research and modelling, with some relevance for society
(Note: there’s some context afterwards.) Talk about “The AI”“The AI” doesn’t “go rogue” The program executes an unexpected process.“The AI” doesn’t “hallucinate” It computes probabilistically without success.“The AI” doesn’t “create” Patterns learned from exploited sources are used to generate.“The AI” isn’t “thinking…”The time-consuming task’s vendors are enticing you to wait.“The AI” has no…
TL;DR: yes, and for sure in public procurement. More generally, the temporal database developers probably will see a place for temporal conceptual modelling since there are a good number of temporal databases that need to be designed and there are SQL features for it, notably since SQL:2011 for temporal SQL [1]. Advanced conceptual modellers and Continue reading Can temporal conceptual modelling…
If it were a LinkedIn post, I suppose I’d be expected to write what I’ve learned, how it made me a better person, give advice for newbies, and how humbled I am with the continued support from the subscribers and casual readers alike. Probably,and I did so before. It’s also my soapbox, and science communication Continue reading Keet blog turns 20
We’ve been working on devising a generic system that can generate educational questions, answers, and explanatory feedback from ontologies. Not tailored to only one ontology, but feeding it any ontology and still obtain decent output, and not MCQs, but other sorts of questions, like Yes/No, true/false, short answer, and so on, for type-level questions. It Continue reading Tailored efficient…
People ask me questions from time to time that are squarely in the realm of professional ethics, probably because I’ve taught computer ethics for a good number of years, co-authored lecture notes on social issues professional practice (now called ‘society, ethics, and the profession’), and I wrote a collection of short stories that fictionalised Continue reading Should you tell the client about…
Let me start the new year with a long overdue topic to write about: low-resourced languages (LRL). If you take English as the benchmark and a calimero attitude of a ‘but they have it much easier with so many resources and that’s not fair’ for computational tasks involving NLP/HLT, then you can complain it’s not Continue reading NLP with low-resourced languages: beyond bean counting artefacts
This is a more concrete follow-up to the previous somewhat theoretical post on ontologies not being just RDF. I tried hard to think of how other people might approach the syntax issues and assumptions. When I asked someone who’s involved in developing a vocabulary represented in a Turtle document about it, it resulted in a Continue reading Just Turtle and RDF vs OWL examples: the CPEV and FIBO
Over the past few years that I’ve been peeking and dabbling outside computer science and the ivory tower of academia more than before, I noticed a disturbing trend, or perhaps even entrenched practice, of talk about “RDF ontologies” and of “ontologies really being no more than just RDF graphs”. But just because ontologies in OWL Continue reading No, an ontology isn’t ‘just RDF’
A bottom-up approach to knowledge graph development may be in part alike bottom-up ontology development from existing and legacy resources, but for sure also involves other tasks, and perhaps principally so. The major other task concerns instance data that also have to turn up in the graph. Digging into a pile of instances begets one Continue reading An initial comparison of approaches to…
The second edition of my ontology engineering textbook was published earlier this month with a non-profit publisher, College Publications, to keep the book affordable. I wouldn’t be getting rich from the number of textbooks sold anyway and affordability of access to knowledge is important for a myriad of reasons. The book is not for free: Continue reading Affordable non-profit publishing being…