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Converting big data into useful data is a difficult challenge.
The problem of securing biological research data is a difficult and complicated one.
In case of existing concrete structures, the estimation of the characteristic strength values from limited data is a difficult, but important task.
Modernizing the infrastructures themselves, along with the way health companies integrate and exchange data is a difficult task — but it's also an important one.
Generating, grouping, and labeling free-sketch data is a difficult and time-consuming task for both user study participants and researchers.
The generation of meteorological surfaces from point-source data is a difficult but necessary step required for modeling ecological and hydrological processes across landscapes.
Similar(43)
The economists acknowledge that these statistics are open to question, since countries have been known to fudge their data and collecting accurate information is a difficult task.
The polling data is a bit difficult to interpret.
However, because of the complexity of tunnel structures and a long data interpretation period, the analysis and interpretation of field data is a relatively difficult and time-consuming task.
To accurately infer the number of total susceptibility variants in the genome from GWAS data is a very difficult problem, and the methodology presented here should only be interpreted as a rough estimate based on the exponential distribution assumption.
However, processing and analyzing such large volumes of data is a technically difficult, time-consuming task which requires bioinformatics expertize and access to computing clusters with high-performance infrastructure.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com