Table of Contents Introduction The new brave age of hyperlinked data Technical questions for hyperlinking data Physical Layer Logical Layer Conceptual layer By reference vs. by value Cross-References Introduction Normally IT people including architects, engineers, scientists and developers are forced to think a particular implementation of an application or a business solution in terms of the query language. Generally speaking most often it is the specific technology and infrastructure behind the scene that dictates how things should be done.
Table of Contents Introduction Information Conceptual, computational semiotics framework Push forward Cross-References Introduction In computer science there are many things we take for granted like the fundamental digital representation of anything with 1s and 0s. It’s often too easy to forget that when you have dived deep into the virtual realm of a computer the only thing you get is a mere representation of abstract concepts. This is our data and because they live in a machine and its peripherals they always have structure no matter how you interpret them.
Table of Contents Introduction Business vs Technological Factors Cross-References Introduction I was motivated to write this post from an article of Christian Kaul “Bridging the Knowledge Gap”. He is making questions about how, what is the best way to bridge the knowledge gap between data modeling experts and people from other fields ? But I think an important role that data modeling experts play is exactly that to bridge the gap between pure IT technical people like developers, database administrators, data engineers and people from other fields e.
Table of Contents Introduction Cross-References Introduction Recently, I have been reading an article for yet another query language, HypergraphQL. But do we really need another query language ? I do agree that it is always good to offer the developer a variety of choices for querying a database, especially if the new query language makes it easier or perhaps better in some sense to fetch or input data.
Important design and implementation principle arising from studying relational data model theory
Have you noticed that what ever the model and data structure in databases we cannot escape from the fundamental principle of managing data allocation space with references, i.e. pointer based logic, memory addressing ?
Both Topic Maps and RDF/OWL exhibit signs of aging. These signs do not indicate maturity levels but on the contrary they signal a re-examination of the data modeling, information representation problem
Although there has been significant progress with first and second generation AI systems in reasoning, learning and perceiving, abstraction has not been part of the game. The mechanism of abstraction can unify these other three processes
The associative data graph database model is still a heavy hitter, stacking up well against property graphs and triples/quadruples. Expect a comeback
A swift introduction to the key factors that influence the performance and unification character of graph databases
Table of Contents Introduction The Problem About Knowledge The Know-How is how you know The “I know something or someone” phrase The “I know this is true” phrase Epilogue Cross-References Introduction Perhaps there is not a better phrase to start this post than the Socratic paradox,
All I know is that I know nothing
This is typical of the great gap that exists between Eastern and Western way of thinking about fundamental concepts such as information, knowledge and wisdom.
Freebase, the best collaborative information management system ever built
The ancient Greek origin of the word information
Part 3/3 - Towards a New Data Modelling Architecture
Part 2/3 - Towards a New Data Modelling Architecture
Part 1/3 - Towards a New Data Modelling Architecture
Neurorganon Upper Level Ontology is an attempt to define the core ontology of Web 3.0 in a practical, well defined, standardized and consistent way.