Case Study: Data Governance

Why a DG Driven model is inherent throughout the Lodestone Insights platform

 Data governance coordination is not just important it is vital to gain trust and consent and, provide access to Buyers, Users and Creators to approve the quality of datasets (LSI Products), and validate the conformance of data changes with adherence to the Creators' internal policies, regulations and user preferences.

Lodestone has a federated and computational data governance model. The governance team is composed of the individual domain data product owners (Creators), the main owners of the data products (DAO teams, Mesh, and LSI), and experts in our Advisory Board.

Data Council and Key Areas of Concern/Responsibility

 The governance function aims to embed policy execution into every data product in a computational and automated fashion through acceptance in the Smart contract (check for conformity, acceptance and implementation) ie GoPES (Governance, Privacy, Ethics and Security) in the Product Buyer smart contract (GoPES, KYC, AML compliance and acceptance) This vastly improves the function of governance which eliminates one of the main barriers when discovering data, approving data, and making sure it follows the necessary policies. We operate in a consent model akin to the one below

Consent Model

As you can imagine, the autonomy of the domains can have undesirable consequences if not checked, These can include:

1. isolation of domains, structure, data taxonomy 

2. incompatibility and disconnection of one domain’s data product from others, 

3. fragmented experience when consuming multiple domains’ data. 

   
   

Our governance heavily relies on the adoption of processes and standards and their acceptance to ensure a consistent, connected, and trustworthy experience using the Lodestone Insights products.

The overall governance model embraces 

1. decentralisation and domain self-sovereignty, 

2. interoperability through global standardisation across LSI /DAO 

   
   

Standardisation allows adhering to a set of global rules, that are applied to all data products and their interfaces. This principle, of course, relies not only on architecture but on a supportive organisational structure.

Governance Model

Lodestone Insights holds a centralised catalogue and metadata overview for Data buyers across our architecture and solution. We start with a simple strategic view: That helps us to determine  the following Data quality framework and Ideals

Subsequently we were able to conduct a basic data audit (of all users and partners) the results of which all parties sign up to, and then that file is written to the blockchain as part of our automated governance structure (GoPES). 

GoPES Lite

This preliminary agreement is expanded as the work with users and third parties grows bringing into consideration Privacy Security and Ethics. This is an extensive and proprietary IP architecture and  can be shared after completion of an NDA) *

Technology overview and how GOPES fits

 In the UML Model below, we utilise API architecture as frequently as possible, maintaining strong security throughout our system. These are all GOPES validated.

Proposed High-Level Design

 We adopt a strong platform-wide security model and through the rest of the common services (e.g., Data service platform, data management, API management). Using our API-based structure (all interfaces indicated above are Restful API, so we can run using an event/messaging server less structure) provides an easy well well-governed path to using well-formed, well-governed accurate data. Below is an example of our tiered API structure that can be leveraged into a simple, well-structured and governed user-specific journey, allowing us to maximise our opportunities, and thus gain the maximum potential revenue, from each user.

Level 0 and Level 1 API schema

 Our enabled messaging between secondary Applications and Lodestone Insights Core allows a deeper synchronisation with Creators and enables further composition of business use cases and richer buyer market products.

Note Lodestone Insights is a comprehensive managed Platform that is modular in design and future-proofed in technology, business practice and data governance. 

Lodestone Insights balances data autonomy and collaboration, having Creators control their local decision-making, such as choosing the best data model for their data products.  Lodestone Insights adds federated and computational governance policies to impose a consistent experience across all data products; for example, standardising the data modelling taxonomy and vocabulary that all domains utilise. Naturally, Creators are given autonomy to build and maintain the lifecycle of their data products and can run those through our own data development engine (DAO) (with sections covering PLM, CLM and EOL.

Data Value

 Lodestone Insights’ domain-agnostic data platform empowers Users with self-serve capabilities to manage the lifecycle of data products declaratively and consistently reducing costs, management requirements and TTR The marketplace makes it feasible for Creators and teams to manage the lifecycle of their data products with autonomy and utilise the skillsets of their generalist developer to do so. The self-serve data infrastructure APIs allow data product developers to build, deploy, monitor and maintain their data products. The APIs allow data buyers to discover, learn, access, and use the data products. Applying GoPES standards across Lodestone Insights entire data infrastructure makes it possible for data products to be joined, correlated and used as a whole, while maintained independently by the Creator to provide deep rich data sets which meet buyers needs and business requirements.

Data and Business Value

 Mapping Data Vale to Business Requirements

Without ensuring data quality, no advancement in value can be created.

Data Value Creation

Mapping value and Data Process

 This allows LSI to create capture and share as much value as possible for our Creative Engine  Partners (DAO). This is calculated on a Proof of Work (POW) basis and the relative share of the value of published works. As shown in the use case above (again using API Framework)payment is in either LODE or Fiat (depending on stage payments)

For more information on the GoPES framework please reach out to, and arrange a discussion with john@aidentity.uk

Further details can be found via the link below https://drive.google.com/file/d/1RzemSUIJzpfDk5rORH4W4LHlJAcVgKP9/view?usp=drive_link