Audio Visual Archiving Through Automated Requirements Match- AVATAR-m
In plain English
AI plain-English summaryArchivists are drowning in digital data, and this project builds the software tools to help them decide what to keep, where to store it, and how much that will cost. The problem is that digital archives—from broadcasters storing decades of video to geologists holding seismic surveys—need systems that are cheap, scalable, and guarantee data won't vanish or become unreadable. Current storage technology is complex and uses jargon that archivists don't speak. This project brings together archive users, storage developers, and academics to build management systems that let archivists configure storage using their own terminology, and to understand the trade-offs between cost and quality of service. The team will also develop new algorithms that match how data is stored to the characteristics of that data—for example, storing video differently from seismic readings. If successful, the tools could transform the generic archiving industry. They would allow organisations to set a required level of data persistence and accessibility, then automatically select the most cost-effective storage technology to meet it. This matters because the amount of digital data that needs long-term preservation is growing rapidly, and the cost of storing it badly—or losing it—is high.
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