This memo provides information for the Internet community. It does not specify an Internet standard of any kind. Distribution of this memo is unlimited.

In many disciplines, data are highly decentralized across thousands of online databases (repositories, registries, and knowledgebases). Wringing value from such databases depends on the discipline of data science and on the humble bricks and mortar that make integration possible; identifiers are a core component of this integration infrastructure. Drawing on our experience and on work by other groups, we outline 10 lessons we have learned about the identifier qualities and best practices that facilitate large-scale data integration. Specifically, we propose actions that identifier practitioners (database providers) should take in the design, provision and reuse of identifiers. We also outline the important considerations for those referencing identifiers in various circumstances, including by authors and data generators. While the importance and relevance of each lesson will vary by context, there is a need for increased awareness about how to avoid and manage common identifier problems, especially those related to persistence and web-accessibility/resolvability. We focus strongly on web-based identifiers in the life sciences; however, the principles are broadly relevant to other disciplines.

We analyzed the UNIX 4.2 BSD file system by recording user-level activity in trace files and writing programs to analyze the traces. The tracer did not record individual read and write operations, yet still provided tight bounds on what information was accessed and when. The trace analysis shows that the average file system bandwidth needed per user is low (a few hundred bytes per second). Most of the files accessed are open only a short time and are accessed sequentially. Most new information is deleted or overwritten within a few minutes of its creation. We also wrote a simulator that uses the traces to predict the performance of caches for disk blocks. The moderate-sized caches used in UNIX reduce disk traffic for file blocks by about 50%, but larger caches (several megabytes) can eliminate 90% or more of all disk traffic. With those large caches, large block sizes (16 kbytes or more) result in the fewest disk accesses.

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