Data integrity in the context of laboratory analytics is a must, particularly in regulated environments. However, how is data integrity exactly defined, and what are the software features required to achieve it?

A new Metrohm white paper answers these questions based on examples from modern Near-Infrared Spectroscopy (NIRS) Software.

Data integrity is commonly defined by a number of properties, which are summarized by the acronyms ALCOA and ALCOA+, respectively. Hence, ALCOA stands for «attributable», «legible», «contemporaneous», «original», and «accurate», while ALCOA+ extends these attributes by the properties «complete», «consistent», «enduring», and «available».