The World Health Organization Europe (WHO/Europe) has been keeping track across Europe in an app which collects vaccine data from each country and displays it in an easy to understand graphic. The team at Jumping Rivers have been providing ongoing support for the WHO Covid vaccinations app.
Case Studies
Hertfordshire County Council’s Public Health Evidence & Intelligence team required a data science platform to undertake and publish analytics, ranging from creating automated reports describing the population's health to machine learning models predicting hospital admission.
Stakeholders for SDS are presented results of research studies in Powerpoint, with graphs generated in Excel and manually transferred into the presentation. They recently expressed a desire to convert this to an automated process, adopting R to perform the analysis and generate the reports.
Public Health Scotland (PHS) are discontinuing their use of the SPSS programming tool and strategically moving to more open source tools such as R and Python in order to save on licensing costs and to have access to the more advanced capability that R and Python provides.
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.
Jumping Rivers reimplemented an existing Shiny app using standard web technologies, achieving Web Content Accessibility Guideline compliance. The Shiny app was divided into a front-end and back-end component, using AWS Lambda to create a scalable and serverless R backend. Infrastructure was codified with Terraform, with the deployment and application life-cycle controlled with GitHub Actions.
In 2019, The Francis Crick Institute requested that we add Python training for their researchers off the back of the existing R training program we had with them.
The IT infrastructure for Public Health Scotland is managed by National Services Scotland, who came to Jumping Rivers with an existing Posit (formerly RStudio) deployment that was unable to provide a stable and reliable platform at a scale that met the requirements. Issues included inconsistent package versioning, which caused analyses that ran on one node to fail on another.
In spring of 2020 Northumbrian Water engaged with Jumping Rivers to build a modelling solution to better understand risks to the consumer within their network in order to provide a better service.
In 2018, Northumbrian Water held their annual Innovation Hackathon. Our winning entry, allowed engineers to reduce leakage throughout the North East.
In the spring of 2018, NHS Scotland expressed a need to move from their existing software, SPSS and SAS, to using R. The difficulty they faced was that there are over two hundred data scientists in NHS Scotland, which made training everyone in the new software a logistical challenge.
The client had developed an advanced, in-house Shiny application. We transformed the application into a commercial project, that is now being used by their clients.
The IFoA required a bespoke R and Posit platform to run their new R-based Actuarial CS1 and CS2 exams. We developed a system that delivered the exam and provided a convenient submission portal. Examiners could monitor results and feedback via a Shiny dashboard.
Jumping Rivers built a tool for creation of experimental risk assessments via a centralised web application. The dashboard allows for collaborative working during the data entry and assessment formulation, report generation and tracks versions along iterations of the process.
The client wanted to assess the viability of R and R Markdown as a reporting tool for creating complex, bespoke documents. We recreated sample reports for them in R Markdown, showcasing that all of their specifications could be met, and provided them with example code and training.
After winning a Water Hub Hackathon, Jumping Rivers were contracted to create a platform for the client using R Shiny, published on Posit Connect. The platform aggregates raw data from many third party sources both internal and external to the EA, through bespoke APIs, commercial databases, and asset management systems.
Over the last two years, we have been working with a cutting edge electronics company to build advanced algorithms using R and Python. Since they are at the research & design stage of the development process, their data structure is unique and challenging.
At the end of 2017, TRACS International contacted Jumping Rivers. TRACS International estimates the volumes of oil and gas in subsurface reservoirs. Their work involves combining a set of inputs for each reservoir layer (such as area, thickness, and up to five other inputs) – and then multiplying these inputs together.
The client came to Jumping Rivers having already written the code for their problem in VBA. They were trying to evaluate four measurements for agreements with their clients. However, VBA is limited in speed. Jumping Rivers were required to build a bespoke R package to replace and quicken the code.
Jumping Rivers created a data pipeline and visualisation dashboard for public and policy maker consumption. The aim was to increase transparency and encourage positive change to the workplace environment. The application allows exploration of key performance indicators stratified by a host of protected characteristics.
Jumping Rivers created a feature rich, bespoke Shiny dashboard through a series of development and user testing sprints. Custom widgets were created using React, to give a tailored application. Using a combination of continuous integration and deployment, the dashboard was deployed directly to shinyapps.io via GitHub.