Gene expression and regulation is the foundation of plant development, organ specific differences and response to environment. RNA-Seq is a high-throughput sequencing technology that has become the primary platform for the study of gene and transcript level expression. Public data archives store vast volumes of raw RNA-Seq data that requires specialist analysis skills and large-scale computational resources to be of value to biologists and is thus an underutilised resource. Since our first attempt at accessing and processing quantitative gene expression data from publicly archived RNA-seq samples, the number of barley RNA-seq datasets have increased >5 fold, which brings challenges in the scale of processing and visualising large numbers of datasets. We propose to build on our existing barley gene expression database and website, EORNA, to provide a scalable, highly automated system for the discovery, retrieval and quantification of barley RNA-seq data. Comparative visualisation of transcript-level expression data will be coupled to improved curation of the experimental metadata. We will update and expand our current EORNA database with all available public barley RNA-Seq data, quantified against the latest state-of-the-art barley pan-transcriptome reference dataset. We will provide scalable transcript expression level plots with direct access to gene sequence information and annotation through an enhanced and easily searchable website. Finally, we will make the entire system generic and provide it as a free resource to the wider scientific community so that researchers working on other organisms can establish their own species-specific databases. Together, this will create an essential gene and gene transcript discovery resource for barley researchers and breeders, and the wider scientific community.