Upper Ontology Summit Glossary    (LKK)

Semantic Interoperability    (LKM)

Semantic Interoperability-def    (LKN)

I think it will be useful to distinguish a base 'semantic interoperability" from the "scalable semantic interoperability" that has been mentioned in the Joint Communique. This page can serve to allow the Upper Ontology Summit participants to reference a definition that describes the intended meaning of that phrase in our documents.    (LKO)

First proposal: March 12, 2006 by Pat Cassidy    (LL9)

(1) Current definitions of "semantic interoperability"    (LLA)

(1.1) For reference, One description of the base concept of "semantic interoperability" occurs in a paper by Heflin and Hendler (http://www.cs.umd.edu/projects/plus/SHOE/pubs/extreme2000.pdf)    (LLB)

"i.e., the difficulty in integrating resources that were developed using different vocabularies and different perspectives on the data. To achieve semantic interoperability, systems must be able to exchange data in such a way that the precise meaning of the data is readily accessible and the data itself can be translated by any system into a form that it understands."    (LLC)

(1.2) Another comes from the glossary of SICoP White Paper number 1:    (LLD)

http://colab.cim3.net/file/work/SICoP/WhitePaper/SICoP.WhitePaper.Module1.v5.4.kf.021605.doc    (LLE)

"Semantic interoperability is an enterprise capability derived from the application of special technologies that infer, relate, interpret, and classify the implicit meanings of digital content, which in turn drive business process, enterprise knowledge, business rules and software application interoperability"    (LLT)

Additional comment in that white paper, though not a "definition" of semantic interoperability, describes the purpose:    (LLF)

"Formally put, the use of semantic technologies makes it possible to describe the logical nature and context of the information being exchanged, while allowing for maximum independence among communicating parties. The results are greater transparency and more dynamic communication among information domains irrespective of business logic, processes, and workflows (Pollock and Hodgson, 2004). "    (LLU)

(1.3) Interoperability generally, from Oscar Corcho and Asunción Gómez-Pérez: "Ontology translation approaches for interoperability: a case study with Protégé-2000 and WebODE" (http://www.cs.man.ac.uk/~ocorcho/documents/EKAW2004_CorchoGomezPerez.pdf)    (LQO)

"In Computer Science, the term ‘interoperability’ is defined as the ability to transmit data and exchange information between systems whilst allowing each system to process information independently [18]. If we refer to ontology tools and languages, the term ‘interoperability’ can be defined as their ability to exchange ontologies without losing knowledge, in such a way that users of the target format (be them human users or applications) can understand correctly the ontology transformed. This complex transformation process is usually known as ontology translation [14]."    (LQP)

(1.4) Other definitions are contained on the ONTACWG Glossary page:    (LLG)

http://colab.cim3.net/cgi-bin/wiki.pl?OntologyTaxonomyCoordinatingWG/OntacGlossary    (LLH)

(2) Proposed definition of "semantic interoperability"    (LM2)

(2.1) Semantic interoperability – base concept    (LLJ)

I would propose a linguistic definition of the base concept in this form (which is weaker than the definitions proposed by Barry Smith, which is closer to what we might now call "scalable semantic interoperability"):    (LLK)

"Semantic Interoperability is the ability of two or more separately developed computer systems, each of which performs inferences on declaratively described data, to exchange their data and arrive at the same inferences from the same data, automatically and without intervention of humans in the process."    (LLL)

(2.2) in this definition, "Declaratively described data" is data that is separate from the procedural program, viewable in some form comprehensible to humans. Data in tables, databases, formatted ASCII files, or unstructured texts are all 'declaratively described data'.    (LLM)

(2.3) NOTE: all computer programs perform inferences. Inferences on declarative data can be performed by full programs, methods, or subroutines. Inferences can be performed by the implicit logic of the procedures, or by rules in a logic which is itself expressed in declarative form, as in axioms in a first-order language. The last might be termed 'declaratively expressed logical rules'. Examples are axioms present in some upper ontologies.    (LLN)

(2.4) The base concept can include a low-level 'semantic interoperability' that is achieved in various ways, including methods that do not require explicit logical rules outside of the communicating programs. Agreement on common XML schemas for message interchange and a method for interpreting those schemas could qualify as 'semantic interoperability' in this base sense. Agreement on a common database schema, with a fixed vocabulary of terms, could qualify as this base 'semantic interoperability'    (LLO)

(2.5) This level of semantic interoperability could be achieved by systems interchanging data using relatively less expressive knowledge formats, such as UML or OWL. The base 'semantic interoperability' includes interoperability relative to interpretive logic that may be less expressive than first order logic.    (LLP)

(3) "Scalable semantic interoperability"    (LM1)

(3.1) "Scalable semantic interoperability" is semantic interoperability that is not restricted to a predetermined topic, can accommodate new topics without change to the fundamental knowledge representation principles, and therefore permits systems to interoperate automatically without human intervention with other systems that have not previously been exposed to the new topics communicated by other systems."    (LLQ)

(3.2) This level of semantic interoperability will require that each interoperating system be able to define (in a broad sense) new concepts of interest to the local system and to communicate those definitions (as well as the data of interest) so that other systems can properly interpret the concepts previously unknown to them, and produce inferences over those concepts identical to the inferences produced by the originating system..    (LLR)

(3.3) If a recipient system has a richer set of axioms or additional information relevant to the topic being communicated, it may reach additional inferences not reached by the originating system alone. In that case, depending on the purpose, a recipient system may also transfer its additional relevant axioms and information back to the originating system, to permit both systems to arrive at identical inferences.    (LLS)