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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.

Data citation and the derivation of semantic constructs directly from datasets have now both found their place in scientific communication. The social challenge facing us is to maintain the value of traditional narrative publications and their relationship to the datasets they report upon while at the same time developing appropriate metrics for citation of data and data constructs.

Although susceptibility loci identified through genome-wide association studies (GWAS) typically explain only a small proportion of the heritability, a classical quantitative genetic analysis now argues that considering together all common SNPs can explain a large proportion of the heritability of these complex traits. A related study provides recommendations for the sample sizes needed in future GWAS to identify additional susceptibility loci.

Article in Nature Genetics:

Data worthy of integration with the results of other researchers need to be prepared to explicit export standards, linked to appropriate metadata and offered with field-specific caveats for use. Data exchange may need to be taught and discussed in handshaking workshops.