In this paper we review the integration of BFO's theory of types with OntoClean's notion of Rigidity, provide our decision tree procedure for evaluating ontologies based on the integration, while also describing its implementation as a Protégé 4 plugin, the BFO-Rigidity Decision Tree Wizard. Finally we provide a practical analysis of controversial and important ontological topics surrounding the BFO-Rigidity integration work. The decision tree approach allows our wizard plugin to implicitly perform inferences on behalf of a modeler based on answers to questions. This approach is accessible because it does not require familiarity with BFO, OntoClean, or our first-order formal system, and does not require the modeler to make assertions that are not normally considered within the scope of a domain level ontology. Having chosen for our implementation a plugin environment that interoperates with a popular ontology editor, we expect that the principles underlying the integration work will become more accessible to both novice and expert domain modelers.

This paper provides a reformulation of OntoClean's notion of Unity and Identity within a formal theory of classes, and evaluates how the reformulations apply to BFO's theory of types, which was previously given within the same formal theory. For Unity, a definition schema and explication together express the underlying dependency between a unifying relation and some proper subrelation of the ‘part of’ relation, which together define how a particular of a class is a whole. For Identity, the notion of an identity criterion is ontologically grounded and formalized as an identity procedure. For both Unity and Identity the formulations are expressed within a sorted first-order logic, where staying within first-order expressivity proved difficult in past work. With our reformulations in hand we evaluate the primary type dichotomy for material entities of BFO, Object and ObjectAggregate. Together with the work that integrates OntoClean's notion of Rigidity with BFO's theory of types, this work augments ongoing efforts to build software designed to evaluate and standardize OBO Foundry candidate ontologies, of which BFO is the upper level ontology.

The Open Biomedical Ontology (OBO) Foundry initiative is a collaborative effort for developing interoperable, science-based ontologies. The Basic Formal Ontology (BFO) serves as the upper ontology for the domain-level ontologies of OBO. BFO is an upper ontology of types as conceived by defenders of realism. Among the ontologies developed for OBO use, there are those which have been ratified, and those currently holding the status of candidate. To maintain consistency between ontologies, it is important to establish formal principled criteria that a candidate ontology must meet for ratification. Members of the OBO Foundry have expressed interest in using OntoClean to help construct BFO compliant domain ontologies. OntoClean is a system that decomposes the notion of sortal into criteria for deciding when subsumption can hold between classes. OntoClean primarily includes three components, based on the notions of Rigidity, Identity, and Unity. The methodology for integrating the OntoClean and BFO approaches to constructing consistent ontologies has been clarified by this dissertation. A formal integration between BFO, the Relation Ontology of BFO (RO), and OntoClean is given. The informal aspects and differing formalisms within and between the theories are analyzed and integrated within the axioms and theorems of one first-order system put forth in the dissertation. To set the foundation for this work, the categorical units of type and property of BFO and OntoClean, respectively, are unified under class. The modal logic axioms that OntoClean's theory of Rigidity is expressed within are interpreted and reformulated in our system, where axioms connecting it with BFO's categorical unit type is given. Central to this work is the axiom that a type is a class that is Rigid, i.e., a class whose definition is fundamental to the existence of the members of the class. A unity criterion for a class is a way in which certain parts of a member of the class are related such that they form the whole member. Our reformulation of this work focuses on the notion of the underlying unifying relation. As opposed to the informal approach taken by OntoClean, we express the notion that a class is unified under a relation as a meta-predicate defined by a definition schema. An identity criterion for a class is a test by which a member of the class can be re-identified. However as given in OntoClean, the notion of identity criteria is ontologically ambiguous. A formalization is given that provides a mapping to processes during which identity is confirmed. The reformulations of Unity and Identity are discussed in terms of Material Entity subtypes of BFO's theory. The integration work and resulting formal system affords a theoretically sound ontological foundation. A method for evaluating and standardizing candidate OBO Foundry ontologies is developed atop this foundation, where the method focuses on BFO's integration with OntoClean's notion of Rigidity. The method is given as a decision tree algorithm that evaluates one class at a time as they are introduced into an ontology, asking a prospective modeler questions that map to specific integration axioms. Finally, an implementation of the decision tree is provided in the form of an interactive Wizard plugin for the ontology editor Protégé. In an iterative approach informal user testing was applied to improve the questions and error messages. The plugin serves to facilitate ontologists and subject matter experts in making explicit what is implicit in, or unclearly specified for, the classes they choose to introduce into an ontology. Ultimately though, the integration axioms serves as a software platform-independent foundation for future software designed to evaluate and standardize candidate domain ontologies for the OBO Foundry.

In the fall 2010 issue of the AI Magazine, we reported the design, implementation and evaluation of a knowledge acquisition system called AURA. AURA enables domain experts in Physics, Chemistry and Biology to author their knowledge, and a different set of experts to pose questions against that knowledge. The evaluation results previously reported were from 50 pages each from science textbooks in Physics, Chemistry and Biology. The results were most promising for Biology. Based on those results we undertook a content building effort to capture knowledge from approximately 315 pages (or 20 chapters) of the same Biology textbook [2] and incorporated the resulting content in the electronic version of that book. In this demo/poster session, we will demonstrate the biology knowledge base (KB) created using AURA, the electronic textbook application Inquire, and discuss the knowledge engineering process we used to construct the KB.

To scale the knowledge base of a Biology textbook from 50 pages to 300 pages in the context of Project Halo, we have formulated a knowledge factory process [1]. The process involves a sentence-based encoding strategy under which a domain expert examines each sentence in the text-book [2] and represents it in a knowledge base (KB) as best as it can be represented. While encoding each sentence, at least two hard problems must be addressed: defining what it means to represent a sentence and defining the necessary ontology primitives that should be used in that representation. The purpose of this poster presentation is to explain these problems in more detail, and discuss the operational solutions that we have adopted for solving them.