Data Sharing is recognised by policy makers as a key enabler for research. However, different research communities are at different stages in adopting the cultural and technological changes required for practical research data sharing. Engineering sciences are seen as relatively low adopters of data sharing in comparison with other research disciplines. Further advocacy and practical development need to be undertaken for engineering researchers to further adopt data sharing practices in the future. The Data and Analytics Facility for National Infrastructure (DAFNI) is leading a study, Data Infrastructure for National Infrastructure (DINI), into data sharing practices within infrastructure systems engineering. In this domain, we are interested in the engineering of systems that involve the interaction of physical components, machines, or buildings within a common ecosystem such as water or energy supply, transport networks or telecommunication links, and the impact of systems within the natural and human (economic and social) environments. The impacts of this research are less on the construction and maintenance of assets, but rather on the wider commercial and government policy landscape. Data sources within Infrastructure Systems Research are often the operational data of commercial enterprises or local or national government rather than the “facts-of-nature" from prior research. Obtaining such data requires negotiating with commercial and government entities, and commercial confidentiality and IP are of high concern. Some data can fall under Critical National Infrastructure as it may expose vulnerabilities to hostile actors, while other data may be personal sensitive, for example energy usage information at a household level. Further, for impact, researchers need to share results with stakeholders in government and industry, and data providers may be willing to share data with researchers, but they may be reluctant to share with impact partners. Data sources are also highly diverse, from many organisations and systems, and the data needs to be interoperable with data from other domains, such as environmental sciences, social and economic data, health data, and within an underlying geospatial context. This increases the diversity of data and its supporting tools and standards. These characteristics form significant barriers to data sharing; however, the potential impact of enhanced data analysis on society could be great by improving decision making and investment in infrastructure. DINI is consulting across the community, focusing on a representative sample of researchers and stakeholder organizations from the energy supply, water supply, and transport (road, rail, air) sectors to explore the barriers and opportunities for data sharing, and identify best practices, supported by use cases. The results of this engagement will be analysed to develop recommendations for further actions to support and enhance data sharing within this sector. In this presentation, we will discuss the challenges of data sharing in this sector, present the results from the community consultation, and propose recommendations for further action to support data sharing and reuse.