Question: As science must be reproducible, by definition, there is increasing recognition that data and code are an essential component of the reproduciblity, as discussed by the [Yale Roundtable for data and code sharing](http://reproducible-research.googlegroups.com/web/CISE-12-5-News.pdf).

In reviewing a manuscript for a journal that does not require data and code sharing, can I request that the data and code be made available 

1. to me at the time of review
2. publicly at time of publication (the journal supports supplements)

also, how might I phrase such a request?

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*update*: although I am interested in the general case, this particular case consists of a meta-analysis with all previously published data, and the code is simple linear models in SAS

*side note* the ability to make cross-study inference (as is the goal of meta-analysis) would be greatly enhanced if more studies provided raw data 

*update 2*: 

I requested the data and code from the editor for purposes of review, the editor considered the request reasonable, and I have received the requested material (sufficient but with cryptic variable names, no metadata, and few inline comments) within a day.

Answer: 
As [John says](https://stats.stackexchange.com/questions/14416/as-a-reviewer-can-i-justify-requesting-data-and-code-be-made-available-even-if-t/14424#14424) availability of data to reviewers should be a no-brainer; careful review should include replicating the analysis and as such necessitates access to the data.

With regards to public availability of the data following publication, I'd say that battle should be fought with the journal generally rather than with regards to a specific submission.

On a more general note, funding agencies and IRBs are becoming increasingly aware that data sharing is both scientifically and ethically necessary component of research. By increasing the availability for re-analysis that could yield new results of correct erroneous reports, data sharing increases the potential benefits to research, thereby modifying the cost/benefit tradeoff to the advantage of the participants of the research. Certainly it is necessary to inform participants of the possibility that their data will be shared, and it is also necessary to set up safeguards to prevent increased risk of identification to participants, but these can be achieved in most circumstances. In my own research, I assure participants (and my IRB) that (1) data will be stored in a strong encrypted format (updated as decryption technology advances), (2) data will be shared with qualified researchers upon request, but only if they agree (3) to similarly store the data in a strong encrypted format (updated as decryption technology advances), (4) refrain from sharing the data (instead referring requests to me), and (5) refrain from connecting the data with data from any other sources unless (6) the data connection is explicitly permitted by an IRB, who would determine whether the connection would unacceptably (relative to the potential benefits of the project) increase the risk of identifiability.
I don't have any experience with this, but it seems to me that you might be able to insist on #1 as a part of your own due diligence in reviewing their results. I don't see how you can insist on #2, though.