As a reviewer, can I justify requesting data and code be made available even if the journal does not? 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.
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 


*

*to me at the time of review

*publicly at time of publication (the journal supports supplements)


also, how might I phrase such a request?

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.
 A: As far as getting data as a reviewer goes, you're entitled to it if you need it to complete your review properly.  More reviewers should be asking for data and assessing it.  Lots of journals have policies that they may require the data and analysis code for review purposes.
Availability at the time of publication isn't clear to me.  It seems that you're saying that you want to force the issue that the data be made publicly available as a condition of publication.  That's a bad idea if it's not journal policy already.  You're making publication an unfair moving target.  They submitted expecting that not to be a requirement and you, nor the editor, ought to be changing the game.
Unbeknownst to many researchers publicly funded researchers, they are required to make their data publicly available.  For example, most NIH grants have clauses where the researcher must be forthcoming with their data.  Most government granting agencies have data sharing clauses that force the researcher to share what they find (perhaps force is a bit strong given that it's very hard to lose a grant over that... perhaps lose renewal though).  The public paid for the data, therefore the public is entitled to it---in the case of human research, entitled to it anonymized.
Some of the most expensive and sensitive data to collect, human FMRI data, is also some of the most commonly made publicly available.  Not just PLoS, but major journals of the field require the submission of the data and maintain a publicly available data bank.  I think this says a lot to people who object for reasons of cost (it's very expensive), and privacy (it's human data from small studies and sometimes unique clinical populations that could be very sensitive).  Those are reasons that make that data more valuable to the public.  Researchers who withhold such data are doing a disservice to the people who bought it (everyone), and need a lesson in what their responsibilities are outside of their little lab and publication competition.
If the research was privately funded, genuinely privately funded, then best of luck.
A: Addressing the two situations seperately:
As a reviewer: Yes, I think you'd have grounds to ask to see the data or the code. But if I were you, I'd prepare to see things like pared down code, or a subsample of the data. People implement future research not being reported in this paper in their code all the time, and you've no entitlement to said code. Since I do mostly biomedical research, I'd also be prepared to have to deal with some fairly restrictive data use agreements.
In the journal itself: No. If a researcher wants to reproduce my results, they can approach me themselves to ask for code - that's why we have corresponding authors. For data, absolutely not, under no circumstances. My data is governed by IRB and confidentiality agreements - it's not just going to be made public. If I want a public-ish data set, I might simulate a dataset with similar properties (i.e. the "Faux-Mesa" network data available in one of the network packages for R), but as a reviewer, you've got no call to force that. If its a journal-wide requirement, then the authors knew their data/code would be public when submitting it, but if its not then no. Your role is to evaluate the quality of the paper itself (hence my being alright with it for the purposes of the review), not use your ability to contribute to the acceptance/rejection of the paper to push what is essentially a philosophical/political point outside the scope of the journal.
At best, I'd put a "I would strongly urge the authors to make their code and data available, where possible" in your comments, but I wouldn't phrase it any stronger than that, and I wouldn't put it in the formal list of "Things I think need fixing before this sees the light of day".
A: As John says 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.
A: 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.
