The 'omics sector, particularly proteomics, is experiencing rapid growth in the amount of data being produced, and in the complexity of the scientific questions being asked. There is now an urgent demand for computational and programming tools to analyze this information, along with the infrastructure to support it. Unfortunately, bioinformaticians tend to be in short supply, which exacerbates this challenge. To support efforts to solve this issue , we are launching a multifaceted community to support Australian life scientists, their collaborators, the proteomics community, and the Australian Core Facilities (ACF). The mission of the Australasian Computational Proteomics community is to democratize decision-making, enhance access to computational resources, and promote the free circulation of gold standard workflows and standard operating procedures (SOPs), as well as best coding practices and open-source software. We believe a community-driven approach is the most effective way to tackle big-ticket issues: sharing the workload involved to affect change, and establishing a level of governance that can drive growth and change when it is most needed. This open community will encompass multiple channels for engagement, including a Slack workspace for real-time discussions and a community GitHub for sharing codebases and resources. There are also plans for future expansion to meet the evolving needs of the field, including building educational support for Early Career Researchers (ECRs) to learn best-practice bioinformatics, thereby ensuring the next generation of scientists is well-equipped. Additionally, we aim to keep members updated on the latest infrastructure offerings and support from Australian BioCommons. By fostering this collaborative and inclusive hub, we will strive to support the growing computational needs of proteomics and life sciences research. This poster will present the current community, its forums, and its vision for beginning to address the complex set of software, data, and infrastructure challenges facing computational proteomics .