For clinical biobanking, facilitating such integration involves huge amounts of work aimed at standardization and harmonization of data and tissue provision as well as efforts aimed at establishing quality control, certification of workflows, substantial and procedural benchmarks for data and tissue collection and management and evidence-based data models (Riegman et al. 2006; Mook 2011)).
Data standards are an essential prerequisite to any large scale information infrastructure because they provide benchmarks for data quality and define how information are formatted and categorized in order to be stored, managed, searched for and used across many different software applications (Bowker, 2008).
There is a need to establish robust benchmarks for data analysis for the comparison of different analytical approaches/software.
Benchmarks for data completeness and accuracy were set at 95.0%; kappa and intraclass coefficient (ICC) calculations were also utilised to supplement this analysis.
This model is an extension of the Poisson regression model, the benchmark for count data, which accounts for over-dispersion of data (Coxe et al., 2009).
Deformation was calculated using benchmarks BM34 (for data between April 2006 and April 2007) and BM25 (for all other data periods) as references (See Fig. 1 for locations of BM34 and BM25).
In contrast, with imputation by either of the three map-dependent methods Beagle, FImpute, and IMPUTE2, the correlation between RD estimates based on imputed and original 90 SNP data was higher than the respective benchmark for all missing data levels.
We propose a micro-benchmark for XML data management to aid engineers in designing improved XML processing engines.
A benchmark for this qualitative data, including its limitations, has been set by the NICE deliberations and evaluation.
Benchmark data, for comparison with the practice's own data, were named as one of the most supportive parts of the method.
