More data than we can handle is no excuse to give up our efforts to promote data access, but it may make us think about new ways to make it sustainable.&#xd;&#xa;[This draft was written in the hope that participants of the Sage Congress will write an Nature Genetics Editorial in the manner of Tom Sawyer&#x2019;s white fence (Twain M. 1876). All contributions received by April 10th 2011 will be attributed.]&#xd;&#xa

Myles Axton

English

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More damn lies about data access 
More data than we can handle is no excuse to give up our efforts to promote data access, 
but it may make us think about new ways to make it sustainable.
[This draft was written by Myles Axton in the hope that participants of the Sage Congress will 
write an Nature Genetics Editorial in the manner of Tom Sawyer’s white fence (Twain M. 1876). 
All contributions received by April 10th 2011 will be attributed.]
Sharing is the concept promoted by kindergarten teachers while the children under their 
instruction are learning from one another to make deals that are mutually beneficial and 
improving their ability to negotiate. Data sharing is a misnomer for what we are doing as adults. 
In science, data are either traded in a market for information or consigned to write-only 
databases. We should perhaps discuss incentives to an effective ideas market rather than restrict 
our discussion to ensuring open data deposition.
Data are often inaccessible or not usefully presented because some data producers do not want 
data to be used by everyone. There is a natural barter process among data holders that 
generates skeptical evaluation as well as discoveries. Whether this process among privileged 
labs is more productive than the scrutiny of many eyes on open data is not for discussion, we 
clearly need both.  What has not been widely appreciated is that funders with their data access 
mandates risk short-circuiting the economy of knowledge production. It also costs to format and 
curate data and those costs are not fully borne by funders because they have no metrics with 
which to judge curation effort and they do not want endless commitment to resources that may 
not be used. 
NCBI and EBI have been the trusted and accountable partners researchers have relied upon for 
sustainable data storage, without which we would be hard pressed to promote any data access 
model. However, recently, NCBI has closed two of its repositories for raw nucleotide sequence 
data http://www.ncbi.nlm.nih.gov/sra mainly because of an explosion of next generation 
sequencing runs that cannot be readily reduced to unambiguous calls. There are alternative 
places to store data. Until SRA returns, journals may have to trust the stability of the links to 
institutional databases that authors provide and handle the complaints of frustrated data users. 
To this end, it may help to have data producers publish citable data management plans 
explaining how to access and use the data. Cloud computing may eventually provide a solution to 
sequence data storage provided there is a suitable business model. Providers will only keep the 
data from which they can make money and reputation.
There is hope that we can arrive at solutions because we share common interests in promoting 
data access. The principle that your reputation is made in the labs of others means that good 
citizenship is good business. You simply cannot publish enough papers on your data yourself to 
equal the productivity of the researchers you inspire. The interests of the journals you publish in 
and the institutions and agencies that fund your work are likewise aligned to do everything they 
can to enable data sharing by their need to demonstrate that they are contributing to the impact of 
the datasets you produce. 
The sustainability of data access is often discussed by publishers of journals of record who have 
in part ensured the stable accessibility of the (albeit smaller) datasets of the past.  Journals could 
step up and charge depositors what it really costs to make a large dataset accessible in 
perpetuity. If they do charge users for access, the price should be transparently related to 
distribution costs and the need to sustain the archive. Maybe sequence data will not accumulate 
exponentially forever.  Simple discounting suggests that it will be cheaper to resequence 
genomes than to store existing reads. It may be that many large datasets are not really useful for 
research but are consigned to public databases as merely the burn-ins for technology that moves 
on. Still, unless we develop suitable metrics for data citation and promote their adoption, the 
experiment to evaluate the utility of data has not been done.  Maybe the funders’ need for data to 
be useful coupled with the incentive for publishers to make open access sustainable would 
provide the motive to do this properly.
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Other incentives that can help with data access are to link author and contributor roles to data 
accessions and to link data accessions semantically into a concept web. Attribution licenses for 
articles and data are a good concept but lack enforcement. Attribution is also currently 
insufficiently granular both at the data level and with respect to the author roles. There are no 
agreed data citation metrics and examples of resource reallocation or career decisions to point to.
In discussions about ORCID (http://www.orcid.org/) and researcher disambiguation, it is essential 
that we discuss distributed as well as centralized ways for researchers to track and display their 
career achievements, connections and productivity. Popular sites like PubMed and Wikipedia 
provide places to start developing metrics, but it is important to give researchers a choice of 
individual, institutional, funder, journal and consortium sites to choose from and to agree on what 
we are counting. Everyone needs to be guaranteed minimum space and the ability to garden their 
own reputations. Institutions need to experiment with evaluating the totality of scholarly 
productivity, for example by participating in experiments like Vivo (http://vivoweb.org/).
Links are often unequal in not giving credit in both directions. Even asynchrony in establishing 
bidirectional attribution between databases or between databases and journals can lead to loss of 
timely attribution. The semantic web will work fine initially with small numbers of trusted early 
adopter databases with strong hierarchic organization. Reliance on linked data URIs may limit its 
adoption and eventual success. Why? Many small databases are happier with relational 
organization and only link to the outside world via generic high level container URIs that leave 
staff free to move items around at will. Unless these items carry indelible universal identifiers 
(UUIDs) there is no external global reference.  It may therefore be better to label everything twice 
(belt and braces) as argued by Josh Knauer in his critique of Tim Berners-Lee’s Concept Web 
http://rhiza.com/2010/05/27/berners-lee/.
The final barrier to data access is related to the way in which we currently protect human subjects 
and obtain their informed consent. Institutional review boards protect individual institutions as well 
as the research subjects they recruit. This concept has worked well but without a duty to put their 
rules and deliberations in the open, IRBs depart progressively from universally agreed ethical 
principles in ways that make it ever harder to combine data collected at multiple centers into well 
powered studies. Professional bioethicists dig ever deeper and address subsets of the issues in 
their field. Research subjects given multiple choices about protection and access to their data 
distribute pretty evenly over the options. A requirement for IRBs to deposit their rules and 
deliberations on the web might be the only way to encourage harmonized and transferrable 
consents because no central agency can ever persuade diverse institutions to adopt an “IRB in a 
box” franchise.
[Please rewrite this editorial to suit the data access aims of the Sage Congress]
http://www.nature.com/nmeth/journal/v7/n7/full/nmeth0710-495.html
http://www.sciencemag.org/content/331/6018/666.full
http://www.w3.org/DesignIssues/LinkedData.html
Twain M (1876) The Adventures of Tom Sawyer. Barnes and Noble Classics, New York, NY, 
USA, 2003, ISBN 1-59308-068-9
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More damn lies about data access

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More damn lies about data access

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