What drives me most is turning data into information and knowledge. My approach to information-driven analysis and design can be called "New Nordic" in the sense that I aim to exploit traditional Nordic ambitions such as superior quality, functionality, reliability and innovation; looking for new ways of communicating the structure and meaning of the business context.
A consultant by heart: I provide consulting, reviews and recommendations to data-driven projects:
Data architecture, Graph data modeling, Metadata and business vocabularies, Database technologies, not least graph models.
Online Trainer at DATAVERSITY Training Center (Graphs)
I am an active writer and speaker. I live in Copenhagen, close to the airport. My company, TF Informatik, was founded in 1995 and is registered in Denmark (DK66048950).
LinkedIn profile
Graph Query Language standardization:
Online Training at Dataversity:
Recent blog posts on Dataversity:
Handling Data Concerns in 2024 and Onwards
Generative AI and Semantic Compliance
Modeling Modern Knowledge Graphs
2023: Mitigating Data Debt by Knowing or by Guessing?
It’s All About Relations!
Say Hello to Graph Normal Form (GNF)
What Kinds of Data Languages Will We Need in the Future?
Tales of Data Modelers
Quick, Easy, and Flexible Data Model Diagrams
What’s in a Name? (aka Data Modeling What?)
Computing: A Human Activity!
2021: Three Game-Changing Data Modeling Perspectives
Generally Accepted Data Modeling Practises
Learning from Complex Data Modeling Practices
To Grok or Not to Grok Data Models: A Summer Special
The Conceptual Model Strikes Back!
The Psychology of Data Modeling
Ten 2020 Visions for Data Modelers
Data Modeling on the Other Side of the Quagmire
Knowledge Graphs and Data Modeling
Modeling Misfit Types: Why Type Inheritance Is Not a Good Fit in Data Models
The Future History of Time in Data Models
The History of Time in Data Models
Timely Concerns in Data Models
Modeling Sets of Data
The Atoms and Molecules of Data Modeling
2019: Full Scale Schema Modeling
Monetizing Information? Show Me Your Data Model
Handling Data Concerns in 2024 and Onwards
Generative AI and Semantic Compliance
Modeling Modern Knowledge Graphs
2023: Mitigating Data Debt by Knowing or by Guessing?
It’s All About Relations!
Say Hello to Graph Normal Form (GNF)
What Kinds of Data Languages Will We Need in the Future?
Tales of Data Modelers
Quick, Easy, and Flexible Data Model Diagrams
What’s in a Name? (aka Data Modeling What?)
Computing: A Human Activity!
2021: Three Game-Changing Data Modeling Perspectives
Generally Accepted Data Modeling Practises
Learning from Complex Data Modeling Practices
To Grok or Not to Grok Data Models: A Summer Special
The Conceptual Model Strikes Back!
The Psychology of Data Modeling
Ten 2020 Visions for Data Modelers
Data Modeling on the Other Side of the Quagmire
Knowledge Graphs and Data Modeling
Modeling Misfit Types: Why Type Inheritance Is Not a Good Fit in Data Models
The Future History of Time in Data Models
The History of Time in Data Models
Timely Concerns in Data Models
Modeling Sets of Data
The Atoms and Molecules of Data Modeling
2019: Full Scale Schema Modeling
Monetizing Information? Show Me Your Data Model
Next and Prior: Pointing in Data Models
The Emergence of "Metadata Science"? Using Graph Technology for Data Modeling
Design Thinking Data Models
Detecting Data Models
Whither Data Modeling Education? (The Future of Data Modeling)
How to Make Decisions About Data Modeling Relationships in Databases
How Not to Get Lost in 2018 with Knowledge Graphs: Map, Graph, Go!
Say No More: Verbal Data Models
Property Graphs: The Swiss Army Knife of Data Modeling
"Talk to me Data" - Getting Data Models Right
State of the art of Data Modeling?
Data Cataloging vs. Data Modeling: Reporting from EDW2017
Surrogate Keys: Paving the Way for Graph / NoSQL Data Models
Artificial Intelligence vs. Human Intelligence: Hey Robo Data Modeler!
Visual Normalization – Use the Power of the Dependencies
Data Models: Why not 3D?
Consulting, review and recommendations within anything data-driven:
- Business information analysis, incl. metadata and business vocabularies
- Data architecture with emphasis on graphs and knowledge graphs
- Data modeling using property graphs
- Database technologies, Neo4j
For more information about the Metadata Recycling book: Contact the author at the email indicated at the bottom of the page.
My Professional Roots
My professor at the University of Copenhagen was Peter Naur
- Co-author with Edsger Dijkstra et al on Algol-60
- The “N” in BNF
- He did not want to be called a “computer scientist”
- He preferred “Datalogy” (still in use today, in Denmark)
- In his book Computing: A Human Activity (1992), a collection of his contributions to computer science, he rejected the school of programming that views programming as a branch of mathematics
- 2005 Turing award winner
- Prof. Peter Chen (ER Modeling)
- Prof. Joseph D. Novak (Psychology of Education, applied concept mapping)
- Prof. Peter Gärdenfors (Cognitive Science, conceptual spaces and cognitive semantics)
- Ralph Kimball (dimensional modelling)
