The Challenge Utah Tech University came to Jumping Rivers wanting to build two dashboards to help administrative staff and other interested parties better understand their student retention and admission data. The client had scoped that the most beneficial way to visualise aspects of their data would be using interactive Sankey and sunburst diagrams. While there are many examples of both these visualisation types built with the D3 JavaScript library, the client required several bespoke features that would allow the user of the dashboard to easily drill-down into the data.
shiny
The Challenge The client’s in-house data science team had developed a Shiny application using the RStudio desktop IDE. The client wished to develop this Shiny application into a product/service that may be provided to their own clients. The application required a thorough code review for performance and security with certain aspects needing further development (both in-house, and with Jumping Rivers’ support). This included integration with a new, secure data management service and integration with an existing user authentication service.
The Challenge Prior to engagement with Jumping Rivers, Fujifilm used an Excel-based tool for experimental risk assessments. This tool collated all data surrounding the process, including experimental parameters, comments, recommendations, and scoring data for a number of metrics. The tool was difficult to update and prone to breaking due to the rigid structure imposed by Excel. Further, versioning the reports and keeping track of the data was impossible without some central management of the process for updating the document.
The Challenge The environment sector generates vast amounts of data and wishes to share this data to drive local action. At a Water Hub Hackathon the Environment Agency (EA) presented their current platform, which includes critical measurements used in determining overall quality of water bodies, and is thus used for identifying potential projects and impact. Our winning submission included the ability to subscribe to data updates, improved visualisation, ability to look at multiple regions at once, improved user experience and modularity.
The Challenge The Fair Work Convention, set up by the Scottish government, acts as an advisory body to Scottish Ministers. The requirement was the creation of an R-Shiny application for public consumption which allows policymakers, ministers and members of the public to explore the current status of key indicators within the Fair Work Measurement Framework. The resultant application would then be handed back to the Scottish Government. The Project Jumping Rivers developed an R Shiny dashboard solution for the exploration of data.
We were very impressed with what you achieved over the 6 weeks and also with how organised you were around documenting and managing your side of the project. Alex Green (National Archives) The Challenge The National Archives required development of a web based application that would allow their users to build and compare storage policies to help archivists manage risk to their digital collection. The project started in September 2020 and was live just 6 weeks later.
There’s only two weeks left to go until Shiny in Production 2023! The events team are hard at work getting things ready for the day, and we wanted to take this opportunity to say a huge thank you to our event sponsors! Gold Sponsor National Innovation Centre for Data The National Innovation Centre for Data (NICD) was created in 2019 with £30 million of funding from the government and Newcastle University.
Earlier this year, two data scientists from Jumping Rivers ran an outreach activity for 14-19 year olds across the UK, in collaboration with the youth charity Speakers for Schools. The three hour workshop focussed on how to create visualisations that are both visually appealing and useful to the viewer. We demonstrated with a few examples of some visualisations that we created from some questions we asked on sign up (their favourite fast food restaurants and snacks) and showed them some examples of visualisations that challenged the view of data visualisation all being bar charts and scatter plots - think football pundit analysis and tube maps!
details { margin-top: 0.5em; } summary { cursor: pointer; } details .highlight { margin-top: 0.5em; } details pre { margin-bottom: 0.2em; } aside { background-color: #eeeeee; padding: 1em; } .blog-content aside h3 { color: black; font-size: 24px; } Browsers have been implementing variations on a JavaScript fullscreen API for over a decade. Unfortunately, for much of that time the APIs varied across browsers. This made actually using it in production somewhat cumbersome.
Word clouds are a visual representation of text data where words are arranged in a cluster, with the size of each word reflecting its frequency or importance in the data set. Word clouds are a great way of displaying the most prominent topics or keywords in free text data obtained from websites, social media feeds, reviews, articles and more. If you want to learn more about working with unstructured text data, we recommend attending our Text Mining in R course