2016 and continuing posts on ontologies

Well, 2015 seems to have gotten away from me. Over the last year, I have been working to design and implement several ontologies for policy-based management. The work is based on Complexible's Stardog graph database, with services accessed through a RESTful API, and with a front-end, single-page web application created with Bootstrap and Backbone. It has been a blast working with and learning all these technologies, and my new year's resolution is to get back into writing my blog and share some of my learnings.

Another thing that I am doing is related to the International Association for Ontology and Its Applications (IAOA). More specifically, I am a part of the Semantic Web Applied Ontologies Special Interest Group (SWAO SIG). The SIG is continuing the work of the 2014 Ontology Summit and facilitating discussions of ontologies and their development and application. I will be contributing to those discussions in 2016, and started with a short post on the various definitions of the term, ontology. Check out the SWAO link above for the discussion!

That's it for now. Happy 2016!

Andrea

Semantic Web and Business (Part 3)

In case anyone is confused by all the technical terms used in semantic computing, here is an explicit translation from ontology "language" to English:

• Concept = class = noun = vocabulary word
• Triple = subject-predicate-object (such as "John went to the library" - where "John" is the subject, "went-to" is the predicate, and "library" is the object)
  
• Role = relation = association = the predicate in the triple = verb
  
• Instance = a specific occurrence of a concept or relationship (can be manually defined or inferred)
• Axiom = a statement of fact/truth that is taken for granted (i.e., is not proved)
• Inference = deriving a logical conclusion from definitions and axioms
• T-Box = a set of concepts and relationships (i.e., the definitions)
  
• A-Box = a set of instances of the concepts and relationships
• Hierarchy = arrangement of concepts or instances by some kind of classification/relationship mechanism - typical classification hierarchies are by type ("is-a" relationships - for example, "a tiger is a mammal") or by composition ("has-a" relationships - for example, "a person's name has the strucutre: personal or first name, zero or more middle names, and surname or last name")
• Subsumption = is-a classification (determining the ordering of more general to more specific categories/concepts)
  
• Consistency analysis = check to see that all specific instances make sense given the definitions, rules and axioms of an ontology
  
• Satisfiability analysis = check to see that an instance of a concept can be created (i.e., that creating an instance will not produce an inconsistency/error)
• Key = one or more properties that uniquely identify an individual instance of a concept/class
  
• Monothetic classification = identifying a particular instance with a single key
• Polythetic classification = identifying a particular instance by several possible keys which may not all exist for that instance
  
• Surrogate key = an artificial key
  
• Natural key = a key that has semantic meaning
• CWA = Closed World Assumption (in databases) = anything not explicitly known to be true is assumed to be false (for example, if you know that John is the son of Mary but have a total of 3 children defined - John, Sue and Albert - and you ask who all the children of Mary are ... you get the answer "John" - 1 child)
  
• OWA = Open World Assumption (in semantic computing) = anything not explicitly known is assumed to be true (using the same scenario above, asking the same question ... you get the answer "John, Sue and Albert" - 3 children)
  

These are the terms that come to the top of my mind, when I think about ontologies. But, if there are others, just send me email or leave me a comment.