Posts Tagged ‘Reasoning’

The Business Value of Reasoning with Ontologies

[Editor’s note: this guest post was co-written by Héctor Pérez-Urbina (Clark & Parsia) and Juan Sequeda (Capsenta)]

Image of a human brain with computer data overlay.Important enterprise business logic is often buried deep within a complex ecosystem of applications. Domain constraints and assumptions, as well as the main actors and the relations with one another, exist only implicitly in thousands of lines of code distributed across the enterprise.

Sure, there might be some complex UML diagrams somewhere accompanied by hundreds of pages of use case descriptions; but there is no common global representation of the domain that can be effectively shared by enterprise applications. When the domain inevitably evolves, applications must be updated one by one, forcing developers to dive into long-forgotten code to try to make sense of what needs to be done. Maintenance in this kind of environment is time-consuming, error-prone, and expensive.

The suite of semantic technologies, including OWL, allows the creation of rich domain models (a.k.a., ontologies) where business logic can be captured and maintained. Crucially, unlike UML diagrams, OWL ontologies are machine-processable so they can be directly exploited by applications.

Read more

Computing Like a Human has posted an article about how scientists are trying to develop computers that can think and see like humans do. The article states, “Hiroyuki Akama at the Graduate School of Decision Science and Technology, Tokyo Institute of Technology, together with co-workers in Yokohama, the USA, Italy and the UK, have completed a study using fMRI datasets to train a computer to predict the semantic category of an image originally viewed by five different people. The participants were asked to look at pictures of animals and hand tools together with an auditory or written (orthographic) description. They were asked to silently ‘label’ each pictured object with certain properties, whilst undergoing an fMRI brain scan.” Read more

Standards News: Using SPARQL to express rules and object behavior for the Semantic Web

SPIN - SPARQL Inferencing NotationThe current stack of modeling languages for the web of data provide excellent mechanisms for capturing the static structure of data. SKOS can be used to describe concept hierarchies and vocabularies. RDF Schema and OWL can be used to define classes, properties and relationships between these conceptual entities. There is, however, a key set of application requirements these languages have not dealt with. Namely, the way to describe general computational behavior of objects.

These requirements are now addressed by an emerging standard that uses SPARQL to express rules for the Semantic Web. It is called SPARQL Inferencing Notation or SPIN. Because of its heavy use of SPARQL it is also known as SPARQL Rules. SPIN has recently been accepted by W3C as a member submission from TopQuadrant, OpenLink and RPI.

SPIN combines concepts from object oriented languages, query languages, and rule-based systems to describe object behavior on the web of data. Read more