Excerpt from Big Data Quarterly
We report on ten years of experience building enterprise ontologies for commercial clients.
A mini case study of using semantics to make application upgrades easier
We're adding Lymba's capability to use NLP to lift triples out of documents.
Announcing a quick and predictable way to implement semantics and FIBO for the Financial Industry.
We consider when it is a good idea to create a named property inverse. We examine several downsides and consider when the are likely to arise.
Some insights into what Semantic Arts is all about.
SHACL RDF Data Shapes provides a great way to both describe and constrain data in an RDF graph
No, Wi-Fi does not stand for "wireless – fireless"
A RESTful interface for Triple Stores
Links to a webinar with Dataveristy
We describe a uniform way to represent pure number units such as percent, dozen, gross and part per million such that the same computational mechanisms can be used to do units conversion for both numbers and for ordinary physical quantities.
We explore an interesting relationship between collections and queries as alternative ways to represent the same information. We consider when each approach make the most sense.
We examing the role of degeneracy as as way to handle challengeing edge cases.
The Season to be Jolly is upon us. We have a look at one great way to be jolly: laughter
We look some of the many facets of gratitude, who is thankful, for what and how was the gratitude felt or expressed?
We describe three kinds of buckets and how to represent them in gist and OWL.
We show how to use SPARQL to change instance URIs in place. This might be necessary if you change the name of a class, and the instance naming convention uses the class name in the URI.
We explain what steps need to be taken to change the URI of an owl:Class in place, and highlight some pitfalls to be aware of.
Getting decimal output from SPARQL
Let's explore writing D3 visualizations in the laziest way possible.
Most upper level ontologies are based on "abstract abstractions" that is, they are based on philosophical ideas that might be correct but are counter productive to try to convince business people and IT people what they are and what they mean.
In large companies, key knowledge assets are often unnecessarily complex, making them hard to understand, evolve and reuse.
It doesn't matter what the term is as long as you can agree on a definition