I describe how to create UI Tests using Selenium, MSTest, and C# on Visual Studio 2017. I also describe PageObjects, which allow me to create more readable tests.
Making a new Rails app, using the example dog adoption app created for RailsBridge Chicago 2015. Works through databases, migrations, models, controllers, and more basics.
Publishing API documentation -- WorkshopTom Johnson
These slides are from the REST API documentation workshop that I gave at the STC Summit 2015. For more details, see http://idratherbewriting.com/publishingapidocs.
Blog post: http://WakeUpAndCode.com/asp-net-core-testing
Learn all about automated unit testing in ASP.NET Core 1.0 (formerly known as ASP.NET 5) and how you can set up Visual Studio so that you can quickly test your apps in the real world.
Gear4music has become one of the largest retailers of musical instruments and equipment in the United Kingdom. I joined the business back in October 2018 as they required a tester with API testing experience for upcoming projects. In this talk, I'll be covering how we went from 0 to 1000+ API tests and how Postman has helped throughout the project's life cycle.I'll also be talking about how I've evolved throughout the years as a Postman user and I'll cover things I wish I knew when I first started.
Laravel is a great framework to use for web applications but what if you need to do more? Come learn how to harness the power of the console in your Laravel applications to do various tasks such as caching data from 3rd party APIs, Expire old content from S3 or other data store, and batch process huge data sets without users having to wait for results. You can even automate tasks such as backing up your remote databases before you run migrations with artisan commands.
This is a presentation by Google Developer Advocate Chris Schalk given to a Software Developer workshop hosted by CyWorld, a new OpenSocial container. This was presented to about 200 software developers in Seoul, Korea, Sept. 2009.
Building State-of-the-art Natural Language Processing Projects with Free Soft...David Talby
Building Complete State-of-the-art Natural Language Processing Projects with Free Software covers free AI-assisted text annotation tools & no-code model building, a Python library with one-line access to 10,000+ pre-trained models in 250+ languages, and an NLP Server to server NLP models & pipelines as REST API's.
Building Customized Text Mining Tools via Shiny Framework: The Future of Data...Olga Scrivner
With the increasing volume of data, there is a growing need for dynamic data visualization to help reveal instant changes in data patterns. There exist many commercial visualization tools, but traditional scholars are often disengaged from the tool development process; thus, the choice of functionalities is contingent upon tool developers whose choice may not fit the end-users. This collaboration, however, has a potential in bridging the gap between traditional scholars, who are more interested in sense-making of the text than in the tools, and the data scientists, who are more interested in the tools than in the substance, but must still contextualize the outcomes. Until recently, this collaborative process was hindered by the complexity of customization procedures and technological hurdles imposed on users with new installations. With the advent of reactive web frameworks, such as Shiny, the user-driven customization becomes not only feasible, but also essential to advance scientific research. In this paper, we demonstrate a collaborative effort between learned scholars and tool developers, allowing for a computational and humanistic fusion.
AWS re:Invent 2016: Open Source at AWS—Contributions, Support, and Engagement...Amazon Web Services
Over the last few years, we have seen a dramatic increase in the use of open source projects as the mainstay of architectures in both startups and enterprises. Many of our customers and partners also run their own open source programs and contribute key technologies to the industry as a whole (see DCS201). At AWS we engage with open source projects in a number of ways. We contribute bug fixes and enhancements to popular projects including our work with the Hadoop ecosystem (see BDM401), Chromium (see BAP305) and (obviously) Boto. We have our own standalone projects including the security library s2n (see NET405) and machine learning project MXnet (see MAC401). We also have services that make open source easier to use like ECS for Docker (see CON316), and RDS for MySQL and PostgreSQL (see DAT305). In this session you will learn about our existing open source work across AWS, and our next steps.
Olga Mierzwa-Sulima talk from eRum 2018 conference.
Talks cover 6 new Shiny packages that Appsilon has developed to extend Shiny's frontend possibilities:
1. Shiny Sementic - Package for SemanticUI components
2. semantic.dashboard - Package for SemanticUI Shiny dashboard
3. shiny.router - Making routing possible with Shiny
4. shiny.i18n - Helps build multi language apps
5. shiny.users - Authentication handled by Shiny done on the application side
6. shiny.admin - Allowing to collect statistics about users activity in the App
blogpost: https://appsilon.com/why-you-should-regret-not-going-to-erum-2018/
github: https://github.com/Appsilon
Youtube: https://youtu.be/6hISTA8fGiA
OPENi perspective on APIs and Cloudlets @Athens hackathon, September 2014Fenareti Lampathaki
An overview of the OPENi results with regard to the APIs (for developers) and personal cloudlets (for end-users) presented to the OPENi Athens Hackathon on September 2014.
An Infographic on My 25 Articles in Open Source For You Magazine Dr. K.S. Kuppu Samy
An infographic on my 25 Articles in Open Source For You magazine. Thank You OSFY team for the opportunity and readers for their feedback.
Dr. K.S.Kuppusamy
Redfine aims to extend OpenRefine to make use of the Redlink APIs for a more advance and performance solution for publishing Linked Data.
A proposal by Redlink GmbH to the Fusepool Open Call for Developers at the Data|Hack|Award 2014.
Mining public datasets using opensource tools: Zeppelin, Spark and Jujuseoul_engineer
There are plenty of public datasets out there available and the number is growing. Few recent and most useful of BigData ecosystem tools are showcased: Apache Zeppelin (incubating), Apache Spark and Juju.
Introduction to Web Scraping with PythonOlga Scrivner
In this workshop, you will learn how to extract web data with Beautiful Soup, a Python library for extracting data out of HTML- and XML-structured documents. You will also learn the basics of scraping and parsing data. In this hands-on workshop, we will also be using the DataCamp platform and participants are requested to have a free account with DataCamp prior the workshop.
Call for paper Collaboration Systems and TechnologyOlga Scrivner
Our minitrack encourages research contributions that deal with learning theories, cognition, tools and their development, enabling platforms, communication media, distance learning, supporting infrastructures, user experiences, research methods, social impacts, learning analytics, and measurable outcomes as they relate to the area of technology and its support of improving teaching and learning. In particular, the significant increase of online and distributed classroom environments brings new technological challenges.
Hands-on workshop on Jupiter Notebook and Machine Learning.
The link to material - https://languagevariationsuite.wordpress.com/2020/02/22/machine-learning-101-with-jupyter-notebook/amp/
CEWIT Hand-on workshop.
Link to materials - https://languagevariationsuite.wordpress.com/2020/01/31/faculty-accelerator-crash-course-rmarkdown-with-r-introduction/amp/
Video of Workshop - https://media.dlib.indiana.edu/media_objects/rj430941s
This is workshop offered via Social Science Research Center to students and faculty to become familiar with an online collaborative writing using Latex and Overleaf.
Workshop nwav 47 - LVS - Tool for Quantitative Data AnalysisOlga Scrivner
In the format of hands-on session, this workshop will introduce participants to the Language Variation Suite (LVS), a user-friendly interactive web application built in R. LVS provides access to advanced statistical methods and visualization techniques, such as mixed-effects modeling, conditional and random tree analyses, cluster analysis. These advanced methods enable researchers to handle imbalanced data, measure individual and group variation, estimate significance, and rank variables according to their significance.
Gender Disparity in Employment and EducationOlga Scrivner
Data analysis is presented at IndyBigData Visualization Challenge 2018. Data is provided by MPH - see https://www.indybigdata.com/visualization-challenge/
CrashCourse: Python with DataCamp and Jupyter for BeginnersOlga Scrivner
Crash course for beginners is based on Python Introduction by Philip Schowenaars from DataCamp and Jupyter Introduction adapted from Adapted from Pryke, B. (2018). Jupyter Notebook for Beginners: A Tutorial. DataQuest. https://www.dataquest.io/blog/jupyter-notebook-tutorial/
Optimizing Data Analysis: Web application with ShinyOlga Scrivner
In the format of hands-on session, this workshop will introduce participants to the Language Variation Suite (LVS), a user-friendly interactive web application built in R. LVS provides access to advanced statistical methods and visualization techniques, such as mixed-effects modeling, conditional and random tree analyses, cluster analysis. These advanced methods enable researchers to handle imbalanced data, measure individual and group variation, estimate significance, and rank variables according to their significance.
Workshop files:
Categorical data csv – Use of R in New York (Labov 1966) - http://cl.indiana.edu/~obscrivn/docs/categoricaldata.csv
Continuous data csv – Intervocalic /d/ (Díaz-Campos et al. 2016) - http://cl.indiana.edu/~obscrivn/docs/continuousdata.csv
Language Variation Suite - https://languagevariationsuite.shinyapps.io/Pages/
Data Analysis and Visualization: R WorkflowOlga Scrivner
The lecture introduces to R project set-up, planning and deploying as well as to the concept of tidy data (Wickham and Grolemund, 2017).
Visual Insights Talks 2018 at
http://ivmooc.cns.iu.edu/
http://cns.iu.edu/
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...pchutichetpong
M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years.
Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success.
MCG reports that the more favorable market conditions expected over the next few years, helped by the winding down of pandemic restrictions and a hybrid working environment will be driving market momentum forward. The continuous injection of capital by alternative investment firms, as well as the growing infrastructural investment from cloud service providers and social media companies, whose revenues are expected to grow over 3.6x larger by value in 2026, will likely help propel center provision and innovation. These factors paint a promising picture for the industry players that offset rising input costs and adapt to new technologies.
According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Discussion on Vector Databases, Unstructured Data and AI
https://www.meetup.com/unstructured-data-meetup-new-york/
This meetup is for people working in unstructured data. Speakers will come present about related topics such as vector databases, LLMs, and managing data at scale. The intended audience of this group includes roles like machine learning engineers, data scientists, data engineers, software engineers, and PMs.This meetup was formerly Milvus Meetup, and is sponsored by Zilliz maintainers of Milvus.
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
Workshop: Data Visualization for Corpus Linguistics via Shiny Framework
1. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
Data Visualization for Corpus Linguistics:
Shiny Framework
Olga Scrivner
2. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
What You Will Learn
1. Introduction to Visual Analytics
2. Reactive Web Framework
3. Shiny Application
4. Practice
https://languagevariationsuite.wordpress.com/
3. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
Data Analytics
“Analytics is the critical technology
needed to bring value out of data”
(Anonymous)
4. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
Visual Analytics
“The science of analytical reasoning
facilitated by visual interactive interfaces”
(Thomas and Cook, 2005)
“Visual analytics integrates new computational and
theory-based tools with innovative interactive techniques
and visual representations to enable human-information
discourse” (Thomas and Cook, 2005)
5. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
Visual Analytics and Linguistics
“ Language is a system of relatively arbitrary symbols”
(Baker-Shenk and Cokely, 1980)
http://www.tableaufit.com/tableau-conference-linguistics-data-visualization/
6. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
Visual Analytics (and Corpus Linguistics)
1. Exploration (Queries)
2. Comprehension (Analysis)
3. Communication (Presentation)
8. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
Visualization Tools
Challenges:
Many tools are built for non-linguistic research
Limited preprocessing
Visualization may not fit linguistic data
9. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
Visualization Tools
Challenges:
Many tools are built for non-linguistic research
Limited preprocessing
Visualization may not fit linguistic data
Solution: Reactive Framework
Interactive and web-based
Research-driven customization
Build your own tool!
10. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
Reactive Web Framework
“Reactive Systems are highly responsive, giving users
effective interactive feedback”
http://www.reactivemanifesto.org/
http://littleactuary.github.io/blog/Web-application-framework-with-Shiny/
12. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
Reactive Framework and Data Science
“The impact of data scientists’ work depends on how well
others can understand their insights to take further actions”
Benefit 1: Interactive display and manipulation of data
Benefit 2: No installation required
Benefit 3: Easy to develop and share with clients and
project teams
Benefit 4: Open source library
http://datascience.ibm.com/blog/shiny-a-data-scientist-best-friend/
13. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
Shiny Application
1. Shiny is an R package for building interactive web
applications
2. Open-Sourced by RStudio 11/2012 on CRAN
3. Uses web sockets (new HTTP):
Interactive communication sessions between the user’s
browser and a server without having to poll the server
for a reply
4. Entirely extensible - custom input/output
14. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
Shiny Library
http://littleactuary.github.io/blog/Web-application-framework-with-Shiny/
15. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
Shiny Gallery - Get Inspired
https://www.rstudio.com/products/shiny/shiny-user-showcase/
16. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
Interactive Text Mining Suite (Scrivner et al.
2016)
1. Web application for text processing and mining
2. Interactive natural language processing techniques
Wordstops, stemming, text-preprocessing
3. High customization
22. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
Format Flexibility
Example: Using Google Books API
Current limitation is 40 books
23. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
Workshop Materials
1. Rstudio
2. R
3. Shiny library
4. Materials:
https:
//languagevariationsuite.wordpress.com/
24. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
R software
R is a free software for data analysis, text mining and
visualization.
To install R on Window:
1. Download the binary file for R
https://cran.r-project.org/bin/windows/base/
R-3.3.1-win.exe
2. Open the downloaded .exe file and Install R
To install R on Mac:
1. Download the appropriate version of .pkg file
https://cran.r-project.org/bin/macosx/
2. Open the downloaded .pkg file and Install R
25. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
R Studio
RStudio is a free user interface for R.
1. Install the appropriate RStudio version https:
//www.rstudio.com/products/rstudio/download/
2. Run it to install R-studio
30. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
Execution - RUN
To execute - click run
In the script (top left window) type:
library(shiny)
Click Run (your cursor can be at the beginning or at the end
of the line)
35. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
Reactive Input/Output
Input - things user can toggle
Output - R objects that user can see, often depend on
inputs
39. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
UI
shinyUI( fluidPage(
titlePanel(“Old Faithful Geyser Data”),
sidebarLayout(
sidebarPanel(
sliderInput(“bins”,
“Number of bins:”,
min = 1,
max = 50,
value = 30)
40. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
UI
shinyUI( fluidPage(
titlePanel(“Old Faithful Geyser Data”),
sidebarLayout(
sidebarPanel(
sliderInput(“bins”,
“Number of bins:”,
min = 1,
max = 50,
value = 30)
41. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
Modifying UI - Practice
Change slider’s label:
Number of bins → Choose a number
Change slider’s values: max and value
Save
RunApp
43. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
HTML
HTML tags:
http:
//shiny.rstudio.com/articles/tag-glossary.html
h1() = header1
br() = line break
p() = paragraph
hr() = line
44. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
Adding HTML Tags to UI.R - Practice
shinyUI( fluidPage(
titlePanel(“My Title”),
h3(“My subtitle”),
p(“This is my first app!”),
br(),
hr(),
49. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
Input Data
1. Blog https:
//languagevariationsuite.wordpress.com/
2. Download csv file - movie metadata.csv
3. Place this file into the directory myshiny
50. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
New Input in UI.R
Let’s look at the fileInput() function from Shiny
Reference page
Type in your browser: fileInput Shiny
or go to the Shiny Reference page -
https://shiny.rstudio.com/reference/shiny/
latest/fileInput.html
51. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
New Input in UI.R
Scroll down to Examples
We will add fileInput function inside sidebarPanel
Copy fileInput function
52. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
New Input in UI.R
Paste it after slider
NB: commas are important!
53. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
Reactive Function in Sever.R
Reactive - it changes every time the user uploads new data
Create a function that reads csv file
myfile() is a function that will read and return csv files
55. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
Function summary in Server.R
output$summary <- renderPrint({
summary(myfile())
})
56. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
New Output Function table in Server.R
output$table <- renderDataTable({
myfile()
})
57. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
Linking summary and table with UI.R
tabsetPanel(
tabPanel("Plot", plotOutput("distPlot")),
tabPanel("Summary", verbatimTextOutput("summary")),
tabPanel("Table", dataTableOutput("table"))
)
58. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
Linking summary and table with UI.R
tabsetPanel(
tabPanel("Plot", plotOutput("distPlot")),
tabPanel("Summary", verbatimTextOutput("summary")),
tabPanel("Table", dataTableOutput("table"))
)
RunApp
60. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
One more IF-Statement - Server.R
We want to do a histogram for csv file:
if (condition) {do..} else {do...}
61. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
One more IF-Statement - Server.R
We want to do a histogram for csv file:
if (condition) {do..} else {do...}
output$distPlot <- renderPlot({
if (is.null(input$file1)) {
....
hist(x, breaks = bins, col = ’darkgray’, border =
’white’)
}
62. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
One more IF-Statement - Server.R
We want to do a histogram for csv file:
if (condition) {do..} else {do...}
output$distPlot <- renderPlot({
if (is.null(input$file1)) {
....
hist(x, breaks = bins, col = ’darkgray’, border =
’white’)
}
else{
x <- myfile()$budget
bins <- seq(min(x), max(x), length.out = input$bins
+ 1)
hist(x, breaks = bins, col=’red’,
main = ’My New Histogram’)
}
})
65. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
Deployment Options
1. Share server.r and ui.r
2. Host on shinyapps.io
3. Host on Shiny server
66. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
Deploy with shinyapps.io
www.shinyapps.io
sign up for an account.
Publish Application button in RStudio and follow
instructions
70. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
Future of Visualization Tools: CNS
Cyberinfrastructure for Network Science Center at Indiana
University - http://cns.iu.edu/
Our current project on Shiny Framework (team Olga
Scrivner and Jivitesh Poojary)
Build Shiny templates for Data Visualization: stage I
https:
//github.com/Jivitesh-Poojary/CNS-Shiny-Apps
Create user-friendly customizable Shiny dashboards:
stage II
Develop preprocessing plugins for Shiny templates:
stage III
71. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
Useful resources
1. Shiny official tutorial -
http://shiny.rstudio.com/tutorial
2. Cheat sheet - http://shiny.rstudio.com/images/
shiny-cheatsheet.pdf
3. Publish your app free - http://www.shinyapps.io
4. Examples -http://www.showmeshiny.com/
5. Tutorial by Dean Attali - http://deanattali.com/
blog/building-shiny-apps-tutorial/
73. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
References
B¨orner, Katy. 2015. Atlas of Knowledge: Anyone Can Map. The
MIT Press
Collins, Christopher. 2012. Bridging the Linguistic Visualization
Divide. LingVis/UNCLH Workshop
Grolemund, Garrett. 2017. How to start with Shiny, Part 1.
Workshop
74. Data Visualization
for Corpus
Linguistics:
Shiny Framework
Olga Scrivner
Visual Analytics
Reactive
Framework
Shiny App
Practice
Credits
http:
//deanattali.com/blog/building-shiny-apps-tutorial/
http://scimaps.org/mapdetail/stream_of_scientific_128
https://github.com/IBMDataScience/dsx-shiny-apps
http://www.slideshare.net/SarahAerni/
data-science-as-a-commodity-use-madlib-r-other-oss-tools-for-data-
http://www.unixstickers.com/image/data/stickers/
react/badge/React-JS.sh.png
https://github.com/rstudio/shiny/issues/250
http://www.slideshare.net/ilio-catallo/
spring-mvc-the-basics