The environment sector generates vast amounts of data and wish to share this data to drive local action. At a Water Hub Hackathon the Environment Agency (EA) presented their current platform. Their current platform includes critical measurements used in determining overall quality of water bodies, and 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. This win led to a project to explore real user needs and requirements, and develop a working prototype of potential solutions.
This project required a significant focus on discovering and engaging with current and potential users. We achieved this through related conference attendance, identification of key users with support from The Water Hub, and one-to-one demonstrations of proposed ideas and discussion of existing work practices related to Catchment Data.
To support discussions we developed wireframes of varying complexity, from static images, to interactive pages with sample data. Initial findings showed that current usage was lower than expected and EA requirements limited the inclusion of desired third party data such that many user requests could not be directly supported.
To fully explore the feedback and user requests we developed a prototype platform separate from the EAs data explorer to provide missing user requests and allow the EA to determine which features they could develop or implement internally.
Using R and Shiny as our main development tools, and RStudio Connect as the publication platform we host a functional prototype of the “Water Body Explorer”. This 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. All data is referenced to original sources allowing users to analyse, correct, or check provenance. Data processing was achieved using Python, R, and other open source GIS tools. In addition, a full report on user findings, development process, technical requirements, proposed further work with technical challenges highlighted was provided by us on completion.
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.
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.
At the end of 2017, contacted Jumping Rivers. AGR 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.
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.
After winning a Water Hub Hackathon, Jumping Rivers were contracted to create a platform for the client using R Shiny, published on RStudio 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.
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.
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 iteration of the process.
The IFoA required a bespoke R and RStudio 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.
The client had developed an advanced, in-house Shiny application. We transformed the application into a commerical project, that is now being used by their clients.
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.
In 2018, Northumbrian held their annual Innovation Hackathon. Our winning entry, allowed enginneers to reduce leakage throughout the North East.
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.
