Ontologizing is a common practice within federation and integration of systems community. Most often ontology is used for provide mappings for data models of participating systems. This mappings would be done in two main architectures:   

• point-to-point (ad hoc) with an ontology knowledge for clarification of meaning of data in each systems   
• to common ontology (reference data) for a federation of systems   

Also ontology can have use of providing powerful concepts (mereology etc.) for federation architectures description, adding means of federation description for architecture languages (both systems architecture and service architecture languages). There are no consensus yet what such ontology-based architectural language can look like.   

Examples of systems integration/federation:   

• PLM systems in systems engineering is a means for system integration for CAD/CAE systems. This is already ontology/terminology based on a base of proprietary ontologies of PLM/CAD/CAE vendors. Most of PLM systems have federation/integration tools based on ontology.   
• there are deficiencies in PLM federation (multiple PLM with different ontologies/terminologies/data models), but strong demand from engineering community. PLM vendors not in help here because this require usage of vendor-neutral ontology.   
• there are multiple domains that need integration in this fields is problems with process/project/case execution integration, but this is more experiments now and cannot be replicated as a product on a market.   

Examples of neutral (“ontology as a standard”) ontologies, specifically targeted for systems integration/federation are ISO 15926, HDQM, Gellish, IDEAS. The most important things were:   

• The broadest possible context,   
• Extensible,   
• Enable anything to be said that is valid (i.e. no artificial restrictions),   
• Explicit ontological commitments that are followed consistently   
• Strong methodology so that the same thing is represented in the same way by different analysts, including,   
  • Choice of alternative approaches left open by ontological commitments,   
  • Consistent representation so the same thing would get pretty much the same name from different analysts.   

Up today there is no understanding for what can be mapping language for federation/integration. Opinions are different:   

• FOL as minimum   
• HOL as actually needed   
• general purpose language (with access for both mapping ontologies in their native representations),   
• combined of all above.   

There are multiple questions about usability of semantic web (RDF/OWL ecosystem) for systems federation purposes, but this is mainstream now.   

Main difficulties for ontology work in federation/integration of systems:   

• absence of quality reference data (available proved/trusted domain ontologies). Expectancy for linguistic processors that will parse engineering, financial and other domains standards and will provide this data. Expectancy of distributed manually producing such a data (ontology crowdsourcing) is not realized up to now. Multiple complex for ontologization domains: process/project/case management, geometry of engineering CAD systems, multi-physics real time models, etc.   
• no knowledge for distributed ontology development/evolution and federation (to map data of different systems first you should federate your reference data). Ontology versioning is a nightmare. Ontology granularity is an issue.   
• performance issues (including a) performance of ontology engines and b) performance of federated SPARQL endpoint on network)   
• quite complex low level API for data access in most available federated systems   
• no ontology/terminology of system federation/integration architecture domain and mapping/translation/compiling domain: this lead to difficulties in collecting of good practices in programming, modeling, ontologizing in-the-large and comparison of existing implementations/frameworks   

Topics for 1st of March 2012 session   

"Leveraging Semantic Technology across systems to meet the goal of having an 'executable, integrated, consumable, solution architecture'" (DennisWisnosky)   

Integration of BEA, BPMN 2, DM2 ontologies and testing it in real systems environment.   

Ontology based Integration Platform for Modelling and Simulation - Simantics (TommiKarhela)   

Activities and experiences in utilizing ontologies in integration of system simulation software like different process simulators, system dynamics tool, LCA-tool and design systems.   

Simantics: open platform for modelling and simulation   

• Developed at VTT since 2006   
• Application development platform   
• Integration solution for modelling and simulation   
• Semantic graph based representation of data   
• Licenced under Eclipse Public Licence   

Goals   

• Reusable components for modeling and simulation infrastructure (less focus on solver technology)   
• Multi-disciplinary, multi-level simulation and modeling   
• Supports the whole life cycle of the facility or product   
• Distributed simulation   
• Model integration   
• Solver integration   
• Team work   

Ontology-Based Systems Federation (AnatolyLevenchuk)   

There are multiple levels of systems federation: hardware, software, peopleware. It should be federated system-of-interest, systems in operation environment and enabling systems models to comprise mega-model of overall endeavour. We need to integrate product model, (including cyber-physics simulation models) and enterprise model (enterpise architecture).   

There are ontologies (data models) that governs potential interoperability of federated systems. This ontologies also need to be federated. There are not too much reasoning here but a lot of mapping.   

One of the examples of such "federated ontologies for system federation" architecture is ISO 15926 that aim now to federate CAD/CAM/PLM systems in industry-wide and business eco-system-wide (beyound boundary of enterprise) scales.   

Semantic Information Modeling for Federation (CoryCasanave)   

This presentation will show how conceptual semantic modeling can be used as a “pivot point” for federating and integrating information. The conceptual modeling approach distinguishes between “conceptual domain models”, models of the “real world”, from “logical information models”, models of information and systems for a particular purpose. These are then joined with “model bridging relations” to achieve federation. We will explore the use of OWL and UML for these purposes.   

This approach of “pivoting through conceptual models” is the subject of an in-progress RFP: OMG “Semantic Information Modeling for Federation” (SIMF). The SIMF RFP asks for submissions for a standard that addresses the federation of information across different representations, levels of abstraction, communities, organizations, viewpoints, and authorities. Federation, in this context, means using independently conceived information sets together for purposes beyond those for which the individual information sets were originally defined.   

The information federation and sharing problems are well known and recognized by every major organization, costing trillions of dollars annually – yet sufficient standards and tools tailored to this problem do not yet exist. We have the opportunity to make a substantial dent in the world-wide “data problem”.   

Cory Casanave is a leader in model driven semantic technologies and is one of the drivers of the SIMF RFP. He has contributed to numerous modeling standards and applied these standards to government and corporate needs. Mr. Casanave is founder of Model Driven Solutions, a services company connecting business needs with technology solutions.   

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