<div dir="ltr">I think throwing out data because it is wrong is a mistake. There is a matter of degree here and since tz info is not authoritative anyway, little is to be gained. Do we think that we can approach anything like 99.99% accuracy by getting rid of suspect data and therefore make the claim that it is more "authoritative"? I think not. Certainty about what time was showing on most clocks in a given area will always be approximate until there is a global control mechanism for setting time zones legally and technically which probably won't happen until there is a one world government (don't hold your breath). There are approximately 60 Amish farms in the Pulaski, NY area all of which observe standard time year round and since we do business with them we have to remember to keep 2 clocks. This was not even an issue a decade ago.<div>
<br></div><div>I really wish that Shanks et al had not "guessed" at transition times, but instead included reports about what transitions were certain and then showed instead the date ranges where there was uncertainty. They probably interpolated between two reports that they could find in their original research, but since they didn't publish their procedures this is a guess on my part. Since there are wide uses for this data I have to agree with Stephen Colebourne here.</div>
</div><div class="gmail_extra"><br><br><div class="gmail_quote">On Sun, Jul 27, 2014 at 5:37 AM, Stephen Colebourne <span dir="ltr"><<a href="mailto:scolebourne@joda.org" target="_blank">scolebourne@joda.org</a>></span> wrote:<br>
<blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div class="">On 27 July 2014 08:25, Clive D.W. Feather <<a href="mailto:clive@davros.org">clive@davros.org</a>> wrote:<br>
> If we know or have good reason to believe that the data is<br>
> completely bogus, then there's no point in retaining it.<br>
<br>
</div>There are two distinct steps here;<br>
1) knowing it is wrong<br>
2) knowing what is right<br>
<br>
It is important not to conflate the two.<br>
<br>
What many (most?) of the list want is for the change to occur only<br>
when both steps are true. What is proposed is for the change to happen<br>
only when the first step occurs (or is claimed - few of us can<br>
actually judge whether it is wrong).<br>
<br>
The reason for requiring both steps to happen before change is that<br>
many (most?) on the place a huge value on stability. We want there to<br>
be the absolute minimum changes necessary to the data, as that<br>
stability is hugely valuable to end-user applications. ie, stability<br>
is the "point in retaining it" you describe.<br>
<br>
As an example, consider Sierra Leone<br>
<a href="https://github.com/eggert/tz/commit/4b4e789d5c5ee79366b4606d139cbb9eb1d5a28d#diff-f4f52c274b8b0af7593e8d85f45ae7f1L1070" target="_blank">https://github.com/eggert/tz/commit/4b4e789d5c5ee79366b4606d139cbb9eb1d5a28d#diff-f4f52c274b8b0af7593e8d85f45ae7f1L1070</a><br>
<a href="https://github.com/jodastephen/tzdiff/commit/c812da9e12bd6f8aa52fa2dd758e236581c23a29#diff-2bfd47a6358d362c0bd99625a1ab8532L1" target="_blank">https://github.com/jodastephen/tzdiff/commit/c812da9e12bd6f8aa52fa2dd758e236581c23a29#diff-2bfd47a6358d362c0bd99625a1ab8532L1</a><br>
where two separate sets of DST affecting 13 years and dates as recent<br>
as 1960 have been obilterated. Where is the discussion of this<br>
specific (huge) change? Where is the justification?<br>
<br>
And there are many other examples.<br>
<span class="HOEnZb"><font color="#888888"><br>
Stephen<br>
</font></span></blockquote></div><br></div>