What’s wrong with splitting data from meaning and purpose?

Are we still on the right track

What's going on: major data leaks, fighting 'the system' when your data is wrong, complex data transformations or misinterpretations between IT-systems and organisations, context loss on data or unauthorized access. 

IT development began with the need to process large volumes of data at high speed. To achieve this we introduced a separation between data stored in fast databases and logic executed in fast programs. As automation advanced organizations started exchanging data internally across different applications, e.g. linking order‑management systems with financial systems, etc. With the rise of the internet countless business applications now exchange data with one another. At the same time we copy as much available data as possible into data lakes to run our analyses. Along the way, we added separate systems to manage authorization, seperate systems to interpret the meaning of data, seperate audit mechanisms to check data usage under privacy regulations, and separate case management systems to control the steps required to get from data input to outcomes. This layering seems to grow more and more complex as functional and non‑functional demands increase. 

With Arqiver, Hans van Bommel, founder and CEO, shows a different path. One in which we can once again 'envelop' data with its meaning, its purpose, its legal constraints, its access rights, its permitted actions, and the frameworks that govern its exchange. Data provided in transactions or agreements between citizens, companies, and government was never meant to be copied endlessly across information systems without consent, context, or protection.

In a series of LinkedIn posts, Hans van Bommel explains the concept of this new approach to handling data, or better still, handling products. It contains several fundamental shifts in how we can shape data handling, business and collaboration.

My intention with this blogpost is to:

• draw attention to an overall concept that, in my opinion, is of real significance
• offer a readers guide to these LinkedIn posts
• offer a visual reference guide that presents all the topics as a coherent narrative, showing their structure and how they relate
• remind you that it's not only theory, look at Arqiver (I have no share in the company)

I wish the reader an engaging and insightful study.

Reference guide - visual map

Here is the link to the visual reference guide that will support you while reading the 8 conceptual Linkedin posts of Hans van Bommel about these new data handling concepts and architecture.

• Remember the visual reference guide is my personal interpretation
• The visual map standard is just rectangles, lines, groups, clockwise, left-right, top-down

Choose the visual format you prefer:

Readers guide - List of the Blogpost 

Chapter 1 - Arqiver concepts and framework

Talks about the Definition and the Construction of a Product, defined as the smallest lawful and semantic unit of value exchange.

Gives away the core concept, the Organization structure, Semantic proces framework and System of contextual governance (the eco-system).

Chapter 2 – The product

Talks about Building a Product Semantic & Contextual Reference Guide that allows humans and AI to act within a shared, verifiable truth.

Gives away the Semantic and contextual reference guide.

Chapter 3 – The organization

Talks about building a Prompt for AI to Create a Product (Service) and Add It to Your Enterprise Data Space.

Gives away the Organization structure and operation.

Chapter 4 – The streams

Talks about how product streams produce an objects with meaning, context, and retention defined by MDTO.

Gives away streams 'running' the product.

Chapter 5 - The  TARI² execution

Talks about a product expressed in meta-data and activity streams ruled by metadata.
Gives away the product execution 'cards', human and AI readable.

Chapter 6 - The data transformation

Talks about the transformation from technology based solutiont to meaning based solutions. 

Gives away Current digital architecture around data, Preparing for dataspaces, Digital architecture around meaning and purpose, Federation by design and Data discipline evolution.  

Chapter 7 - The collaboration transformation

Talks about comparing the fundamentally different (and in the end complementary) worldviews on data spaces.

Gives away Federated collaboration and data analysis end Arqiver collaboration concept.

Chapter 8 - The case transformation

Talks about case management in a data-centric federated eco-system and how a product (service) context acts as an AI knowledge for case management execution.

Gives away Product context and execution, and Product context and AI for case management

Appendix A - The internals

Talks about Arqivers Data spaces technology to reach its goal 'Trust for Everyone Unlimited Provisioning Scalable, Distributed Federation by Design'.

Appendix B - Europe's path

Talks about why Europe must learn to reach its digital ambitions by evolution not by total structured control. Strength comes from continual adaption, like nature teaches us.

Ending

I hope you enjoyed studying these concepts and architecture. Once you see this new perspective it's hard to unsee it in the every day problems that Business and IT experience in handling data.

Remember that If you are already working on e.g. your semantics, the meaning of your data and meta-data handling, then you're already on the way to this new 'product' concept.