Perdita Barran

Meet Perdita Barran

In analytical science, laboratory data is recorded in the form of a measurement that can be linked to a fundamental physical property for example mass, or electronic state, or the effect on incident EM radiation imparted by molecular structure. This primary measurement is then translated via statistical manipulation and/or additional data to a form more “convincing.” In this manipulation some of the integrity of the original measurement can be irrevocably lost. For example, in mass spectrometry based omics science, the x values are useful, they are the mass or a given separated ion, but the y values frequently are discarded since working out the bias in ion intensity is deemed “difficult” or not important enough to consider. This data then is translated to knowledge, but at what loss of its integrity? The same is true for image analysis, where the practitioner decides which parts of the image to report and can with ease discount much, some of which may be inconvenient to explain or worse may contradict the results.

In an age of alternative facts, fake news and a world of image and identity manipulation or hallucination coupled with ever increasing availability of data there is a clear need for a multidisciplinary understanding and definition of what is real. No matter which way you determine the truth, it has to be the same on each and every occasion; thus in Chemical Analysis, Truth is represented by Mass, Abundance, and Identity. It is fundamental to analytical science to retain truth in data as it is translated from initial measurement to applied knowledge. This relies on the integrity of analytical measurement scientists documenting how raw data is inevitably manipulated and altered as it is translated to useful knowledge.

A hundred years ago much biological research was conducted simply using an optical microscope while most chemists only used a thermometer; now we have the ability watch proteins fold in live cells; to collect multi-“omic” data from large patient cohorts with the aim to personalize medicine; and to understand at the atomic level by analyzing tissue the interactions between drug molecules and their targets. In our interconnected world, the spread of information (real or “fake”) is so rapid that the need for multidisciplinary approaches to critique and validate data is ever more pressing.

As Mark Twain said:

“Truth is the most valuable thing we have. Let us economize it.”

A consequence of rapid technological development is a need to train researchers to understand the translation of vast quantities of raw data into useful knowledge whilst retaining the provenance (metadata). It is vital that we train people to responsibly use new techniques and experimental approaches, whilst being true to the measurand – with the ability to take projects from conception to commercialization. It is essential for public understanding, adoption and acceptance of new technologies that we can responsibly translate the data along with meaningful metadata into something of use. Coupled with this is the need to understand the nature of the measurement and the responsibility around data collection provenance and curation. The collaboration of experts in analytical science, data, responsible innovation, and policy is key to ensure the successful translation of true measurement to knowledge.