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Browse files- README.md +20 -18
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README.md
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Various global frameworks govern how companies practice accounting - the most important of which are IFRS and GAAP. These standard-setters do not (themselves) proscribe the mandate to use their methods. But their application is mandated by governments and multilaterals (who may wish to use them to standardise accounting practices within a geopolitical blog, for instance).
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In essence, impact accounting attempts to shift the viewpoint through which companies are valued from the self-serving one (how much money did we make or lose) to a 'global' one (how much money did we make or lose - offset by the proxied total cost of our net impacts to society and planet).
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 released the **Global Value Factors Database (GVFD)**. This pioneering dataset provides a framework for converting non-traditional impacts into financial terms, offering a new lens for evaluating global value creation. For the full scope, methodology, and theoretical underpinnings, I encourage readers to consult the official IFVI website and accompanying documentation.
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The dataset continues to be governed by IFVI’s terms of use, as set out in the original publication (available at [ifvi.org](https://ifvi.org)). My work here is based on the **first release** of the GVFD. Should IFVI publish subsequent versions, they supersede the dataset refactored in this project.
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The original GVFD was released as a single `.xlsm` (macro-enabled Excel) file.
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My primary aim was to reformat the GVFD for **machine readability** and **workflow compatibility**, especially in contexts requiring:
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3. Creation of **structured JSON files**, reflecting the data’s original hierarchical presentation.
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4. Production of **compact Parquet versions**, auto-generated via Hugging Face for efficient querying and storage.
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## Data Edits (Non-Substantive)
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No substantive changes were made to IFVI’s data values or methodologies. However, I applied several light-touch edits to improve usability and consistency:
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###
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* Country names as listed in the original dataset were mapped to **ISO Alpha-2 codes**.
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* Both the **original names** and their **ISO equivalents** are retained in the refactored dataset.
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* Non-sovereign entities (e.g., certain territories, U.S. states) without ISO codes were omitted.
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###
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* The GVFD values are denominated in **U.S. dollars**.
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* To preserve numeric integrity, I removed dollar signs (`$`) from all values.
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* Currency denomination is now recorded in the dataset’s **metadata and documentation** rather than embedded in each cell.
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* **JSON representations** preserve the original units and structure of the GVFD.
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* **Country-level JSONs** were generated to allow users to focus on all value factors within a single nation.
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## Dataset Access Links
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| Category | Description | Link |
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|----------|-------------|------|
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| **Root Directories** | | |
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| Per Country | JSON data organized by country | [View](https://huggingface.co/datasets/danielrosehill/IFVI-Global-Value-Factors-Dataset-V2/tree/main/refactored/json/per-country) |
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| US States | JSON data for US states specifically | [View](https://huggingface.co/datasets/danielrosehill/IFVI-Global-Value-Factors-Dataset-V2/tree/main/refactored/json/per-country/us-states) |
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The GVFD represents a milestone in the effort to measure and assign value to non-traditional impacts. My **Data Analysis Refactoring V2** initiative is intended to extend the usability of IFVI’s work by making the dataset friendlier for modern analysis pipelines.
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I am grateful to IFVI for granting permission to republish the data in this restructured form. Any inaccuracies or errors in the refactoring are solely my own.
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---
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Various global frameworks govern how companies practice accounting - the most important of which are IFRS and GAAP. These standard-setters do not (themselves) proscribe the mandate to use their methods. But their application is mandated by governments and multilaterals (who may wish to use them to standardise accounting practices within a geopolitical blog, for instance).
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In essence, impact accounting attempts to shift the viewpoint through which companies are valued from the self-serving one (how much money did we make or lose) to a 'global' one (how much money did we make or lose - offset by the proxied total cost of our net impacts to society and planet).
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---
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For impact accounting to evolve into a viable practice that could eventually succeed traditional accounting, it must be standardized on multiple levels. Standardization is needed both in its application and in the precise mathematical methods used to translate companies’ environmental and social impacts into monetary values. This translation allows such impacts to be compared directly—on a like-for-like basis—with established financial reporting standards. In effect, the process involves converting raw data about impacts into monetary terms.
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---
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In late 2024, the International Foundation for Valuing Impacts (IFVI) released the **Global Value Factors Database (GVFD)**. This pioneering dataset provides a framework for converting non-traditional impacts into financial terms, offering a new lens for evaluating global value creation. For the full scope, methodology, and theoretical underpinnings, I encourage readers to consult the official IFVI website and accompanying documentation.
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The dataset continues to be governed by IFVI’s terms of use, as set out in the original publication (available at [ifvi.org](https://ifvi.org)). My work here is based on the **first release** of the GVFD. Should IFVI publish subsequent versions, they supersede the dataset refactored in this project.
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No substantive changes were made to IFVI’s data values or methodologies. However, I applied several light-touch edits to improve usability and consistency:
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### XLSM -> CSV, JSON
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The original GVFD was released as a single `.xlsm` (macro-enabled Excel) file.
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My primary aim was to reformat the GVFD for **machine readability** and **workflow compatibility**, especially in contexts requiring:
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3. Creation of **structured JSON files**, reflecting the data’s original hierarchical presentation.
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4. Production of **compact Parquet versions**, auto-generated via Hugging Face for efficient querying and storage.
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### ISO Alpha-2 Mapping For Geographic Entities
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* Country names as listed in the original dataset were mapped to **ISO Alpha-2 codes**.
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* Both the **original names** and their **ISO equivalents** are retained in the refactored dataset.
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* Non-sovereign entities (e.g., certain territories, U.S. states) without ISO codes were omitted.
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### Currency Symbol Redaction
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* The GVFD values are denominated in **U.S. dollars**.
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* To preserve numeric integrity, I removed dollar signs (`$`) from all values.
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* Currency denomination is now recorded in the dataset’s **metadata and documentation** rather than embedded in each cell.
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Note: some of the value factors are six decimal places. If ingesting this dataset into databases it is recommended to choose an appropriate decimal type.
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Structure and Accessibility
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* **JSON representations** preserve the original units and structure of the GVFD.
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* **Country-level JSONs** were generated to allow users to focus on all value factors within a single nation.
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## Dataset Access Links
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These links are to the roots of the refactored dataset on Hugging Face and are provided for ease of navigation and access:
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| Category | Description | Link |
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|----------|-------------|------|
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| **Root Directories** | | |
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| Per Country | JSON data organized by country | [View](https://huggingface.co/datasets/danielrosehill/IFVI-Global-Value-Factors-Dataset-V2/tree/main/refactored/json/per-country) |
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| US States | JSON data for US states specifically | [View](https://huggingface.co/datasets/danielrosehill/IFVI-Global-Value-Factors-Dataset-V2/tree/main/refactored/json/per-country/us-states) |
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## Thanks, Credits
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The GVFD represents a milestone in the effort to measure and assign value to non-traditional impacts. My **Data Analysis Refactoring V2** initiative is intended to extend the usability of IFVI’s work by making the dataset friendlier for modern analysis pipelines.
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I am grateful to IFVI for granting permission to republish the data in this restructured form. Any inaccuracies or errors in the refactoring are solely my own.
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