One of the difficult things when building software for the cannabis space is the lack of standards. This is very visible across the laboratory space. Each of the software vendors (BioTrack, Akerna/MJPlaform/LeafData, METRC) has their own way of referencing hundreds of metrics. Building software to sit on top of these platforms (like our Lab Portal) requires some tedious mapping. Additionally, each government agency has their own set of rules and requirements that increase the data-clarity burden.
Of course, these dozens of different ways of doing identical works is wasteful, prone to error and makes cross-market comparisons difficult.
Briefly, these Lab Metrics are all the items we care about for testing the cannabis products. This include General Inspection, Potency, Pesticides, Solvents, Microbes, Terpenes and other attributes. There are almost 200 (we track 187 as of this writing) – and currently there is no agreement on reference.
Many have similar names – but even some similar names may have different meaning in different systems. And each system has a unique way of representing their data – information that is industry standard. These metrics however are not (yet) data-specification standard.
All these metrics from the Lab can (and should be) represented in tabular-format – that means a spreadsheet (or data-table). It’s pretty simple right? Maybe just add the Test Group, Test Name and Test Result Value and Test Result Unit of Measure. But we’re still talking past each other, because names and groups and interpretation can still deviate. And we don’t want that.
In our API project we have created a reference data-set for Laboratory Metrics. Each metric has been given a unique-id that will not, ever collide with any other id (assuming that others use ULID properly). And now, we can map Laboratory Metrics across systems, across states, across laboratories and across products.
By following these specifications, software providers, laboratories and other businesses in the cannabis space can accurately and precisely communicate this critical data.