Ontology Reuse In MBSE Henson Graves Abstract January 2011 The promise of Model-based systems engineering (MBSE) is to reduce traditional problems of complexity management and allow for design evaluation before implementation. The promise has been difficult to realize. The promise requires the ability to share models without the necessity of the model being accompanied by a subject matter expert to explain what the model means and what assumptions are made. An ontological foundation, or formal foundation, for a modeling language enables model sharing between humans and computers as the meaning of the model is in a form that is independent of subject matter experts. An ontological foundation not only provides the ability to share models, but also provides the justification for inference. SysML does not currently have an ontological foundation. However, it can be retrofitted with one. The retrofit is outlined using a SysML model as an example. The formal foundation uses intuitionistic type theory. the semantics of type theory accords well with the informal semantics. An intuitionistic type theory is generated from axioms expressed in the language of a multi-sorted signature of types, properties, and operations. Henson Graves January 2011

Outline Examples of reuse of existing ontologies Potential reuse Opportunities What are the benefits Approaches to ontology reuse Some observations on reuse Next steps

Ontology Reuse In MBSE Examples Units and measures Physical interactions (laws) Material classification and properties Enterprise concepts Levels of rigor in ontologies Vocabulary Informal textual semantics of vocabulary Formal (axiomatic) semantics

Potential Reuse Opportunities Ontology for events Ontology for computational methods Ontology for experimental setups Ontology for system engineering artifacts Ontology for product structure and attributes Ontology for measurement value spaces

Ontologies may be Organized into hierarchies Foundation Ontologies Base, Mission, Project, Quantities-Units-Dimensions-Values, Analysis, Artifact, Architecture Description Discipline Ontologies Mechanical, Electrical, Physics, Thermal, Propulsion, Attitude Control, Navigation, … Application Ontologies Star Tracker, Sun Sensor, Reaction Wheel, Thruster,.. 2-axis vs. 3-axis S/C; Radio vs. optical comm; … use Fundamental terms use in all projects, disciplines, and applications Discipline-specific terms specified and owned by discipline experts Kinds of items that are modeled in a project; specified and owned by application experts Focus is integration and interoperation Focus is reuse

What Are The Benefits Leveraging reusable knowledge to jump start engineering Basis for model integration and large scale collaboration Standardization of engineering work products

Approaches To Achieving Reuse Opportunistic Reuse: identify candidate ontologies, acquire and refurbish and make available Designed Reuse: establish modeling principles and start over, making use of lessons learned

Opportunistic Reuse Identify candidate ontologies, acquire and refurbish and make available Opportunistic reuse has only had limited success in Hardware component design Software design Reuse only worked well when the right units of modularization were understood, e.g. ASICS, Patterns

Designed Reuse Process Collect any reuse ontology candidates Document modeling principles to be used in redo Chose a foundation (upper) ontology, e.g., DOLCE in accord with design principles Modify if needed, based on experience Create specializations of subsets of the upper ontology, e.g., For physical laws, enterprise concepts Repeat as needed

Upper Ontology Concepts That Might Be Useful Classes Properties

Example From Upper Ontologies That Is Particularly Useful: Qualities Physical Object hasQuality Quality Type Car hasMeasuredWeight Measured Weight inPounds 1D Space With units The DUL class hierarchy includes classes for Physical Object, Quality, Event, and Region. These classes capture many concepts needed for systems engineering. Physical objects exist in time and have qualities such as weight, shape, color that are observed or measured. DUL differentiates between individual qualities (e.g., the weight of a specific material item), quality types (weight and color), quality spaces, and quality positions (locations in quality spaces). These together with Regions (measure spaces) which is used as the value space for a quality of an entity. DOLCE differentiates between individual qualities (e.g., the weight of a specific material item), quality types (weight and color) quality spaces, and quality positions (locations in quality spaces) these, together with measure spaces (which coordinitize the quality spaces). Quality – used to classify entities that are perceived or measured, have values, about some other entity. Examples of qualities are color, length, mass, and shape, Region – used to classify the actual value of qualities associated with particular entities. Empty 1969 VW <Vw,mwt> Weight object <mwt, 18k> 18K pounds

Next Steps For Ontology Reuse Development Get a working group established for this purpose Collect any reuse ontology candidates Document modeling principles to be used