The Global Indexer is a pivotal tool within the Guardian ecosystem on the Hedera Network, designed to optimize data search, retrieval, and management. It offers advanced search capabilities across all Guardian data, including policies and documents, while improving data storage and indexing for efficient analytical queries and duplicate checks. With access to a comprehensive dataset from all Guardian instances, the Indexer ensures thorough data retrieval. Its user-friendly interface simplifies navigation, and its integration with Hedera and IPFS enhances the handling of large datasets and complex queries, making it an essential component for efficient data management.

Before we begin, lets figure out what type of user you are:

Existing MGS Account Users Start Here

New Users Without an MGS Account Start Here

Overview

With regard to ecological markets, business leaders will find themselves in these four phases:

• Creating Verified Supply

• Establishing Demand

• Buying & Selling

• Offsetting

There are many rationales that can be applied here such as Greenhouse Gas Emission Profiles, Renewable Energy Credits, and Carbon Offsets. While emission allowances are subject to government regulation, a Carbon Offset, for example, is an intangible asset that is created in a process involving a project or program whose activity can be claimed to reduce or remove carbon as a result, that is independently verified and turned into a carbon offset. These offsets are minted, or issued, by an environmental registry that created the standard methodology or protocol used to create the verified carbon offset claim. The offset then represents the original owner’s property right claim to the carbon-related benefits. The asset owner(s) can then sell their credits directly to buyers, or at wholesale. The ultimate end-user has the right to claim the benefits and can retire the offset permanently – usually as part of a netting process, where the claimed CO2 benefits are subtracted from that end-users other Greenhouse Gas (GHG) emissions.

The process to create renewable energy or carbon offset claims that can be validated and verified to be turned into a product is called measurement, reporting, and verification (MRV) data. Today, this process of collecting the supporting data for these carbon offsets is heavily manual and prone to errors. The main factors driving these error-prone are:

• Poor data quality

• Lack of assurance

• Potential double counting

• Greenwashing

This is where the Guardian solution which leverages a Policy Workflow Engine (PWE), is a sensible approach to ameliorate the issue with the current processes. The dynamic PWE can mirror the standards and business requirements of regulatory bodies. In particular, the Guardian solution offers carbon markets the ability to operate in a fully auditable ecosystem by including:

• W3C Decentralized Identifiers (DIDs): Decentralized Identifiers (DIDs) are a new type of globally unique identifier that are designed to enable individuals and organizations to generate their own identifiers using systems they trust.

• W3C Verifiable Credentials (VCs): A digital document that consists of information related to identifying a subject, information related to the issuing authority, information related to the type of credential, information related to specific attributes of the subject, and evidence related to how the credential was derived.

• W3C Verifiable Presentations (VPs): A collection of one or more VCs.

Watch this quick 2-minute video to learn about Schemas:

The Managed Guardian Service (MGS) Custom GPT is a specialized AI assistant designed to facilitate users in understanding and utilizing the Managed Guardian Service platform. This tool represents an advanced version of ChatGPT, customized specifically to cater to the needs of users engaging with MGS. It has been meticulously programmed with a comprehensive range of MGS-related documentation, policies, and operational guidelines.

You can find it here: https://chat.openai.com/g/g-dTwGOkcw7-managed-guardian-service-assistant

You can also find it in the Chat GPT Store

The primary function of the MGS Custom GPT is to act as an interactive knowledge base. It helps users navigate the complexities of the MGS platform, which is pivotal for businesses involved in emissions reporting, carbon offset, and renewable energy credit creation. This AI assistant stands out due to its ability to quickly process and provide insights from a vast array of MGS documentation, which has been integrated into its system.

Key Features of MGS Custom GPT

1. Customized Assistance: Tailored specifically for the Managed Guardian Service, it provides focused and relevant information, making it a reliable source for MGS-related queries.

2. Rich Knowledge Base: Equipped with extensive data from MGS documentation, it can answer a wide range of questions, from basic setup to complex operational procedures.

3. Efficient Query Resolution: Designed to interpret and respond to user queries by referencing the integrated MGS documentation, ensuring accurate and up-to-date information.

How to Use MGS Custom GPT:

1. Ask Specific Questions: Users can inquire about specific aspects of MGS, such as setting up user profiles, managing tenants, or understanding policy implementations.

2. Seek Clarifications: If there are aspects of the MGS documentation or operations that are unclear, the tool can provide detailed explanations.

3. Explore Features: Users can explore different functionalities and features of the MGS platform through interactive questioning.

The Managed Guardian Service Custom GPT serves as an invaluable asset for users, significantly enhancing their ability to effectively utilize the MGS platform. By providing instant access to a wealth of information and guidance, it empowers users to make the most out of the MGS services and capabilities.

Watch this quick video to learn about the Managed Guardian Service Vault

New Features

Seamless Email-Based Login & Tenant Selection

Logging in to MGS is now smoother than ever! We've removed the friction of manually entering Tenant IDs. Instead, users can now log in using just their email and password, with a tenant selection screen for those associated with multiple tenants. This streamlined approach eliminates confusion, improves accessibility, and enhances the overall user experience.

A set of regulations or instructions that specify how carbon offset projects are created, validated, confirmed, and tracked are referred to as policies in the Guardian. These regulations aid in ensuring that carbon offsets are legitimate, quantifiable, and capable of reducing or eliminating actual emissions.

The Guardian platform offers a framework for developing and overseeing carbon offset projects in accordance with a number of widely accepted international norms, such as the Verified Carbon Standard (VCS) or the Gold Standard. For various carbon offset project types, such as renewable energy, energy efficiency, forestry, or agriculture, these standards provide specific requirements.

The Guardian platform's policies are made to be flexible and adaptable to the particular requirements and objectives of each carbon offset project. They cover a variety of options and conditions, such as project parameters, baseline emissions, additionality standards, monitoring techniques, and reporting needs.

Project developers can make sure that their carbon offset projects adhere to the highest standards of reliability and quality by establishing policies within the Guardian platform. Involved parties, investors, and buyers of carbon offsets who want to make sure that their investments contribute to actual and significant emissions reductions or removals can also receive transparency and accountability from them.

Watch the videos in this youtube playlist to learn how to breakdown methodologies and create policies for the Guardian:

New

• Core Guardian Upgrade to v2.21

Watch this quick video to learn about Dry Run:

Watch this quick video to learn about Retirement Contracts

Managed Guardian Service (MGS) builds on the core capabilities of the , incorporating powerful cloud-driven enhancements to streamline and elevate your carbon market and environmental data management experience. Here’s a look at the key features that make MGS the ideal solution:

Use the UI or APIs to create your own digital methodologies

Policies are one of the most important concepts to understand in the Guardian. We recommend that you take a moment and watch the video about Policies in the "." The Policy Workflow Engine defines and validates all requirements for methodologies. We give you the option to create them using the UI and also APIs. Make sure to read our

New Features & Enhancements

Trustchain Stability Fix Resolved an issue where accessing the Trustchain triggered a 422 error if the associated policy lacked a mint block. This fix ensures Trustchain visibility remains consistent and error-free regardless of policy configurations.

Improved Multi-Account Login Experience Users with multiple accounts tied to the same email can now easily select which account to log into during authentication. This streamlined selection process enhances usability across tenants and roles.

Token Minting Performance Optimization Addressed major performance bottlenecks during token minting—especially for high-load policies like. This update significantly improves loading speed and prevents UI freezing during heavy operations.

New Features & Enhancements

Infrastructure Resilience & Uptime Enhancements MGS Beta v11 introduces major upgrades to our core infrastructure — built to support seamless, zero-downtime deployments. This behind-the-scenes improvement ensures that updates, hotfixes, and feature rollouts happen without interrupting your operations. Whether you're streaming MRV data, minting tokens, or managing live policies, your work stays uninterrupted. These enhancements reinforce one of MGS’s core promises: maximum uptime, continuous performance, and uninterrupted trust.

Azure B2C Single Sign-On Integration For enterprise teams building custom front ends, MGS now supports Azure Active Directory B2C (SSO) integration. Organizations can authenticate users through their own identity systems while seamlessly accessing MGS — no separate login required.

Overview

With the recent shift in the Managed Guardian Service (MGS) infrastructure, incorporating web3.storage as a critical component for data storage and management is essential. This guide provides an introduction to web3.storage, outlining its significance, operational mechanics, and the steps required for Tenant Admins to integrate it with their MGS tenants.

Complete guide to deploying, monitoring, and maintaining carbon certification policies in production environments

Chapter 16 covered advanced policy patterns and testing. Chapter 17 focuses on the critical final phase: deploying policies to production, managing live carbon credit certification systems, handling upgrades, and ensuring ongoing operational excellence.

This chapter addresses the real-world challenges of running production carbon registries with financial and environmental stakeholders depending on reliable, accurate policy execution.

Production Deployment Architecture

Watch this quick 2-minute video to learn about policies:

New

• Hedera Network selection: Mainnet (new), Testnet, Previewnet

• Core open-source Guardian Upgrade v2.8 to v2.11

Tenant Configuration

Now, with a Secret Access Token generated, you can proceed with configuring a new or existing tenant in MGS. If you wish to create a new tenant, log in as Tenant Admin, select the ‘Tenants’ menu option, and click ‘+ Add New Tenant’. In the modal window, enter the Tenant Name, choose the appropriate Network from the list, and select ‘filebase’ among the IPFS Storage Provider options. In the ‘filebase token’ field, enter the Secret Access Token you copied earlier. Click the ‘Create Tenant’ button to finalize the creation of this tenant.

If you need to change the IPFS Storage Provider for an existing tenant, select the ‘Tenants’ menu item, find the tenant, and click the ‘Open’ button. Then, go to the Settings tab, select ‘filebase’ from the IPFS Storage Provider list, and paste the Secret Access Token you copied earlier into the filebase token field. Click the Save Changes button at the bottom of the page to apply your changes.

New

• New Hedera Testnet reconfiguration after testnet reset

• Web3.storage Validation

Overview

In response to the evolving needs of our Managed Guardian Service (MGS) infrastructure, we are thrilled to introduce the Managed IPFS node as a pivotal addition to our suite of data storage solutions. This section is dedicated to providing a comprehensive understanding of the Managed IPFS node, highlighting its importance, operational dynamics, and integration process for Tenant Admins within the MGS ecosystem.

What is a Managed IPFS Node?

The Managed IPFS node is a fully managed and hosted service provided by MGS, designed to streamline the storage and management of data on the decentralized web. Leveraging the power of the InterPlanetary File System (IPFS), our Managed IPFS node offers a seamless and scalable approach to handling vast amounts of data with enhanced security, redundancy, and ease of access.

Overview

In response to evolving data management needs within the Managed Guardian Service (MGS) infrastructure, integrating filebase as a key IPFS provider has become imperative. This documentation serves as a comprehensive guide to incorporating Filebase, emphasizing its importance, functionality, and the step-by-step process required for Tenant Admins to seamlessly integrate it with their MGS setup.

What is filebase?

filebase is a pioneering platform that leverages the InterPlanetary File System (IPFS) to offer scalable and decentralized data storage solutions. By harnessing the power of IPFS and blockchain technology, Filebase provides users with a secure, efficient, and cost-effective method for storing data across a distributed network. This platform is exceptionally well-suited for applications demanding high data integrity, availability, and redundancy — characteristics that align with the core objectives of the MGS ecosystem.

The integration of filebase with MGS not only enhances the platform's data storage capabilities but also aligns with the overarching goal of leveraging decentralized technologies for improved security and efficiency. This guide will navigate through the necessary steps to integrate filebase with MGS, ensuring a smooth transition for Tenant Admins aiming to optimize their data management strategies within the MGS framework.

New Features

Database Vault Restriction for Mainnet API Access To ensure data security on the Mainnet, API access to the Hashicorp vault is now restricted, aligning API functionality with UI standards. This measure prevents unauthorized use of the vault, providing an added layer of protection for mainnet operations.

Enhanced Tenant ID Accessibility Tenant ID visibility has been streamlined for improved user experience. Previously accessible only by email or Admin login, the Tenant ID is now displayed directly within the tenant dashboard, making it easier for users to locate this essential information.

User Role Selection on Invite To improve the invitation flow, Tenant Admins can now select user roles (Standard Registry or User) when inviting new users. This update allows for better management of permissions and access levels, streamlining the onboarding process. Invitations are tailored to reflect the specific user role, enhancing clarity and usability.

Indexer Enhancements

Login Access for Indexer Interface We've added a dedicated Login/Signup button to the Indexer UI page, allowing users to directly access the login page without redirecting through the main MGS portal. This update simplifies access to Indexer functionality, making navigation smoother and more intuitive.

Global Search Integration with Indexer The Indexer is now integrated with Global Search, enabling users to search policies across the entire Hedera Testnet and Mainnet from within MGS. This enhancement improves search capabilities, providing faster, more comprehensive access to policies across instances and standard registries.

Customizable Indexer Hosting In this release, we’ve added options for hosting and customizing the Indexer. Organizations can now configure the Indexer to suit specific search and data access needs, making MGS even more flexible and adaptable to unique use cases.

Updates

MGS Upgrade to Open-Source Guardian 3.0 In alignment with the latest open-source Guardian version 3.0, MGS Beta V10 includes all the latest features and improvements from the Guardian platform. This update ensures that MGS users have access to cutting-edge functionality, security enhancements, and performance optimizations.

New

Below is a list of features that are included in the initial launch of the Managed Guardian Service Beta v1

• Open-Source Guardian Version 2.7

• Introduction to Admin Users

• Multi-tenancy

• Pre-loaded Policies

  • Carbon Offsets Policies:

    • Verra Redd+ VM0007 Developed by Envision Blockchain

    • Carbon Reduction Measurement - GHG Corporate Standard Developed by TYMLEZ

• Downloadable APIs

Tenant Admins play a crucial role in integrating the Managed IPFS node with their MGS tenants. Here's a step-by-step guide to get you started:

For New Tenants

1. Click the Add New Tenant Button

2. Fill out the Tenant Name and select the appropriate Network

3. When asked for the IPFS Storage Provider click the drop down and select Managed IPFS node

For Existing Tenants

1. From the Tenant Admin screen, click the "Open" button

1. Navigate to the "Settings" tab

1. When asked for the IPFS Storage Provider click the drop down and select Managed IPFS node

1. Save Changes

New

Below is a list of improvements that are included in the Managed Guardian Service Beta v2

• Upgrade to core open-source Guardian v2.8 (Retirement process for assets, Matched Assets, 3rd Party Content Providers, Modular Benefit Projects, and LedgerWorks Eco Explorer Implementation)

• Adding 2 DOVU CRU methodologies to the preloaded policies (Agrecalc and Cool Farm)

• Extend the POST/tenants/invite endpoint with the ability to return the inviteId in response

• Updated Swagger Documentation for Beta V2

• Enable Admins to manage users

• Improved Internal Alerts

• Enhanced Autoscaling for performance loading

• Bug fixes

New

Email Alert on Successful Publishing of Policies

To improve communication and ensure that users are promptly informed, we have added an email notification feature. Whenever there is a successful publishing of any methodology on Testnet/Mainnet, an email alert with detailed information will be sent to the user.

Further Evolution of Policy Comparison (Mass Diff)

We have extended our policy comparison functionality to allow for mass-comparison of policies across the entire ecosystem. Users can now search for local policies similar or different to a given policy based on a similarity threshold, without needing to import them into the Guardian instance. This feature enhances the efficiency and breadth of policy analysis.

Updates

UI Improvements

We have made several enhancements to the user interface, including updates to dialog boxes, notification bars, and login screens. These improvements aim to provide a more cohesive and user-friendly experience.

Obsolete Banner Display

The obsolete banner, which should appear at the top of the page when launching MGS, is now functioning correctly and will be displayed as intended.

Policies with Tools in Dry Run Mode: Performance Improvement

The performance of executing policies with tools referenced in dry run mode has been significantly improved. Users will now experience faster execution speeds when importing and running these policies.

To ensure seamless integration and compatibility with a wide range of data storage needs within the Managed Guardian Service (MGS) framework, we have expanded our list of supported IPFS (InterPlanetary File System) storage providers. Each provider brings unique features and benefits tailored to different requirements, offering flexibility and choice to our users. Whether you are looking for enhanced security, specific geographic data residency, cost-efficiency, or scalability, our diverse range of compatible IPFS storage providers ensures that your data storage needs are met with the highest standards. Below is a list of IPFS storage providers that are fully compatible with MGS, designed to enhance your experience and optimize your data management strategy within the MGS ecosystem.

MGS Managed IPFS Node

New

• Guardian Core patches

  • Fixing an issue that the TokenId created are published with UUID formatting instead of a tokenId property.

  • Improvement of how the Policy Service handles large policies.

Return Tenants.

POST /tenants

Return Tenants. For Admin role only.

{
content:
            application/json:
              schema:
                type: object
                properties:
                  totalCount:
                    type: number
                  tenants:
                    $ref

{
    // Response
}

New

1. Filebase Support Added

In our continuous effort to expand and improve the IPFS solutions available in MGS, we have now added Filebase as an additional option. This integration allows users to choose Filebase for their IPFS needs, alongside the existing options. With Filebase support, users can leverage its unique features and benefits as part of their workflow in MGS.

Understanding the importance of effective communication, especially during downtimes, we have introduced a new notification system for all users. This feature is designed to inform users about any planned or unexpected downtime promptly. Here's what makes the downtime notification system stand out:

• Location and Visibility: The notification is prominently displayed at the top of the screen when enabled, ensuring maximum visibility.

• Interactivity: Users can dismiss the notification with a simple click of the [X] button. Once closed, it will not reappear until a new message is issued.

3. Enhanced Final User Profile Setup Wizard Descriptions

To make the setup process as smooth and understandable as possible, we have added helpful descriptions to each step of the Final Setup wizard. These descriptions are designed to provide users with clear information about what is required at each step, ensuring that both Standard Registry and Default User roles can be configured with ease and confidence.

4. Update to Guardian v2.22

Beta v6 includes Guardian version 2.22, bringing all the latest improvements and fixes from the Guardian platform into MGS.

Overview

As part of the evolving Managed Guardian Service (MGS) platform, Tenant Admins now have the flexibility and autonomy to select their own IPFS (InterPlanetary File System) storage providers. They must select and configure their preferred IPFS storage provider prior to creating a tenant.

This new feature significantly enhances the customization and control Tenant Admins have over their data storage solutions within the MGS ecosystem. This introduction aims to guide Tenant Admins through the process of selecting and integrating an IPFS storage provider with their MGS tenant.

The Role of IPFS in MGS

IPFS is a peer-to-peer network protocol that enables decentralized data storage and sharing. In the context of MGS, it serves as a backbone for storing digital environmental assets securely and efficiently. Choosing the right IPFS storage provider is crucial for optimizing data accessibility, redundancy, and overall system performance.

Importance of Selecting an IPFS Provider

1. Customized Data Storage Solutions: Tenant Admins can choose a provider that best fits their specific data storage needs and requirements.

2. Enhanced Data Sovereignty: By selecting their own provider, Tenant Admins have greater control over where and how their data is stored.

3. Scalability and Flexibility: Different providers offer varying levels of scalability and flexibility, allowing Tenant Admins to tailor their storage solutions as their needs evolve.

Steps for Tenant Admins

1. Research and Evaluate IPFS Providers: Understand the offerings, features, and pricing models of various IPFS storage providers. Key factors to consider include storage capacity, redundancy, security measures, and network performance.

2. Compatibility with MGS: Ensure that the chosen IPFS provider is compatible with the MGS platform. This compatibility is essential for seamless integration and operation within the MGS ecosystem.

3. Integration Process: Follow the specific steps provided to integrate the selected IPFS storage provider with your MGS tenant. This may involve configuring API connections, setting up access credentials, and customizing storage settings.

Conclusion

The ability to select their own IPFS storage providers empowers Tenant Admins with greater control and flexibility in managing their data storage solutions within the MGS platform. This feature aligns with the overarching goal of MGS to provide a customizable, secure, and efficient environment for managing digital environmental assets. Tenant Admins are encouraged to take advantage of this feature to optimize their MGS experience and meet their specific data storage needs.

Logging into filebase

To start using filebase as an IPFS provider in MGS, you need to first register your account. If you already have an account, you can directly go to https://console.filebase.com. If you don’t, follow these steps:

• To sign up for a filebase account, navigate to https://filebase.com. To create a new account, click the ‘Try for Free’ button in the top right corner of the webpage.

• Next, fill out the form fields, including an email address and password, and agree to the filebase terms to create your account.

• You will receive an email with confirmation instructions. Click the link included in the email to confirm your account and complete the registration process. Once finished, you can access the .

Buckets

Buckets are like file folders; they store data and associated metadata. Buckets are containers for objects. Navigate to the Buckets dashboard by clicking on the ‘Buckets’ menu option. Here you can view your existing buckets and create new ones.

If you already have the Bucket you wish to use with MGS, skip this step. To create a new bucket, click the ‘Create Bucket’ button in the top right corner of the webpage, enter the name for the new bucket, and click the ‘Create Bucket’ button.

If successful, you will be redirected to the Bucket dashboard with your newly created bucket.

Access Keys

The Access Keys menu option leads you to the access keys dashboard. Here you can view, manage, and rotate your access keys. From this menu, you can also generate a Secret Access Token to be used with MGS. To generate this token, click the dropdown menu for 'Choose Bucket to Generate Token', then select the IPFS filebase Bucket you intend to use.

Copy the generated Secret Access Token.

Tenant Admins play a crucial role in integrating Web3.Storage with their MGS tenants. Here's a step-by-step guide to get you started:

For New Tenants

1. Click the Add New Tenant Button

2. Fill out the Tenant Name and select the appropriate Network

3. When asked for the IPFS Storage Provider click the drop down and select Web3.Storage

1. Fill out the IPFS Storage API Key and IPFS Storage API Proof that you obtained from the .

For Existing Tenants

1. From the Tenant Admin screen, click the "Open" button

1. Navigate to the "Settings" tab

1. When asked for the IPFS Storage Provider click the drop down and select Web3.Storage.

2. Fill out the settings and click "Save Changes."

New

1. Fix for IPFS Resolution Issue When using the MGS hosted IPFS storage provider option; we've resolved the "IPFS not resolved" error, enhancing the stability and reliability of our IPFS integrations.

2. Enhancements in Policy Import Process Addressing performance issues, we've fixed a critical bug in the circuit traversal loop during policy comparisons, significantly reducing processing times and CPU utilization. Additional optimizations have also been made to improve memory usage.

3. MGS Vault Integration for BYOD Key To further secure and customize your experience, we've integrated MGS Vault to support Bring Your Own DID (BYOD) Key, allowing for enhanced security and personalization within the MGS framework.

4. User Interface Improvements This version rolls out several UI enhancements designed to improve interaction and usability across the MGS platform.

5. Update to Guardian v2.23 Continuing our commitment to staying current with the latest technological advances, MGS has been updated to Guardian core version 2.23, incorporating all the new features and improvements.

Beta v7 includes Guardian version 2.23, bringing all the latest improvements and fixes from the Guardian platform into MGS.

Return Tenant related settings.

GET /tenants/settings

Get Tenant related settings. For Tenant Admin role only.

{
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/TenantSettings'
}

New

• Revolutionized User Interface: Navigate with ease and enjoy a more intuitive experience.

• Custom Tenant Branding: Tailor every one of your tenant spaces with unique branding elements for a personalized touch.

• Enhanced Standard Registry Attributes: Dive into a more comprehensive and detailed asset management journey.

• MGS Vault Additions: Secure your data with integration options including Azure Key Vault and GCP Secret Manager. Learn more about MGS Vault configurations .

• Core Guardian Upgrade to v2.20: Experience the pinnacle of our foundational technology, ensuring efficiency and reliability.

• AI-Powered Search Capabilities: Navigate through data with unprecedented ease and intelligence.

New

Improve the UI/UX for OpenSource Policy Import Function

We have added a cleaner and more intuitive way to search for open-sourced policies directly within MGS, making it easier to find and import the policies you need.

Expose APIs for User Setup Flow

To improve integration capabilities, we've exposed public APIs for user creation functionalities (e.g., Standard Registry and Policy Users). This allows customers to seamlessly integrate MGS into their existing systems, managing user setup processes including IPFS storage providers and vault selections through their own interfaces.

Policy Lifecycle Management

Addressing performance inefficiencies, we've optimized the policy service to handle policy states more effectively. By managing obsolete policies post-Hedera testnet reset, we've reduced unnecessary load and SaaS infrastructure costs. Users can now better manage their policy data, minimizing potential data loss and improving overall satisfaction.

Updates

Update MGS to Guardian v2.24

In our commitment to staying current with technological advances, MGS has been updated to open-source Guardian version 2.24. This update brings all the latest features and improvements from the Guardian platform into MGS.

Beta V8 includes Guardian version 2.24, incorporating the latest improvements and fixes from the Guardian platform to enhance the overall functionality and reliability of MGS.

Send Invite link.

POST /tenants/invite

Send an Invite link for a new user. For Tenant Admin role only.

Request Body

Establishing the foundational knowledge for methodology digitization on Guardian platform

Overview

Part I provides the essential foundation for understanding methodology digitization, the Guardian platform, and the VM0033 reference methodology. This part consists of three focused chapters designed to prepare readers for the technical implementation phases that follow.

Status: ✅ Complete and Available Implementation Focus: VM0033 emission reduction calculations, Guardian Tools architecture, and comprehensive testing frameworks

This part covers the implementation of calculation logic in Guardian environmental methodologies, with VM0033 as the primary example and AR Tool 14 demonstrating Guardian's Tools architecture.

Part Overview

Part V provides comprehensive guidance on implementing and testing calculation logic for environmental methodologies in Guardian:

New

• Tenant Logs

Overview Two-factor authentication (2FA) adds an extra layer of security to your MGS account. Once enabled, signing in will require your password and a one-time code from your mobile device. This applies to all user types, including Tenant Admins, Standard Registry and Policy User accounts.

Access Your Profile

• Log into your MGS account.

• Click your user name at the bottom left of the sidebar.

Delete Tenant User

DELETE /tenants/{tenantId}/users/{userId}

Delete Tenant User

Return user Tenants only.

GET /tenants/user

Return user Tenants. For Tenant Admin role only.

Return Tenant Users

POST /tenants/{tenantId}/users

Return users for Tenant. For Tenant Admin role only.

Create new Tenant.

PUT /tenants/user

Create new Tenant. For Tenant Admin role only.

Delete Tenant

POST /tenants/delete

Delete Tenant and all related data. This action can't be undo. For tenant admin role only.

Common templates, frameworks, and systems used across all parts of the Methodology Digitization Handbook

Overview

This directory contains shared infrastructure used across all parts (I-VIII) of the Methodology Digitization Handbook to ensure consistency, quality, and maintainability.

Shared Components

Standard templates for consistent content structure across all chapters and parts

System for ensuring accurate VM0033 references throughout all handbook content

System for linking handbook content with existing Guardian documentation

Comprehensive collection of test artifacts, Guardian implementations, calculation tools, and validation materials including:

• VM0033 Reference Materials: Complete methodology documentation and Guardian policy implementation

• Test Data & Validation: Official test cases, real project data, and Guardian VC documents

• Guardian Tools & Code: Production implementations including AR Tool 14 and calculation JavaScript

• Schema Templates: Excel-first schema development templates for Guardian integration

Usage Guidelines

For Content Developers

1. Use Standard Templates: All chapters must follow templates in templates/

2. Follow VM0033 Integration: Use vm0033-integration/ system for all methodology references

3. Link Guardian Docs: Follow guardian-integration/ patterns for existing documentation

For Methodology Implementers

1. Start with Artifacts: Use test artifacts and reference implementations as foundation

2. Validate Calculations: All implementations must match test artifact results exactly

3. Use Production Code: Reference er-calculations.js and AR-Tool-14.json for proven patterns

For Part Maintainers

1. Reference Shared Systems: Link to shared infrastructure rather than duplicating

2. Contribute Improvements: Enhance shared systems for all parts

3. Validate Compliance: Ensure part-specific content follows shared standards

4. Update Artifacts: Keep artifact collection current with platform changes

Integration with Parts

Each part should reference these shared systems:

Maintenance

Shared System Updates

• Updates to shared systems benefit all parts automatically

• Version control ensures consistency across handbook

• Centralized maintenance reduces duplication

• Artifact collection updated with Guardian platform evolution

Quality Assurance

• Calculation Accuracy: All artifacts validated against methodology requirements

• Guardian Compatibility: Production code tested in Guardian environment

• Test Coverage: Comprehensive test cases covering all calculation scenarios

• Documentation Quality: All artifacts include usage instructions and integration examples

Advanced integration techniques, troubleshooting procedures, and expert-level methodology implementation patterns

Part VIII covers advanced topics for expert-level methodology implementation, including sophisticated external system integration, comprehensive troubleshooting procedures, and best practices learned from production deployments.

Overview

Building on operational deployment from Part VII, Part VIII addresses complex integration scenarios, advanced troubleshooting techniques, and optimization strategies for large-scale methodology implementations serving thousands of users.

Why Advanced Topics Matter:

• Complex integration scenarios require sophisticated architectural patterns

• Production issues demand systematic troubleshooting and resolution procedures

• Performance optimization enables scaling to enterprise-level deployments

• Best practices prevent common pitfalls and ensure long-term success

Part VIII Structure

Bidirectional data exchange between Guardian and external platforms. Covers data transformation using VM0033's dataTransformationAddon block and external data reception using MRV configuration patterns from metered energy policies.

Common problems encountered during methodology digitization and their solutions, with specific examples from VM0033 implementation. Covers debugging techniques, performance optimization, and issue resolution.

Prerequisites

From Previous Parts

• Parts I-VII: Complete methodology implementation through production deployment

• Experience with methodology operations and user management

• Understanding of production system monitoring and maintenance

Technical Requirements

• Advanced Guardian platform knowledge and API expertise

• Experience with external system integration and data transformation

• Understanding of production troubleshooting and debugging techniques

Learning Outcomes

After completing Part VIII, you will be able to:

Advanced Integration Mastery

• Implement data transformation using dataTransformationAddon blocks with JavaScript

• Configure external data reception using externalDataBlock and MRV patterns

• Handle Guardian-to-external system data export and formatting

• Set up automated monitoring data collection from external devices and systems

Expert Troubleshooting

• Diagnose and resolve complex methodology implementation issues

• Optimize performance for large-scale production deployments

• Implement comprehensive monitoring and alerting systems

• Handle edge cases and unusual integration scenarios

Best Practices Implementation

• Apply proven patterns from successful methodology deployments

• Avoid common pitfalls and implementation mistakes

• Optimize for maintainability, scalability, and performance

• Establish expert-level quality assurance and testing procedures

Implementation Timeline

Chapter 27 (External Integration): 3-4 hours

• Advanced integration pattern implementation

• Enterprise system connectivity and data transformation

Chapter 28 (Troubleshooting): 2-3 hours

• Comprehensive troubleshooting procedures and issue resolution

• Performance optimization and advanced debugging techniques

Total Part VIII Time: 5-7 hours for advanced mastery and expert-level implementation

Status

✅ Available - Part VIII chapters are complete and ready for use.

Completion: Part VIII completes the Methodology Digitization Handbook, providing comprehensive coverage from foundation concepts through expert-level implementation and troubleshooting.

Standard templates for consistent content structure across all handbook parts

Overview

These templates ensure consistent structure, formatting, and quality across all chapters in the Methodology Digitization Handbook (Parts I-VIII).

Available Templates

Standard structure for individual chapter sections with:

• GitBook formatting (hints, tabs, collapsible sections)

• VM0033 integration points

• User input requirement markers

• Guardian documentation reference patterns

Standard structure for chapter summaries with:

• Key takeaways organization

• Next chapter preparation

Template Usage Guidelines

Available Elements

Templates may or may not include these elements depending on chapter context:

• Learning Objectives: Specific, measurable outcomes

• Prerequisites: Clear requirements and dependencies

• VM0033 Context: Practical methodology examples

• Guardian Integration: Links to existing documentation

GitBook Formatting Standards

• Hint Blocks: <div data-gb-custom-block data-tag="hint" data-style='info|success|warning|danger'></div>

• Tabs: <div data-gb-custom-block data-tag="tabs"></div> and `

`

• Collapsible Sections: <details><summary>Title</summary>Content</details>

• Code Blocks: Proper syntax highlighting

• Cross-References: Consistent linking patterns

Content Quality Requirements

• Reading Time Constraints: Specific time limits per template type

• Dual Audience Focus: Content serves both Verra maintenance and newcomer learning

• Practical Focus: Emphasis on actionable guidance over theory

• Accuracy Requirements: All examples must be user-validated

Template Customization

Part-Specific Adaptations

Templates can be adapted for specific parts while maintaining core structure:

• Part-specific learning objectives

• Relevant Guardian documentation references

• Appropriate VM0033 examples for the part's focus

Chapter-Specific Modifications

Individual chapters may modify templates for specific needs:

• Additional sections for complex topics

• Specialized validation procedures

• Extended examples for difficult concepts

• Custom formatting for technical content

Quality Assurance

Template Compliance Validation

Overview Managed Guardian Service (MGS) supports Single Sign-On (SSO) through Azure B2C for organizations integrating their own front-end application with MGS. This capability is available as part of the Cortex integration pattern, allowing organizations to use their existing Azure B2C tenant for authentication. Azure B2C SSO is not available in the default MGS UI—it is supported only for integrated front ends.

Key Points

• Azure B2C SSO can be enabled for any MGS tenant, but configuration is tenant-specific (one Azure B2C connection per tenant).

• All Azure B2C application setup and management must be performed in the end user’s Azure portal before connecting to MGS.

• Only tenant admins can configure Azure B2C SSO in MGS.

Prerequisites

• An Azure B2C tenant and application registered in the organization’s Azure portal.

• The following details from Azure B2C:

  • Issuer URL

  • Application (Client) ID

Enabling Azure B2C SSO in MGS

1. Create or Select a Tenant

• Log into the MGS admin interface.

• As a tenant admin, create a new tenant or select an existing tenant from the “Tenants” list.

2. Access the Azure B2C Tab

• Click “Open” for the desired tenant.

• Navigate to the Azure B2C tab in the tenant configuration.

3. Enable Azure B2C

• Click the Enable button.

4. Enter Azure B2C Details

• Fill in the following fields using information from your Azure B2C portal:

  • Issuer URL (e.g., https://your-tenant-name.b2clogin.com/your-tenant-id/v2.0/)

  • Application (Cliet) ID (from the Azure B2C registered application)

  • JWKS URL (public key set endpoint, typically available from Azure B2C)

• Click Save Changes.

5. Confirm Configuration

• Once saved, MGS will use your Azure B2C settings for authentication to this tenant through your integrated/custom front end.

Notes

• Azure B2C setup and application registration must be completed in your own Azure portal. MGS only connects to the already-configured Azure B2C app.

• If you need to disable or update Azure B2C, use the Disable button or update the configuration fields as needed.

• Azure B2C SSO is not available on the default MGS user interface; it is supported only through integrated or custom UI implementations following the Cortex integration pattern.

Troubleshooting

• Ensure all URLs and IDs are entered correctly from your Azure B2C portal.

• For issues with SSO login, verify the Azure B2C configuration and application permissions in Azure.

• Contact your organization’s Azure administrator or MGS support for assistance.

Complete methodology validation and production deployment preparation using Guardian's testing and API frameworks

Part VI transforms your methodology implementation from working calculations into production-ready systems. Using VM0033's patterns and Guardian's testing capabilities, you'll learn to validate complete workflows, automate operations through APIs, and prepare for large-scale deployment.

Overview

Building on the calculation logic from Part V, Part VI focuses on system-level validation and operational readiness. These chapters teach you to test methodology implementations as complete systems, automate workflows through Guardian's API framework, and validate production readiness using real-world scenarios.

Why Integration and Testing Matters:

For additional information, please visit:

Methodology analysis and digitization planning using the approach developed during VM0033 digitization

Part II transforms the foundation established in Part I into practical, actionable digitization plans through analysis and planning. Building directly on your understanding of methodology digitization concepts, VM0033 domain knowledge, and Guardian platform capabilities, this section shares the workflow developed during the first VM0033 methodology digitization project.

The four chapters in Part II follow the sequence we found most effective during VM0033 digitization: methodology decomposition → equation mapping → tool integration → test artifact development. Each chapter builds incrementally toward the technical implementation phases that will come in Part III, ensuring you have the analysis and planning foundation needed for successful digitization.

The Approach We Developed

Part II follows the approach developed during VM0033 digitization work. This workflow emerged from experience working through environmental methodology requirements and represents what was learned about moving from methodology understanding to implementation readiness.

The Analysis Approach:

1. Methodology Analysis (Chapter 4): Break down methodology documents into manageable components using structured reading techniques

2. Mathematical Component Extraction (Chapter 5): Use recursive analysis to identify all equations and parameter dependencies

3. External Dependencies Integration (Chapter 6): Handle CDM tools, VCS modules, and other external calculation resources

4. Validation Framework Creation

This sequence ensures that no critical elements are missed while building toward implementation. Each step validates and builds upon previous work, reducing the risk of discovering missing requirements during technical development.

Why This Approach Works: Starting with broad understanding, then progressively narrowing focus to specific components, handling external dependencies, and finally creating validation frameworks helps manage methodology complexity while ensuring important requirements aren't missed. This natural problem-solving approach works well for methodology digitization by keeping each stage manageable while building toward implementation.

Chapter Progression and Learning Objectives

Focus: Approach to reading and analyzing methodology PDFs, identifying key components, stakeholders, and workflow requirements.

What You'll Learn: Techniques for breaking down methodologies like VM0033 into digitization-ready components. You'll learn structured reading approaches that focus on core methodology sections, parameter extraction techniques, and recursive analysis fundamentals that serve as the foundation for all subsequent work.

VM0033 Application: Step-by-step analysis of VM0033's structure, demonstrating how to identify and prioritize the most critical sections for digitization. You'll see how VM0033's complexity can be decomposed into manageable components while maintaining the integrity of the overall methodology requirements.

Focus: Mathematical component extraction using recursive analysis techniques starting from final emission reduction formulas.

What You'll Learn: The recursive approach to equation mapping that helps ensure no mathematical dependencies are missed. You'll learn parameter classification systems, dependency tree construction, and documentation techniques that create calculation frameworks ready for implementation.

VM0033 Application: Mapping of VM0033's emission reduction equations, including baseline emissions, project emissions, and leakage calculations. You'll work through actual VM0033 equations using the recursive approach, building dependency trees that capture all parameter relationships.

Focus: Approach to handling external tools and modules that methodologies reference, creating unified calculation frameworks.

What You'll Learn: Integration techniques for CDM tools, VCS modules, and other standardized calculation components. You'll learn to create cohesive calculation systems that integrate multiple external dependencies while managing versioning and compatibility requirements.

VM0033 Application: Integration of the tools implemented for VM0033, including AR-Tool14 for biomass calculations, AR-Tool05 for fossil fuel emissions, and AFLOU for risk assessment. You'll see how to create unified frameworks that incorporate external calculation resources while maintaining VM0033's specific requirements.

Focus: Creating test spreadsheets that serve as validation benchmarks for digitized methodology implementations.

What You'll Learn: How to work with Verra to develop test scenarios using real Allcot project data, covering all methodology pathways and creating input datasets. You'll learn to create test artifacts that serve as accuracy standards for digital policy validation.

VM0033 Application: Development of VM0033 test spreadsheet with multiple project scenarios covering different wetland types and restoration activities. Using the actual VM0033 test case artifact, you'll understand how test frameworks validate digitized methodologies.

Building on Part I Foundation

Part II assumes you have completed Part I and builds directly on that foundation. The concepts introduced in Part I - methodology digitization principles, VM0033 domain knowledge, and Guardian platform capabilities - form the essential context for the analysis and planning techniques introduced in Part II.

Progressive Technical Depth: While Part I focused on understanding and context, Part II introduces the technical rigor needed for implementation. However, the technical depth remains focused on analysis and planning rather than coding or configuration. You'll work with methodology content, equation structures, and test frameworks, but the implementation details come in Part III.

Practical Industry Focus: Every technique in Part II comes from real-world digitization projects. The approaches, recursive analysis methods, and integration techniques represent practices used successfully in methodology implementations like VM0033.

Part II Completion and Part III Readiness

Completing Part II ensures you have the analysis and planning foundation needed for Part III (Schema Design and Development). The approach developed through these four chapters provides the detailed understanding required for technical implementation.

What You'll Have Accomplished:

• Methodology analysis skills applicable to any environmental methodology

• Mathematical component extraction using recursive techniques

• External tool integration planning and unified framework design

• Validation framework with test artifacts serving as accuracy benchmarks

Preparation for Part III: The detailed analysis and planning work in Part II directly supports the schema design and policy workflow development covered in Part III. The parameter classifications, dependency trees, and test artifacts created in Part II become the foundation for Guardian schema development and policy implementation.

Time Investment and Learning Approach

Part II is designed for focused, practical learning with each chapter requiring 15-20 minutes of reading time. The total investment of approximately 60-80 minutes provides comprehensive analysis and planning capabilities that significantly reduce the time required for technical implementation phases.

Recommended Approach: Complete Part II chapters sequentially, as each builds on previous analysis work. The systematic progression ensures you develop comprehensive analysis capabilities while maintaining practical focus on implementation preparation.

The industry techniques introduced in Part II represent knowledge gained through real-world methodology digitization experience. Mastering these systematic approaches provides the foundation for efficient, accurate methodology implementation across any environmental standard or framework.

Chapter Navigation

After defining schemas, you need to test and validate them before deployment. This chapter provides a practical checklist to ensure your schemas work correctly and provide good user experience.

Schema Validation Checklist

1. Set Default, Suggested, and Test Values

Add values to help users and enable testing. These are helpful but not mandatory.

In Guardian Schema Editor:

• Default Value: Pre-filled value that appears when users first see the field

• Suggested Value: Recommended value shown to guide users

• Test Value: Value used for testing schema functionality

Example Values Setup:

Benefits:

• Users see helpful starting values

• Testing becomes easier with pre-filled data

• New users understand expected input formats

2. Preview and Test Schema Functionality

Use Guardian's preview feature to test your schema before deployment.

Preview Testing Process:

1. Click "Preview" in Guardian schema interface

2. Fill out form fields using test values

3. Test conditional logic by changing enum selections

4. Verify required field validation works

Test These Elements:

• All enum selections show/hide correct fields

• Required fields prevent form submission when empty

• Field types validate input correctly (numbers, dates, emails)

• Help text displays properly

3. Update Schema UUIDs in Policy Workflows

Insert your new schema UUIDs where documents are requested or listed in policy workflow blocks.

UUID Replacement Process:

1. Copy new schema UUID from JSON schema (click hamburger menu next to schema row, click on "Schema")

2. Open policy workflow configuration

3. Find blocks that use old schema references:

   • requestVcDocumentBlock

4. Verify Test Artifact Completeness

Ensure no fields are missing compared to your test artifact design from Part II.

Completeness Check:

1. Open your test artifact spreadsheet from Part II analysis

2. List all required parameters from methodology

3. Check each parameter has corresponding schema field

4. Verify calculation fields capture all intermediate results

Missing Field Checklist:

• All methodology parameters have schema fields

• Calculation intermediate results are captured

• Evidence requirements have file upload fields

• Conditional parameters appear based on method selection

5. Optimize Logical Flow and User Experience

Organize fields and sections for intuitive user experience.

UX Organization Principles:

• Logical Grouping: Group related fields together

• Progressive Disclosure: Basic information first, complex details later

• Clear Labels: Use terminology familiar to domain experts

• Helpful Ordering: Required fields before optional ones

Field Organization Checklist:

• Project information appears first

• Method selection drives appropriate conditional fields

• Calculation parameters grouped by methodology section

• Evidence fields grouped near related data fields

Example Logical Flow:

Once schemas pass this validation checklist, they're ready for integration into Guardian policy workflows. Well-tested schemas provide:

• Smooth user experience for data entry

• Accurate data types for calculations

• Proper validation to prevent errors

• Clear organization for efficient workflows

The next part of the handbook covers policy workflow design, where these validated schemas integrate with Guardian's policy engine to create complete methodology automation.

Understanding Guardian's parameter relationship framework for environmental methodologies

This chapter details the use of Formula Linked Definitions (FLDs) and how it enables users to view/cross-check human readable mathematical representations of the customLogicBlock calculations whenever they look at relevant schemas, policies or documents with data. It will also describe how to create Formula Linked Definitions by linking the relevant fields in schemas with the parameters in the mathematical equations of Methodology.

Once the FLDs are created, when the particular Verifiable Credentials (VCs)/Schemas are viewed in the published policy. The formulas will be displayed alongside the relevant fields enabling users such as VVBs and auditors to verify that the formulas are in sync with the methodology and the calculations are accurate.

Learning Objectives

Guardian's schema system is more sophisticated than simple data collection forms. When implementing VM0033, we needed to translate over 400 structured data components for wetland restoration methodology requirements into Guardian's schema architecture. This required understanding how schemas integrate with Guardian's broader platform capabilities while maintaining usability for different stakeholder types.

This chapter demonstrates schema development foundations using VM0033 implementation as a concrete example. VM0033's complexity provides practical examples of architectural patterns, design principles, and implementation approaches that apply to environmental methodology digitization more broadly.

The schema architecture establishes the foundation for translating methodology requirements from Part II analysis into working Guardian data structures. Rather than building everything at once, establishing architectural understanding first enables building schemas that handle complexity while remaining practical for real-world use.

Guardian Schema System Foundation

Guardian schemas serve multiple functions beyond data collection. They define data structures, generate user interfaces, implement validation rules, support calculation frameworks, and create audit trails through Verifiable Credentials integration.

Guardian Schema Functions:

• Data Structure Definition: Specify exactly what information gets collected and how it's organized

• User Interface Generation: Automatically create forms that stakeholders use for data input

• Validation Rule Implementation: Ensure data meets methodology requirements before acceptance

• Calculation Framework Support: Provide data structures that calculation logic operates on

VM0033 demonstrates how these functions work together. The methodology's complex calculation requirements needed schemas that could capture parameter data accurately, generate usable interfaces for Project Developers and VVBs, validate data according to VM0033 specifications, and support calculation workflows for emission reduction quantification.

JSON Schema Integration: Guardian builds on JSON Schema specifications for data structure definitions. Every parameter identified in Part II analysis translates into JSON Schema field definitions with appropriate types, validation rules, and relationships.

Verifiable Credentials Structure: Each schema generates Verifiable Credentials (VCs) that create cryptographic proof of data integrity. For VM0033, this means every project submission, monitoring report, and verification result becomes an immutable record with full audit trail capabilities.

Schema Content Classifications

Guardian organizes schema content into five distinct types, each serving different purposes in methodology digitization. VM0033 uses all five types across its schema implementation:

general-data: Basic project information, stakeholder details, geographic data, and descriptive content that doesn't require complex validation. VM0033's project description sections use general-data for project locations, implementation schedules, and stakeholder consultation results.

parameter-data: Methodology-specific parameters with equations, units, data sources, and justifications. These components implement the mathematical framework from Part II analysis. VM0033's parameter-data includes biomass density values, emission factors, and quantification approach selections.

validation-data: Calculation results, emission reduction outcomes, and verification results that require special audit trail handling. VM0033's validation-data captures final carbon stock calculations, emission reduction totals, and VVB verification decisions.

tool-integration: External tool implementations including AR Tools, VCS modules, and methodology-specific calculation frameworks. VM0033 integrates AR Tool 5 for fossil fuel emissions and AR Tool 14 for biomass calculations through tool-integration components.

guardian-schema: Complex nested schemas and advanced Guardian features requiring sophisticated configuration. VM0033's monitoring period management and multi-year calculation tracking use guardian-schema features for handling temporal data relationships.

This classification system helps organize complex methodologies like VM0033 while ensuring each component uses appropriate Guardian features and validation approaches.

Two-Part Schema Architecture

For VM0033 we implemented a two-part schema structure that separates project description from calculation implementation. This pattern worked because methodologies have foundational project information that establishes context, and calculation machinery that processes that information into emission reduction or removal results.

Project Description Foundation

The Project Description schema establishes all foundational project information while supporting multiple certification pathways. For VM0033, this meant supporting both VCS-only projects and VCS+CCB projects through conditional logic that adapts the interface based on certification selection.

Core Project Description Components:

• Project Metadata: Title, location, timeline, proponent information, and basic project characterization

• Certification Pathway Management: Conditional logic supporting VCS v4.4 requirements and optional CCB benefits documentation

• Stakeholder Information: Project developer details, VVB assignments, and community consultation documentation

• Methodology Implementation

VM0033's Project Description schema contains 3,779 rows of structured data. This demonstrates how complex environmental methodologies require extensive information capture while maintaining usability for stakeholder workflows.

Why This Foundation Approach Works: Establishing clear project context before calculations helps stakeholders understand what they're implementing and why. The foundation information also provides the context that calculation engines need to process parameters correctly.

Calculations and Parameter Engine

The Calculations section implements VM0033's computational requirements through structured parameter management and automated calculation workflows. This architecture handles the recursive calculation dependencies identified during Part II analysis.

Calculation Engine Components:

Monitoring Period Inputs: Time-series data collection framework with 47 structured fields handling annual data requirements across 100-year crediting periods. This component manages the temporal aspects of VM0033's monitoring requirements.

Annual Input Parameters: Year-specific parameter tracking with 44-50 configured fields supporting VM0033's requirement for annual updates to key variables like biomass density, emission factors, and area measurements.

Baseline Emissions Calculation: 204-field calculation engine implementing VM0033's baseline scenario quantification including soil carbon stocks, biomass calculations, and greenhouse gas emissions across all relevant carbon pools.

Project Emissions Calculation: 196-203 field calculation framework processing project scenario emissions with restoration activity impacts, modified emission factors, and project-specific boundary conditions.

Net ERR Calculation: 21-field validation engine that processes baseline and project calculations into final emission reduction results, including leakage accounting, uncertainty deductions, and buffer requirements.

This calculation architecture handles VM0033's complex dependencies where final results depend on annual calculations, which depend on monitoring data, which depend on project-specific parameters established in the Project Description foundation.

Guardian Field Mapping Patterns

Translating methodology parameters into Guardian field configurations requires patterns that preserve methodology integrity while generating usable interfaces. VM0033's implementation established consistent approaches for different types of methodology content.

Standard Parameter Field Structure

Every methodology parameter from Part II analysis translates into Guardian fields using a consistent structure that captures all necessary information for implementation and validation.

Required Parameter Fields:

• Description: Clear explanation of what the parameter represents and how it's used in methodology calculations

• Unit: Measurement units (t CO2e, hectares, percentage) matching methodology specifications exactly

• Equation: Reference to specific methodology equations where the parameter appears

• Source of data: Methodology requirements for how this parameter should be determined

For example, VM0033's BD (Biomass Density) parameter implementation:

This pattern ensures that every parameter implementation maintains full methodology traceability while providing clear guidance for data collection and validation.

Conditional Logic Implementation Patterns

VM0033's multiple calculation pathways required conditional logic that shows relevant fields based on user selections while maintaining methodology coverage.

Conditional Logic Examples from VM0033:

Certification Type Selection:

• Selecting "VCS v4.4" shows core VCS requirements

• Selecting "VCS + CCB" adds community and biodiversity benefit documentation requirements

• Each pathway maintains methodology compliance while avoiding unnecessary complexity

Quantification Approach Selection:

• "Direct method" shows field measurement data entry forms

• "Indirect method" shows estimation parameter inputs

• Each method implements VM0033's approved calculation approaches

Soil Emission Calculation Selection:

• CO2 approach selection determines which soil carbon stock calculation methods appear

• CH4 and N2O approach selections control emission factor parameter visibility

• Each combination implements VM0033's flexible calculation framework

This conditional structure ensures users see only methodology-relevant fields based on their project characteristics, reducing complexity while ensuring requirements coverage.

UX Patterns

Progressive Disclosure: Complex calculation parameters appear only after basic project information completion. This prevents overwhelming initial experiences while ensuring users understand project context before diving into technical details.

Role-Based Interface: Different stakeholder roles see appropriate field sets:

• Project Developers see data entry requirements with guidance

• VVBs see verification-focused interfaces with tabs for validation & verification reports

• Standard Registry sees approval-focused documentation with key decision points highlighted

Contextual Help: We're working on a new feature to enable field-level methodology references, calculation explanations and source justifications in Guardian schemas.

Validation Checks: Real-time validation feedback helps users understand data requirements and correct issues immediately rather than discovering problems during submission review.

Next Steps

This chapter established the architectural foundation for Guardian schema development using patterns demonstrated through VM0033's production implementation. The two-part architecture, field mapping patterns, and other techniques provide the framework for implementing granular data collection effectively.

The next chapter applies these principles to PDD schema development, demonstrating how to implement project description requirements and calculation frameworks using the patterns and techniques established here.

One of the most challenging aspects of VM0033 digitization was handling the external calculation tools that the methodology references. These aren't just simple formulas - they're complete calculation systems developed by other organizations with their own parameter requirements, validation rules, and output formats. This chapter shares our experience integrating the three tools we implemented: AR-Tool05 for fossil fuel emissions, AR-Tool14 for biomass calculations, and the AFLOU non-permanence risk tool.

The integration challenge went beyond just implementing calculations. Each tool was designed as a standalone system, but we needed to make them work seamlessly within VM0033's calculation framework while maintaining their original logic and validation requirements. The approach we developed balances faithful implementation of tool requirements with practical usability in the Guardian platform.

Understanding External Tool Dependencies

When we first analyzed VM0033, we found references to numerous CDM tools and VCS modules scattered throughout the methodology. Initially, this seemed overwhelming - how could we possibly implement all these external systems? The recursive analysis from Chapter 5 helped us understand which tools were actually needed for our mangrove restoration focus.

VM0033's Tool References: The methodology mentions over a dozen external tools, but our boundary condition analysis revealed that the Allcot ABC Mangrove project only required three:

• AR-Tool05: For calculating fossil fuel emissions from project activities

• AR-Tool14: For estimating carbon stocks in trees and shrubs

• AFLOU Non-permanence Risk Tool: For assessing project risks that might reverse carbon benefits

Why Only These Three: The Allcot project boundary decisions eliminated the need for most other tools. No fire reduction premium meant no fire-related tools. Mineral soil only meant no peat-specific calculations. Simple planting activities meant minimal fossil fuel calculations.

Tool Integration Strategy: Rather than trying to implement complete standalone versions of each tool, we focused on integrating the specific calculation procedures that VM0033 actually uses from each tool.

Tool vs. Methodology Calculations

Distinguishing Tool Logic from Methodology Logic: VM0033 uses tool calculations as components within its larger framework. For example, AR-Tool14 calculates biomass for a single tree or plot, but VM0033 scales this across multiple strata and time periods. Understanding this distinction helped us design integration that preserves tool accuracy while meeting methodology requirements.

Data Flow Management: Each tool expects inputs in specific formats and produces outputs that need to be transformed for use in VM0033 calculations. We had to map data flows carefully to ensure information passes correctly between tool calculations and methodology calculations.

AR-Tool05: Fossil Fuel Emission Calculations

AR-Tool05 handles emissions from fossil fuel use in project activities. Even though the Allcot project excludes fossil fuel emissions (mangrove planting doesn't require heavy machinery), we implemented this tool because it's commonly needed in other restoration projects.

Tool Purpose: AR-Tool05 provides standardized approaches for calculating CO₂ emissions from equipment, vehicles, and energy use during project implementation. This includes direct fuel combustion and indirect emissions from electricity consumption.

Integration Challenge: AR-Tool05 is designed as a comprehensive energy accounting system, but VM0033 only needs specific emissions calculations. We had to extract the relevant calculation procedures while maintaining the tool's validation logic.

Key Calculation Components We Implemented:

Direct Combustion Emissions: Calculate CO₂ from fuel burned in vehicles and equipment using fuel consumption data and standard emission factors.

Equipment-Specific Calculations: Different equipment types (boats, trucks, generators) have different fuel consumption patterns and emission factors that the tool accounts for systematically.

Activity-Based Scaling: The tool calculates emissions per activity (hours of operation, distance traveled, area covered) which VM0033 then scales across project implementation schedules.

AR-Tool05 Implementation Approach

Simplified Parameter Collection: Instead of implementing AR-Tool05's complete equipment catalog, we focused on the equipment types commonly used in mangrove restoration: boats for site access, small equipment for planting, and vehicles for transportation.

Validation Logic: AR-Tool05 includes validation rules for fuel consumption rates and emission factors. We preserved this validation because it catches data entry errors that could significantly affect results.

Output Integration: AR-Tool05 produces total CO₂ emissions that get added to VM0033's project emission calculations. The integration required unit conversions and time period alignment with VM0033's annual calculation cycles.

AR-Tool14: Biomass and Carbon Stock Calculations

AR-Tool14 is central to mangrove restoration because it provides the standardized allometric equations for calculating carbon storage in trees and shrubs. This tool became one of our most important integrations because it directly affects the project's carbon benefit calculations.

Tool Purpose: AR-Tool14 contains allometric equations that estimate biomass from tree measurements (diameter, height, species). These equations were developed from extensive field research and provide standardized approaches for different forest types and species groups.

Why This Tool Matters: Without AR-Tool14, every project would need to develop its own biomass equations, which is expensive and time-consuming. The tool provides scientifically validated equations that are accepted by carbon standards worldwide.

VM0033 Integration Points: VM0033 uses AR-Tool14 calculations in several places:

• Baseline biomass estimation for existing vegetation

• Project biomass growth projections over time

• Above-ground and below-ground biomass calculations

• Dead wood and litter biomass when included

AR-Tool14 Implementation Details

Species-Specific Equations: AR-Tool14 includes different allometric equations for different species groups. For mangrove restoration, we implemented equations specific to tropical wetland species that match the restoration targets in the Allcot project.

Multi-Component Calculations: The tool calculates separate estimates for above-ground biomass, below-ground biomass, dead wood, and litter. VM0033 uses these component estimates in different parts of its calculation framework.

Growth Projection Logic: AR-Tool14 provides approaches for projecting biomass growth over time using diameter increment data. This became critical for VM0033's long-term carbon benefit projections.

Parameter Requirements We Mapped:

• Tree diameter at breast height (DBH) measurements

• Tree height measurements for species without height-specific equations

• Species identification or species group classification

• Site condition factors (soil type, climate region, management intensity)

Handling AR-Tool14 Complexity

Equation Selection Logic: AR-Tool14 contains dozens of allometric equations for different species and conditions. We implemented selection logic that chooses appropriate equations based on user-provided species and site information.

Unit Management: The tool uses various units for different equations (DBH in cm, height in m, biomass in kg or tons). Our implementation handles unit conversions automatically to prevent errors.

Validation and Error Handling: AR-Tool14 includes validation rules for measurement ranges and species applicability. We preserved these validations because they prevent calculation errors from invalid input data.

AFLOU Non-Permanence Risk Assessment

The AFLOU (Agriculture, Forestry, and Other Land Use) non-permanence risk tool assesses the likelihood that carbon benefits might be reversed due to various risk factors. This tool was essential for VM0033 because it determines buffer pool contributions that affect final credit calculations.

Tool Purpose: AFLOU evaluates project risks across multiple categories (natural disasters, management failures, political instability, economic factors) and calculates a risk score that determines what percentage of credits must be held in buffer pools.

Why Risk Assessment Matters: Carbon projects can lose stored carbon through storms, fires, disease, or management changes. The AFLOU tool provides standardized risk assessment that ensures projects contribute appropriately to insurance buffer pools.

Integration with VM0033: VM0033 uses AFLOU risk scores to calculate buffer pool contributions that reduce the net credits a project can claim. Higher risk scores mean higher buffer contributions and fewer credits available for sale.

AFLOU Implementation Approach

Risk Category Assessment: AFLOU evaluates risks across multiple standardized categories. For mangrove restoration, the most relevant categories include:

• Natural disturbance risks (storms, sea level rise, disease)

• Management and financial risks (funding stability, technical capacity)

• Market and political risks (land tenure, regulatory changes)

Scoring Integration: AFLOU produces risk scores that feed into VM0033's buffer pool calculations. We implemented the scoring logic while simplifying the user interface to focus on risks most relevant to mangrove restoration.

Project-Specific Customization: The tool allows project-specific risk assessments based on local conditions. Our implementation guides users through risk evaluation while maintaining consistency with AFLOU's standardized approaches.

Creating Unified Integration Framework

Rather than implementing three separate tools, we designed a unified integration framework that manages data flows between tools and VM0033 calculations while maintaining each tool's specific requirements.

Shared Parameter Management: Many parameters are used by multiple tools. For example, tree species information affects both AR-Tool14 biomass calculations and AFLOU risk assessments. Our framework ensures parameter consistency across tool integrations.

Calculation Sequencing: Some tool calculations depend on outputs from other tools. Our framework manages calculation sequences to ensure data is available when needed while handling dependencies gracefully.

Validation Coordination: Each tool has its own validation requirements, but some validations overlap or conflict. We designed validation logic that satisfies all tool requirements while providing clear feedback to users about any issues.

Framework Benefits

Consistent User Experience: Users interact with a single interface that handles all tool integrations rather than switching between different tool interfaces.

Data Quality Assurance: The unified framework ensures data consistency across all tool calculations and catches errors that might arise from parameter mismatches between tools.

Maintenance Efficiency: Updates to tool calculations or requirements can be managed in one place rather than updating multiple separate integrations.

Practical Integration Lessons

Start with Core Functionality: Our initial approach tried to implement complete tool functionality, which was overwhelming. It worked much better to start with the specific functions VM0033 actually uses and expand from there.

Preserve Tool Validation: Each tool's validation logic exists for good reasons - usually to prevent calculation errors or inappropriate application. Preserving this validation prevented problems during implementation and ongoing use.

Plan for Tool Updates: CDM tools and VCS modules get updated periodically. We designed our integration to accommodate updates without requiring complete reimplementation.

Test with Known Results: Each tool typically includes example calculations or test cases. We used these to validate our integration implementation before connecting it to VM0033 calculations.

Document Integration Decisions: When tools provide multiple calculation options, we documented which options we implemented and why. This helped with maintenance and troubleshooting later.

Integration Testing and Validation

Tool-Level Testing: We first tested each tool integration separately using the tool's own test cases and examples to ensure calculation accuracy.

VM0033 Integration Testing: After individual tool testing, we tested the complete integration using VM0033 calculation examples to ensure data flows correctly through the full calculation chain.

Cross-Tool Consistency: We tested scenarios where multiple tools use the same input parameters to ensure consistent results and catch parameter handling errors.

Edge Case Testing: Each tool handles edge cases (unusual measurements, boundary conditions) differently. We tested these scenarios to ensure graceful handling across the integrated system.

From Tool Integration to Test Artifacts

The tool integration work creates the foundation for comprehensive test artifact development in Chapter 7. Understanding how tools connect to VM0033 calculations enables creating test scenarios that validate not just methodology calculations, but also the integration points where tools provide inputs to methodology calculations.

Test Coverage Requirements: Tool integrations add complexity that must be covered in test artifacts. Tests need to validate tool calculations individually and integration points where tools connect to methodology calculations.

Parameter Coverage: Tools introduce additional parameters that must be included in test scenarios. The parameter mapping work from tool integration directly informs test artifact parameter requirements.

Validation Testing: Tool validation logic must be tested to ensure it properly prevents calculation errors without blocking valid parameter combinations.

Tool Integration Summary and Next Steps

Key Integration Outcomes:

• External tool identification and prioritization based on project boundary conditions

• AR-Tool05 integration for fossil fuel emission calculations

• AR-Tool14 integration for biomass and carbon stock calculations

• AFLOU integration for non-permanence risk assessment

Preparation for Chapter 7: The tool integration work provides essential components for test artifact development. The parameter requirements, calculation procedures, and validation logic from tool integration become key elements in comprehensive test scenarios.

Real-World Application: While we focused on three specific tools for the Allcot mangrove project, the integration approach applies to any external calculation tools referenced by environmental methodologies. The unified framework approach scales to handle additional tools as project requirements expand.

Practical schema development using Excel-first approach and Guardian's schema management features

Part III transforms your methodology analysis from Part II into working Guardian schemas through hands-on, step-by-step implementation. Using VM0033 as a concrete example, this section teaches practical schema development from architectural foundations through testing and validation.

The five chapters follow a logical progression: Guardian schema basics → PDD schema development → monitoring schema development → advanced schema management techniques → practical testing checklist.

Schema Development Approach

Part III focuses on practical schema development using proven patterns from VM0033 implementation. Rather than theoretical concepts, each chapter provides step-by-step instructions for creating working schemas that capture methodology requirements accurately.

Development Sequence:

1. Schema Architecture Foundations (Chapter 8): Guardian schema system basics and field mapping principles

2. PDD Schema Development (Chapter 9): Approach to building comprehensive PDD schemas step-by-step

3. Monitoring Schema Development (Chapter 10): Time-series monitoring schemas with temporal data management

4. Advanced Schema Techniques (Chapter 11): API schema management, field properties, Required types, and UUIDs

This hands-on approach ensures you can build production-ready schemas while understanding Guardian's schema management capabilities.

Chapter Progression and Learning Objectives

Focus: Guardian schema system fundamentals and the two-part architecture pattern used in VM0033.

What You'll Learn: Guardian's JSON Schema integration, Verifiable Credentials structure, and the proven two-part architecture (Project Description + Calculations) that handles methodology complexity. You'll understand how to map methodology parameters to Guardian field types.

Practical Skills: Field type selection, parameter mapping, and architectural patterns that simplify complex methodologies into manageable schema structures.

Focus: Step-by-step Excel-first approach to building comprehensive PDD schemas.

What You'll Learn: Complete PDD schema development process from Excel template through Guardian import. Includes conditional logic implementation, sub-schema creation, and essential field key management for calculation code readability.

Practical Skills: Excel schema template usage, Guardian field configuration, conditional visibility logic, and proper field key naming for maintainable calculation code.

Focus: Time-series monitoring schemas that handle annual data collection and calculation updates.

What You'll Learn: Monitoring schema development with temporal data structures, quality control fields, and evidence documentation. Covers field key management specific to time-series calculations and VVB verification workflows.

Practical Skills: Annual parameter tracking, temporal data organization, monitoring-specific field key naming, and verification support structures.

Focus: API schema management, standardized properties, Required field types, and UUID management.

What You'll Learn: Schema management with API operations, the four Required field types (None/Hidden/Required/Auto Calculate), standardized property definitions from GBBC specifications, and UUID management for efficient development.

Practical Skills: API schema updates, Auto Calculate field implementation, standardized property usage, and UUID-based schema version management.

Focus: Practical validation steps using Guardian's testing features before schema deployment.

What You'll Learn: Systematic testing approach using Default Values, Suggested Values, and Test Values. Covers schema preview testing, UUID integration into policy workflows, and user experience validation.

Practical Skills: Guardian schema testing tools usage, validation rule configuration, logical field organization, and pre-deployment checklist completion.

Building on Part II Foundation

Part III directly implements the analysis work from Part II. Your methodology decomposition, parameter identification, and test artifacts become the inputs for schema development.

Implementation Translation: The parameter lists, dependency trees, and calculation frameworks from Part II translate directly into Guardian schema configurations through the techniques taught in Part III.

Test Integration: Test artifacts from Chapter 7 integrate with schema testing in Chapter 12, ensuring implementations maintain accuracy while providing good user experience.

Part III Completion

Completing Part III provides you with:

• Production-ready PDD and monitoring schemas for your methodology

• Guardian schema development skills transferable to other methodologies

• Understanding of schema testing and validation best practices

• Schema management techniques for efficient development and maintenance

Preparation for Part IV: The schemas created in Part III integrate directly with Guardian policy workflow blocks. Your data structures and validation rules become the foundation for complete methodology automation.

Time Investment

Each chapter requires approximately 15-25 minutes reading plus 30-60 minutes hands-on practice:

• Chapter 8: 20 min reading + 30 min practice (architectural understanding)

• Chapter 9: 25 min reading + 60 min practice (comprehensive PDD schema development)

• Chapter 10: 20 min reading + 45 min practice (monitoring schema development)

• Chapter 11: 25 min reading + 45 min practice (advanced techniques)

Total Investment: ~3-4 hours for complete schema development capabilities

Chapter Navigation

Building complete Guardian policies using your schemas from Part III

Part IV transforms your schemas from Part III into working Guardian policies that automate complete certification workflows. You'll learn Guardian's Policy Workflow Engine by building on VM0033's production policy, creating stakeholder workflows, and implementing token minting based on verified emission reductions/removals.

The five chapters progress logically: policy architecture understanding → workflow block configuration → VM0033 implementation deep dive → advanced patterns → testing and deployment.

Policy Development Approach

Part IV uses VM0033's complete policy implementation as your guide. You'll see how real production policies handle Project Developer submissions, VVB verification, and Standard Registry oversight through Guardian's workflow blocks.

Development Sequence:

1. Policy Architecture and Design Principles (Chapter 13): Guardian PWE fundamentals and integration with Part III schemas

2. Guardian Workflow Blocks and Configuration (Chapter 14): Step-by-step configuration of Guardian's 25+ workflow blocks

3. VM0033 Policy Implementation Deep Dive (Chapter 15): Complete analysis of VM0033's production policy patterns

4. Advanced Policy Patterns and Testing (Chapter 16): Multi-methodology support, testing strategies, and security patterns