Case Studies

Dragonfly Data Science partnered with Ōamaru Penguins to develop a new website and transform decades of little penguin (kororā) monitoring into a modernised data management system. This data was brought to life as interactive tools that support conservation and engage visitors.

This project put data on New Zealand’s regional economies online, making the information widely available. We created a desktop version and iPad and mobile apps to help people explore the numbers.

Our statistical analysis enabled fisheries managers to make a decision about which method was the most effective at reducing the number of albatross killed in trawl fisheries.

We reviewed a koala population study, checking that the report authors had used appropriate spatial modelling and data analysis methods, and that its conclusions were fair.

The National Plan of Action—Seabirds sets out the policy for managing interactions between fisheries and seabirds. Our seabird risk assessment underpins that policy - it supports the prioritisation of management actions and provides clear metrics for assessing the performance of the fishing industry.

We used our expertise in reproducible reporting to improve a team's data analysis processes. This saved significant time and effort in their regular report production.

A good understanding of marine predator-prey relationships is important for managing fisheries. Using statistical analysis we can model the strength of interactions between different species to help decide how much of a predator or prey species can be harvested without adversely affecting the other.

The New Zealand pāua (abalone) fishery is a $50 million export industry. We carry out analysis of pāua fisheries to provide information that is critical for responsive, well-informed management.

Dragonfly team member Philipp Neubauer worked with The Pacific Community (SPC) to more accurately assess the status of silky sharks in the Pacific Ocean.

Understanding avian influenza variants in New Zealand: a collaborative project between Dragonfly Data Science and the Ministry for Primary Industries

Forest & Bird's annual 'Bird of the Year' competition has been a passion project for Dragonfly data scientist, Yvan Richard, for over a decade. This year, Dragonfly Data Science is officially joining the flock as the competition's provider of verified vote counts.

We are developing a new technology named ‘Right Time, Right Place’ to improve efficiency, sustainability, and profitability in the commercial fishing industry.

We worked with the Occupational Therapy Board of New Zealand (OTBNZ) to help validate their best practice model through the analysis of eight years’ worth of textual data from their members.

This combined view of wellbeing data and the impacts of a severe weather event is a first for Aotearoa New Zealand.

We worked with a team from the Ministry for the Environment and Ackama to enhance the ministry’s submission processing and analysis tool, Croissant.

The interactive digital tool we built replaced the narrative-based Research, Science and Innovation System Performance Report. It was designed to be fast, beautiful and responsive.

Vibrant Planet develops tools for land management planning and monitoring to help increase the resilience of forests around the world. Our work with Vibrant Planet is producing data to support these tools.

Action to halt the estimated annual 5 percent decline of the Antipodean albatross population is essential. The integrated population model and app we created allow stakeholders to explore the effects of different threats and management strategies. This is intended to help guide decisions to secure the future of the species.

We created a pipeline to collect, verify, manage and visualise data about the accidental bycatch of marine protected species by recreational fishers. This data management system is helping DOC better understand interactions between fishers and protected species and informing management decisions.

Our work with the Ministry for Primary Industries replaced a manual production process with an automated system. New data can now be piped in to recreate each year’s National Exotic Forest Description – this is significantly faster, cheaper and more accurate than building the report from scratch using Word, Excel and InDesign.

We worked with the Ministry for Primary Industries and the Department of Conservation to make information with high public interest available online.

Each year, detailed data is collated by the 40,000 or so resource consent applications made to New Zealand’s district and regional councils. This information is critical for understanding how the resource management act is functioning in New Zealand.

We built a prediction service to allocate visa applications to either fast track or review track streams, based on previous decisions. Handling applications appropriately brings faster and more reliable decision-making.

Machine learning methods are ideal for classifying streaming data rapidly. We developed Kōkako, a language monitoring app to identify different languages broadcast on radio stations in New Zealand. Kōkako won a Best Design Award in 2016.

We created an online survey to map the distribution of four species of sea turtle in the Pacific Ocean. The maps fed into simulations of turtle interactions with fisheries that were produced at an international workshop.