SDG 9 : Industry, Innovation and Infrastructure

Research increasingly depends on large and complex amounts of data, but the systems, policies and expertise needed to manage that data vary between institutions. In 2025, a University of Limerick (UL)-led project completed work on a new National Research Data Management Framework designed to strengthen how research data is managed across Ireland.

Led by Armin Straube, Research Data Manager at UL, the National Research Data Management Framework project, known as iFrame, was funded by the National Open Research Forum (NORF). The project worked with research performing organisations across Ireland to assess their existing research data management capabilities and identify where services, policies and infrastructure could be strengthened.

Participating institutions used a structured assessment process to examine their current provision and identify priorities for development. The work provided individual institutions with assessments and recommendations while also building a national picture of the challenges and opportunities facing research data management in Ireland.

Drawing on this work and wider consultation with the research community, iFrame developed recommendations for a national approach to research data management. These included shared infrastructure and services, clearer national guidance and coordination, subject-specific support networks and measures to strengthen research data management skills and expertise.

Promising research does not automatically become something that can be used in the real world. Moving new technologies beyond the laboratory often depends on researchers finding entrepreneurs, investors and commercial partners with the expertise and resources to develop them further.

In December 2025, University of Limerick's (UL) Technology Transfer Office hosted a Deep Tech Partner Opportunity Platform event at the Nexus Innovation Centre, bringing researchers developing emerging technologies directly together with potential investors and entrepreneurs.

Seventeen researchers showcased work originating from nine institutions across Ireland: UL, University College Dublin, University College Cork, Atlantic Technological University, University of Galway, Teagasc, Munster Technological University, Dublin City University and RCSI. The research spanned areas including semiconductors, food technologies, artificial intelligence, batteries, medical and educational technologies, renewable energy and robotics.

Researchers met entrepreneurs, investors, mentors and commercial leaders who could potentially help develop their work towards market-ready applications. The event was the fourth in a series of Business Partner events led by UL's Technology Transfer Office, creating an ongoing forum for engagement between publicly funded research and people with the experience to help translate it into commercial opportunities.

Health, nutrition and food-security information in Uganda is held across different systems, making it difficult to connect and use existing data effectively for policy and planning. Rather than creating additional parallel systems, an international project led by University of Limerick (UL) is examining how existing information can be better integrated.

IGNITE is a Research Ireland-funded collaboration focused on strengthening digital health systems for nutrition and food-security decision-making in Uganda.

During 2025, the project assessed digital health systems nationally and brought stakeholders together to identify priorities for connecting health, nutrition and food-security information. This work is informing the development of a shared set of essential data and a framework for how that information will be governed.

Led by UL, the project brings together Makerere University, Uganda's Ministry of Health, GOAL Uganda, UNICEF, the World Health Organization, the Food and Agriculture Organization, the World Food Programme and other national stakeholders.

Male factors contribute to around half of infertility cases, yet treatment options remain limited. One barrier to developing a better understanding of male infertility is surprisingly practical: researchers need to be able to separate the different cell populations within human testicular tissue so they can study what each does and how it may be affected in infertility.

Through a Research Ireland Industry Fellowship, University of Limerick (UL) researchers are working with Waters Biosciences, formerly BD Biosciences, to develop a reliable method for identifying and separating different cell types in human testicular tissue. The work uses fluorescence-activated cell sorting (FACS).

The collaboration combines UL expertise in male reproductive research with advanced cell-sorting technology and technical expertise that are not routinely available in an academic research environment. During 2025, the team made significant progress in understanding how human primary testicular cells can be identified and separated using FACS technology, an important step towards establishing a reliable method for isolating individual cell populations.

The partnership has also continued beyond the fellowship, creating opportunities for further joint research and technology development.

Artificial intelligence is increasingly being used to forecast how much municipal waste countries will produce. Those forecasts can inform decisions about waste infrastructure, circular-economy policy and compliance with European waste legislation. But University of Limerick (UL) research published in 2025 found that the way these AI models are commonly evaluated can give a misleading picture of how well they actually work.

The researchers reviewed 18 published studies using machine learning to forecast municipal solid waste. Fifteen relied primarily on R², a statistical measure of model fit, to judge performance.

Using Irish waste data from 2000 to 2020, the team compared R² with measures of prediction error. They found that the measures could give conflicting assessments of the same models, including a simple model that predicted no change from the previous year.

The researchers recommend combining measures of prediction error with diagnostic checks and testing models on later data than those used to train them.

Batteries hidden inside discarded electrical and electronic equipment can complicate recycling. Identifying them before waste enters mechanical treatment could make recycling safer while helping to recover valuable battery materials rather than losing them within mixed waste streams.

University of Limerick (UL) researchers are addressing this challenge through XBAT+, a project combining optical and X-ray imaging with artificial intelligence to identify battery-containing waste electrical and electronic equipment (WEEE) and distinguish between different battery chemistries.

The proposed system uses an AI confidence score to guide the next step. Items identified with high confidence as containing batteries can proceed to battery removal, while less certain cases undergo X-ray screening. Removed batteries can then be directed to dedicated collection and treatment streams.

Working with industrial partners Peregrine Technologies and KAON, the research is exploring how this technology could support safer recycling and improve the recovery of critical raw materials from discarded electronics.