Bio-mirror improves on download speeds, but requires that the data be replicated across all servers, is restricted to only very popular genomic datasets, and does not include the fast growing datasets such as the Sequence Read Archive (SRA) ( ). Bio-Mirror ( ) was started in 1999 and consists of several servers sharing the same identical datasets in various countries.

Many different solutions have been proposed to help with many of the challenges of moving large amounts of data. This allows faster transfer times and decentralization of the data. B) The peer-to-peer file transfer protocol, BitTorrent, breaks up the dataset into small pieces (shown as pattern blocks within black box), and allows sharing among computers with full copies or partial copies of the dataset. This can cause transfers to be slow due to bandwidth limitations or if the host fails. Illustration of differences between traditional and peer to peer file transfer protocols.Ī) Traditional file transfer protocols such as HTTP and FTP use a single host for obtaining a dataset (grey filled black box), even though other computers contain the same file or partial copies while downloading (partially filled black box). Even if bandwidth limitations are very large, these file transfer methods require that the data is centrally stored, making the data inaccessible if the server malfunctions. Unfortunately, as the number of requests for data increases and the provider's bandwidth becomes saturated, the access time for each data request can increase rapidly. In addition, the server of the data has to have a large amount of bandwidth to provide adequate download speeds for all data requests.

These protocols require that a single server be the source of the data and that all requests for data be handled from that single location ( Fig. However, the practical aspect of moving data from one location to another has relatively stayed the same that being the use of Hypertext Transfer Protocol (HTTP) or File Transfer Protocol (FTP). Considerable effort and attention has been given to improving the portability of data by developing data format standards, minimal information for experiment reporting –, data sharing polices, and data management –. In parallel, and also at an increasing rate, is the demand to make this data openly available to other researchers, both pre-publication and post-publication. The amount of data being produced in the sciences continues to expand at a tremendous rate.

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