Shane Ian Murphy on TriParty Tokenisation: Give Every Sample Field a Meaning

A column headed “quantity” looks perfectly understandable until two people try to explain it. One may imagine individual objects. Another may assume kilograms. A third may believe the number includes packaging. The disagreement can remain invisible because everyone recognises the word. That is why I would begin a sample data exercise with a dictionary before spending much time on the appearance of the table.

I am Shane Ian Murphy, cofounder of TriParty Tokenisation. This is my affiliated founder commentary on a process exercise I would like to use when developing explanations. It describes a proposed teaching method, not work already completed by the business. My interest here is modest: can someone understand an invented record without borrowing the author's unstated assumptions?

For the exercise, imagine a table describing fictional storage containers. It contains a sample reference, a recorded quantity, a unit, a measurement date and a note. These are teaching objects, not investment instruments or records of real inventory. Their simplicity lets the group concentrate on language. Even this small table creates enough ambiguity to make a dictionary worthwhile.

I would give every field a short definition and a concrete example. “Recorded quantity” might mean the amount entered for this particular fictional observation, expressed in the separate unit field. It would not mean capacity, a previous observation or an amount someone expects to find later. Naming those boundaries helps because a useful definition explains what a value actually answers.

Units deserve their own attention. A reader should not have to infer them from the size of a number. If the sample uses kilograms, I would write kilograms and use the same convention throughout the exercise. If another unit is introduced for comparison, that change should be visible in the record. I would avoid adding conversion arithmetic unless the learning objective requires it. Extra arithmetic can distract from the question the exercise is meant to expose.

Then comes the deceptively difficult empty cell. An absent quantity could mean nobody measured it, the measurement was unreadable, or the record was left unfinished for teaching purposes. None of those meanings is equivalent to zero. In this exercise, zero would represent an expressly entered quantity of nothing under the sample's definition. Missing would represent a value the exercise does not supply. Those are different statements even when a spreadsheet makes both look unremarkable.

I would therefore define an allowed way to express missing information. The dictionary could pair an empty quantity with a separate explanation such as “not supplied in this example.” The exact arrangement matters less than consistency and readability. A participant should be able to say what is absent without inventing the absent value. I would also explain whether a note is optional or whether its absence leaves the example incomplete.

Dates create another useful discussion. Does the date describe the observation, the entry or the preparation of the sample? A heading such as “date” conceals those alternatives. Calling it “observation date” and defining it in one sentence gives the reader a better starting point. This does not require an elaborate document. It requires a writer willing to replace familiar shorthand with a specific meaning.

My next step would be a reading exercise. I would ask someone who did not write the dictionary to describe two sample rows in ordinary sentences. If that person cannot distinguish a zero quantity from a missing quantity, the definitions need more work. If they can read the rows but disagree about what was measured, the unit or field boundary needs attention. I would treat those responses as evidence about the explanation, rather than a judgement of the reader.

A dictionary can also become too ambitious. Filling it with every conceivable field would make the exercise harder to use. I would keep the first version small enough to discuss and retain only definitions that support the sample. The wider tokenization conversation often moves quickly towards scale. For this proposed TriParty Tokenisation exercise, I would judge progress by a quieter result: two readers assigning the same meaning to the same invented entry, and recognising when the entry does not tell them enough.