• Why data management?

part 1: Thinking Globally, The meaning of data to people

part 2: Thinking Globally, The representation of data to machines

  • Simulating meaning and understanding
  • Equivalence of representation
    • Syntax and its role in data management
  • Models and meta models
  • Model transformations and mapping
    • Mapping versus deriving existence
  • Generating machine readable artifacts

part 3: Thinking Globally, Managing Data and Knowledge at scale

  • Data architecture, solution architecture and business architecture
  • The consequence of decentralization on ownership, mandates and cooperation
  • How to make a controlled vocabulary for an organization
  • How to make a knowledge graph based on ontologies for an organization
  • Planting data seeds

part 4: Acting Locally, how Teams Work within a Data Architecture

part4 : expert knowledge

  • A closer look at meta-models
  • A closer look at transformations
Papers

Acting Locally Introduction

In the universe of agile organizations and decentralized governance, those who built and maintain the individual parts of our IT landscape, have the most influence on how these parts are realized, and thus how they will interact with other parts. This is closely related to the concept of do-ocracy where those who do the work have or get the mandate make the decisions. Whether an organization explicitly adopts do-ocracy or not, more often than not it effectively it is the case: it is the best model to describe what happens or gets done.
Papers

Identity and Persistence

In this part we’ll have a closer look at the identity of the things we keep data of. One could argue that this is mostly a ‘pattern of miscommunication’ however, this one requires a little more background to understand so we treat it separately. The question about identity is about wondering about what one is thing and it being the same. This becomes relevant when dealing with aboutness and master data management: when we are wondering whether we have two records about the same thing in multiple information systems.
Papers

Two approaches to modelling meaning

In this piece I want to introduce two approaches to model meaning that are relevant to data architecture. They evolve around the Triangle of Reference that was introduced in a ‘The Meaning of Meaning’ by Ogden and Richards in 1923. In a nutshell the, the triangle relates the thoughts or concepts we have (top of the triangle) to the things in the worlds that we have thoughts about (the Referents) and the symbols we use to symbolize our thoughts (like words, pictograms, data etcetera).
Papers

What is information

Before we talk about data management, and how people and machines interact with data, it is important to take a moment to explore why we have data in the first place. And for that we need to take a step back and explore the nature of information. This will allow us to better understand the strengths and limitations of data and also put its expressiveness in context. I’d like to make an important scope not here.
Papers

Patterns of Miscommunication and Misrepresentation

In the ontological process, understanding each other is key. However, people, colleagues, misunderstanding each other is so common, so unavoidable, we accept it as part of life. In semantic discussions, however, I have noticed a couple of recurring patterns in miscommunication, that, once we are aware of them, we may be able to avoid or quickly resolve. Some of these patterns are relatively simple to recognize, overcome and correct for. Others are much harder to identify and often have far reaching consequences for how we think we see the world and the ways we collect data about it.