Welcome to Onts and Quants.  This blog reflects my passions for the development of logical and statistical models for a variety of subject areas.

The logical models are known as ontologies.  The classical definition of ontology is the philosophical study of the nature of being.  In the Semantic Web/Linked Data community, an ontology is a description logic model of concepts, attributes, and relationships.  Capturing the essence of a problem in an ontology allows the formulation of rules that allow one to reason on the information and to draw conclusions from it.

Another important type of model for understanding a process is a quantitative statistical model.  In recent years the increase in computing power has enabled more powerful methods for organizing data and applying statistical techniques to them.  Whether you refer to these techniques as predictive analytics or machine learning, the ideas are similar.  Given a volume of data with multiple attributes, both involve determining which features can we extract in order to summarize the data and to make forecasts.

My career has been spent in performing these types of analyses to a variety of problems, from the testing of Navy weapons systems to the development of financial models.  I can quickly analyze a problem, identify the relevant data items, and build a model that represents the metrics that really matter.  I can help you with your analytics needs.  More details about Onts and Quants Capabilities are given here.

Pete