Knowledge regarding gene bank accessions characters facilitates the identification of the most promising for future use. Sampling of accessions from a cultigen available at a gene bank may be based on diversity and variability analysis relying on characterization or evaluation data, DNA markers, or both. Core subsets may aid selection by guiding users to genetic differences. Evaluation results must be shared promptly and widely worldwide, so germplasm users can request them for further utilization in plant breeding or research on plant genetic resources. This chapter relates therefore to gathering accurate and precise evaluation of diverse accessions in well-designed trials. Such knowledge is essential for identifying the most relevant accessions for further use. This information needs to be shared widely and quickly with users to achieve a maximum impact because any germplasm user should be aware of the potential of gene bank accessions in order to fully exploit such plant genetic resources.This chapter also illustrates the need for an objective assessment of gene bank accessions, deals with sampling of core subsets for evaluation of gene bank accessions, explains the principles of experimental design for trials of gene bank accessions and provides basic knowledge regarding trial data analysis.

Data management is key to conservation and this includes: the types of data, how data are recorded, data standardization and conservation data management. The main sources of data are passport (provenance) and ecogeographic data, characterization and evaluation data, and management or curatorial data, each of these data are collated and managed by conservationists. Although associated with these data management types, three fundamentally important pieces of data are pivotal. The accession number (or unique identifier), the scientific name of the taxon being conserved and the date of the conservation intervention (e.g. seed collection or population monitoring date). Often today data management is assisted by using a conservation data management system (e.g. GRIN Global) to improve efficiency and help enforce data standardization. Further data management is assisted by use of data collection templates or accession / population descriptors. Much of these data are then made available to the user community via web-based platforms such as EURISCO or GBIF. The importance of access to and ownership of the various kinds of data is emphasized as fundamental to good data management practice.