An epic effort by our world university rankings data supplier, Thomson Reuters, to collect information from hundreds of universities around the world concluded successfully last week.
The rankings will be based on three key data sources: research publication data already owned by Thomson Reuters; the results of our academic reputation survey; and information on a range of factors such as staff, students and income that has been provided and verified by institutions themselves.
Thomson Reuters supported universities in making their submissions with published guidance, international webinars and tutorials, and the deployment of a dedicated team of data editors around the world.
But in such a big exercise, some mistakes or anomalies will no doubt creep in. So, what then?
Simon Pratt, project manager for institutional research at Thomson Reuters, said the company had introduced a data validation system to ensure quality control.
Logical data errors, usually caused by mistakes in data entry or misinterpretation of the definitions, are easy to spot and weed out algorithmically. Data are also compared with information from reliable third-party sources, such as the UK's Higher Education Statistics Agency, to highlight any serious variations.
Thomson Reuters will also identify any further errors by "comparing data to expected values and looking for outliers", Mr Pratt said. "For example, if a university has a funding per person ratio that is far higher than the ratio for the university's peer group, we can recognise that there may be a potential problem.
"Once an error has been identified, we contact the university and ask for a correction or explanation."
We thank universities for their patience, understanding and cooperation through this process.