A new low in data sharing: The Taiwanese Outbreak of H5N8

I am interested in the spread of H5N8 avian influenza and after seeing the spread of cases in Taiwan on the OIE website I have been eagerly waiting to see sequence data emerge to carry out some detailed evolutionary analysis. I have waited and waited and waited and today I got my RSS feed from Google Scholar to say a paper is available showing the relationship to the Korean outbreak. The authors had been hoarding the data to publish it rather than making it more widely available and being pipped to the publication, as we live by the law of publish or perish.

Now it is published the data must be available for everyone as it no longer matters for priority of publication. I checked the sources Genbank, GISAID (the worlds first password access only resource for sharing publicly funded biological sequence data) and a Taiwanese government database - http://ai.gov.tw/index.php?id=720  It is so easy to find a database that is only in Chinese script with no English translation. That is the perfect way to share data.

Anyway we should all know more languages and they have a good reason to publish in their native language. Google can translate it anyway. So there is a page with the sequences and here is the link http://ai.gov.tw/index.php?id=704 There is just one slight catch. These are image files. In order to extract the sequences you are going to have to retype them all from the images. 1600 characters for each entry! That is not data sharing. That is not a public database. That is not good practice or good science. That is obstruction pure and simple.

Japan made its data available almost immediately as well as issuing local warnings to farmers about the risk from wild birds of the spread of the new H5N8 variant. The result of this was a relatively small number of cases in domestic birds. However the lack of transparency from the Taiwanese laboratories contributed to the deaths of 3.2 million birds including nearly 60% of the domestic goose population. This is an avoidable disaster that has cost millions to farmers and the scale of which could have been reduced by improved sharing of information.