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What is IMDE?

Interoperable Modular Data Exchange (IMDE) is a framework that will enable machine-2-machine exchange data across the entire value network. Minimizing the cost for collecting, using and distributing data. IMDE can overcome a number of the challenges faced by organizations, solution providers and data processors like datapools in terms of improving simplification of data exchange while at the same time improving data quality (consistency, relevance, completeness, accuracy and timeliness). The biggest benefits are in exchanging data with both upstream and downstream business partners. The beneficiaries are machines!, so not humans. The whole framework is designed for fully autonomous communication between machines.

Why Interoperable and Modular?

Many of the initiatives in the past focussed on creating standards for specific use cases, or in specific industries. These standards often covered all six layers of data exchange:

IMDE - 6 Layer Framework for Interoperable Modular Data Exchange

L1	TX	Taxonomy	Establishes a unified communication language to ensure consistent terminology and understanding across different systems and platforms.	Link
L2	IM	Information Model	Defines the structure and relationships of data elements, providing a common blueprint for organizing and interpreting data.	n/a
L3	ID	Identifiers	Supports various standards for uniquely identifying entities such as locations, products, brands and organizations.	Link
L4	CL	Code Lists	Standardizes sets of codes used to represent specific data elements, ensuring consistency and interoperability across different datasets and platforms. Example: Unit of Measure	Link
L5	DF	Data Formats	Accommodates multiple data formatting standards in formats like JSON, XML, or spreadsheet templates, with clear declarations for each data container to facilitate seamless data exchange.	Link
L6	DX	Data Exchange	Defines the protocols and methods for securely and efficiently transferring data between systems, ensuring compatibility and effective communication across diverse platforms.	Link

The challenge in this approach is that the world is big, so there are many standards, for different territories, industries and use cases. Which has resulted in the fact that data exchange is still a technical and organizational nightmare. Example: A Food manufacturer sourcing raw materials and components from multiple suppliers and selling both A-Brand and Private Label products can be dealing with dozens of different ways to exchange origin and allergen data. While the type of data is 100% the same in all situations: Allergens information has the same data points for raw materials, production materials, semifinished goods and finished goods, and allergen data is not different for A-Brands or Private label brands. But still, from a technical standpoint, organizations need to deal with many ways to export or import allergen related data.

The solution is to move away from all-in-one standards, where all standards had the strategy to become THE standard. And where every standard covers all 6 layers: the dictionary, the information model, the message structure, the exchange technology, the identifiers and the code lists. This new approach is based on the idea of allowing modular standards with independent solutions for all 6 layers. Also supporting/allowing multiple standard per layer. For example:

• Support data exchange using either an Excel file or an XML message.
• Exchange technology: Indirect via and or more data pools or direct via a RestAPI.

The key principle is to model for multiple interoperable modular standards in any part of the framework. In this way, industries, organizations and solutions providers can choose the standard per part of the data exchange that suits best.