Key Points


KEY POINTS


Applying the Method

A) In daily use, using the restructured value framework to gather data. Using both traditional paper & pencil methods and computational methods (data loggers and powerful algorithms) to record the data for delivery to ledgering computers.

B) Creating opportunity to create financially-useful new/old data value-spread rewards. Society-wide, the practical applications are community, charitable, P3 and private services delivering and using data from data loggers (handhelds, mobile phones, IoT devices, sensor mesh networks).

Metadata: Digital Data (email, chat, text, G-Suite, Office 365, macOS, etc.) that is gathered as users and organizations engage in activity.

Sensordata: Digital Data collected by electronic devices (RFID, sound, accelerometers, etc.) that detect the passing flow of data sources.

Data Loggers: Actively and/or passively record passing flow of data.  

C) Using this in the Income Statement to convert Labour Expense into Real Property and Expense for accounting purposes. This shocked accountants. It is not supposed to be possible.

D) Value-add is to get net compensation, where “Economic Value” = Cash or Equivalent Value (tax credits, cash, favourable tax rules, GAAP rules, etc.) for lending/leasing/providing/selling valuable data between the parties (public/private/non-profit & charitable), and to simultaneously offer tax credits for maximizing least-energy-cost to gather that data for donation. Example: Maple Syrup Farm Trade Association members might donate micro-climate data to their association (or cultivar stress markers, or pre-harvest yield data, etc) so their Association can obtain net compensation value.

E) This becomes especially valuable to help cut Greenhouse Gas (GHG) emissions, because it takes electronics to generate data. We can use DVA to profitably measure and cut the energy it takes to produce the accounting data – which measures all generated data.  Creating a world where this is a key tool to assess and cut the energy cost and emissions produced across civilization, all the way down to everyone’s smartphone, home, and vehicle.

E) This becomes especially valuable for the post-AI Future of Work = Could this create millions (billions?) of micro-service businesses? or Universal Basic Income cash flows? creating a world where data generated and traded by individuals become the basis of economic exchange?


Applications

Society & Charity aggregated data generated by volunteers
All businesses (small to corporate) donating (volunteering) data
Financing, forecasting, budgeting to generate tradeable valued
DataCompensate for maximizing energy efficiency when creating Data
Using IoT to create earning opportunities for least able populations
IoT/Future of Work purposes (example: Universal Basic Income)


Key Pages

A) Re-Thinking the Fundamental Nature of Data

    • [link] This page (executive summary)
    • [link] 2-page outline note [see “First Principles“, below]

B) Rewarding Data Volunteers using the Internet of Things

    • [link] 1-page Technical note with Sum Calculation [(w + x) – y = z]
    • [link] Jobs & Income-earning implications

C) Step-by-Step: Three Innovations [see “Notes” below]

° See Note 5

Three Steps to Calculated Net Value

    • Practical Daily Use: Record data for valuation
    • Ledger Record : Convert Labour Expense to Assets for claim
    • Obtain Tax Value: Calculate for Net Charitable Tax Credits

Three Steps in the Accounting Ledger

    • Split Labour Expense into Expense and Real Property
    • Record this as “Cost of Data Collected” line item**
    • Sum in-flowing calculations using [(w + x) – y = z]

** referencing line-item with a treatment note.

Accounting Standards Associations [link] could agreeably also:

    • encourage use of “Cost of Data Collected” on the Income Statement


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