Every research project necessitates data, often requiring sharing and collaborative review within a team. However, there is a dearth of good open-source data sharing and reviewing services. Existing file-sharing services generally mandate paid subscriptions for increased storage or additional members, diverting research funds from addressing the core research problem that a lab is attempting to work on. Moreover, these services often lack direct features for reviewing or commenting on data quality, a vital part of ensuring high quality data generation. In response to these challenges, we present DataDock, a specialized file transfer service crafted for specifically for researchers. DataDock operates as an application hosted on a research lab server. This design ensures that, with access to a machine and an internet connection, teams can facilitate file storage, transfer, and review without incurring extra costs. Being an open-source project, DataDock can be customized to suit the unique requirements of any research team, and is able to evolve to meet the needs of the research community. We also note that there are no limitations with respect to what data can be shared, downloaded, or commented on. As DataDock is agnostic to the file type, it can be used in any field from bioinformatics to particle physics; as long as it can be stored in a file, it can be shared. We open source the code here: https://github.com/lxaw/DataDock

翻译：每个研究项目都需要数据，通常需要在团队内共享并进行协作审查。然而，目前缺乏优质的开源数据共享与审查服务。现有的文件共享服务通常要求付费订阅以增加存储空间或添加成员，这导致研究经费从实验室试图解决的核心研究问题中分流。此外，这些服务往往缺乏直接用于审查或评论数据质量的功能，而这是确保高质量数据生成的关键环节。为应对这些挑战，我们提出了DataDock，一个专为研究人员设计的文件传输服务。DataDock作为一个应用程序托管在研究实验室的服务器上。这种设计确保了只要拥有设备和互联网连接，团队即可在不产生额外成本的情况下实现文件存储、传输和审查。作为一个开源项目，DataDock可根据任何研究团队的特殊需求进行定制，并能持续演进以满足研究社区的需求。我们还指出，在可共享、下载或评论的数据类型方面没有任何限制。由于DataDock对文件类型无特定要求，它可应用于从生物信息学到粒子物理的任何领域；只要数据能存储在文件中，即可进行共享。我们在以下地址开源代码：https://github.com/lxaw/DataDock