ontologies

Ontologies, what are they good for really?

  • Posted on: 1 February 2024
  • By: warren
Ontologies have a chequered past in the business arena, although many significant benefits have been realised over the past two decades in biological and medical research. Wrapped up in the AI hype and occasionally lumped in with knowledge management projects or taxonomy projects they are often shelved curiosities whose original purpose is lost by their champions. What is an ontology? Generally speaking, it is a set of concepts, their properties and the relationships that link the concepts together.
 
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What is going wrong with the Semantic Web?

  • Posted on: 10 April 2018
  • By: warren

The US Semantic Technologies Symposium was held at Wright State University a month ago where there were great discussions with Craig Knoblock about SPARQL servers reliability1Eric Kansa about storing archeology data and Open Context, Eric Miller about the workings of the W3, mid West farmers and old bikes, Matthew Lange about tracking crops with LOD and a 'fruitful' talk with Evan Wallace about farm data storage standards. 

Thinking through these conversations, I decided to outline what I think are the troubling conclusions for our area, namely that a) Semantic Web adoption is lagging, b) we keep rehashing old problems without moving on and c) our ongoing lack of support for our own projects after which I'll suggest a few solutions.

English

Creating specialized ontologies using Wikipedia: The Muninn Experience.

  • Posted on: 25 June 2012
  • By: warren

Wiki.png

Creating specialized ontologies using Wikipedia: The Muninn Experience.
Paper Session III, Saturday June 30, 10:30-11:30
 
Abstract:
This paper reports on the experiences of the Muninn project in creating specialized ontologies for historical governmental and military organizations using the Wikipedia data set and its linked open data companion DBpedia.  The motivation for the ontologies and the extraction methods used are explained and their performances reviewed.  Overall Wikipedia is a very accurate knowledge base from which multilingual concepts can be extracted.  The caveat is that while the information is almost always present, it is not always straightforward to retrieve because of missing structures or categorization information. Hence, an iterative methodology has been found to work best in extracting information from Wikipedia.
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