A paradigm shift in open science is occurring as national funding agencies for scientific research are requiring that researchers guarantee to publish their data in repositories in accordance with the FAIR Principles. Thus, effective data sharing among repositories has become a critical concern for multiple stakeholder groups: scientists sharing data, data curators organizing and coordinating datasets, technologists crafting repository tools (including infrastructure, network, security, graphics, and more), and end users consuming the data. To balance the needs and goals presented by the other stakeholder groups, data curators must be strategic in their role to successfully integrate data and metadata files from various sources and organize them for sharing via science gateways. Data curators ensure that data submissions to repositories adhere to the FAIR Principles, addressing issues that can arise from data or metadata. For instance, curators often encounter a lack of database fields that would allow benchmarking queries and reports to be created. There may also be problems with the data itself, such as incorrect formatting, missing data, duplicate values, etc. Data ingest workflows should be carefully designed to take these types of issues into consideration so they are rectified (or at least minimized) and not exacerbated. The complexity of ingesting datasets requires planning to preserve both data accuracy and incorporation of FAIR standards. Since data curators serve as a connection between technologists and scientists, they are uniquely positioned to offer insight on how to help digital repositories maintain FAIR and open standards. This poster presents a "data curation toolbox," useful tools and tactics that data curators can employ in their professional practice. This toolbox is generalized to allow for reproducibility by curators working on other gateways as well as empowering scientists to perform curation on their own projects.