The Foundation Ontology as a Basis for Semantic Interoperability Patrick Cassidy

1. The Foundation Ontology as a Basis for Semantic Interoperability Patrick Cassidy MICRA, Inc., Plainfield, NJ cassidy@micra.com Version modified from the OIC-2008 presentation

2. Outline • Accurate general Semantic Interoperability requires that different systems represent their knowledge using a common Foundation Ontology (FO). The common Foundation Ontology provides a common set of concept representations that can be used to logically describe the intended meanings of any of the more complex concepts not in the FO. • Basing the common FO on the full set of fundamental conceptual elements (sometimes called “semantic primitives”) provides a means to limit the need for agreement; viewing the FO as a means to translate among different representations allows complete freedom for locally optimal representation. • A common foundation ontology that can be widely adopted should be as small as possible, to maximize agreement • To make usage easier, utilities are necessary; a good Natural Language interface may be required • A collaborative project to develop an FO according to these principles, by a consortium of about 100 participants, is feasible and limited only by the need for funding of the participants

3. The Problem of Independent Applications • Different groups develop their own databases, terminologies, and ontologies. Local communities want to do their own thing, not be forced to conform. • When there is a need to communicate information among independently developed databases or applications, for automatic use (without human intervention) information needs to be communicated and interpreted accurately – i.e., systems need to interoperate at the semantic level. • The ability to create special data structures without reference to a common vocabulary standard for information transfer within a community having specific needs cannot scale to the general situation where information must be in a form interpretable by any other system that can use it. • The absence of a common vocabulary for data elements makes accurate interoperation impossible. • Semantic Interoperation requires a common standard of meaning; if any undefined terms are used in the description of a term or concept, accurate interpretation is impossible. Only an agreed basic vocabulary will support accurate interpretation within a community. The FO supplies the basic “vocabulary” for logical representation of many domains, allowing translation of any domain ontology into any other.

4. A Language is More Than a Grammar • The term “language” has been used to mean qualitatively different things, such as computer “languages” like FORTRAN, C, or JAVA. • A language in the sense relevant to the interoperability problem must have both a grammar and a vocabulary. • Ontology “languages” such as OWL or CL consist primarily of a grammar, with a minimal semantics defining the logical operations. • Regardless of how widely any grammar such as OWL is used, accurate communication will be impossible without some agreement on a vocabulary. • The FO tactic makes that agreement easier by requiring agreement only on the basic concepts used to describe all others, leaving application developers free to invent an unlimited number of terms and concepts for local use without any contact with other groups, and still have their information accurately interpreted by any other system using the basic vocabulary. • The goal of the FO project is to find agreement on that limited vocabulary of basic ontology elements, and demonstrate that this is adequate to support general interoperability.

5. A Solution for The Problem • Locally developed applications can use small, specialized ontologies, idiosyncratic ontologies, or no ontology at all and still perform their work perfectly, and share information using local agreements for the meaning of the data. • BUT When local applications need to share complex information with many other systems, a common, expressive standard of meaning (i.e. a common language) is essential for communication. • The Solution – a common Foundation Ontology to provide a standard for Content to complement the existing standards for Format and basic-level Semantics (such as OWL or FOL). • There is a widespread assumption that getting some broad agreement on a common Foundation Ontology is impossible. This assumption is largely based on the ambiguity of language, and a simplified view of the function of the Foundation Ontology. There is no technical, social, or psychological barrier – what has been missing is a proper interpretation of the function of the FO, and adequate funding.

6. Overview of the FO Project • The goal is to find a means to translate assertions in one ontology language (grammar + vocabulary) into another ontology language. The translations will use axioms having elements in common between the two ontologies. • there are some ontology elements whose intended meanings cannot be expressed solely as an FOL combination of other ontology elements. These are called the "primitives“ in this discussion. (3) for any given group of domain ontologies, there will necessarily be some set of such primitives that will be sufficient to logically specify by FOL combination the intended meanings of the non-primitive elements of all of the other ontologies in the study. These constructed meanings will not necessarily be complete descriptions of the intended real-world referents; they will be sufficient to perform the computations desired for the applications supported by the domain ontologies. (4) To *accurately* translate logical assertions among those domain ontologies, the most parsimonious tactic (and probably the fastest) would be to identify the primitives in common among those domain ontologies, include them in an FO, and use them to create translations of assertions between the domain ontologies. Those translations will use "bridging axioms" to convert assertions from the form in one ontology to the form in another ontology.

7. Overview of the FO Project (2) (5) To minimize the changes in the FO as new domain ontologies are linked to (mapped to or logically expressed by) the FO, it is advisable to try to identify as many of the possible primitives as can be identified, at the earliest stages of testing of the FO. This should reduce the number of new primitives that need to be created as new domain ontologies are linked to the FO. Since the test has never been done, we do not know whether or how quickly the need for new primitives will drops for each new domain. That can only be determined by testing the FO process. It is possible that new primitives will need to be continually added; even so, this method promises to be the most effective to achieve the maximum and most accurate semantic interoperability that is possible at any given time.

8. Overview of the FO Project (3) (6) As possible inventories of primitives that should be included in a *starting* FO, to aim for the broadest coverage as quickly as possible, I suggest using the senses associated with the Longman dictionary defining vocabulary - 2148 words, and probably over 4000 senses. Longman has been tested for its ability to linguistically define all other words in the dictionary, but whether there could be a similar small inventory of primitive ontology elements that can combine to specify *all* other ontology elements is unknown and may be impossible. The more relevant question is whether a set of primitive ontology elements can be found that will not need *significant* supplementation as new domains are linked to the FO; if little supplementation is needed, the FO should be stable enough for most practical tasks requiring semantic interoperability. This question can only be answered by testing multiple domain ontologies versus some common FO. (7) Other possible sources of essential primitives could be the 3000 most frequent Chinese characters (covering 98.9% of modern text) and the 4000 most common signs of AMESLAN. But these symbols have not been tested as a "defining vocabulary".

9. Overview of the FO Project (4) (8) The fastest method to test the FO hypothesis is to create a consortium of multiple diverse groups of ontology developers and potential users (and relevant standards groups), to (1) conduct a carefully organized study to agree on a common FO containing all of the primitives necessary to translate assertions among their domain ontologies; (2) test the utility of the FP-linked ontologies in practical applications, and (3) test the ability of the FO to support accurate semantic interoperability among those applications.

10. The Principle of Semantic Primitives • For any given group of domain ontologies, it is possible to identify some set of basic ontology elements (the Foundation Ontology, or FO) that can be combined to form the more complex ontology elements in the domain ontologies. Those basic ontology elements can be viewed as representing the “semantic primitives” for that group of ontologies. These primitive elements can be used to translate information from its form in any one of those ontologies to its form in any of the others. Any logical contradictions among the linked ontologies can be recognized and represented. • As the number of ontologies linked increases, the number of new primitive elements required to link those ontologies will decrease. At some point the FO will be stable enough to serve as a reliable standard of meaning for accurate semantic interoperability.

11. What are the “intended meanings”? The intended meaning of an ontology element reflects two criteria: • The meaning that the creator of the ontology element intends to capture by the logical specification: ideally, this will be unambiguously described by the linguistic documentation as well as reflected in the logic. • The behavior of the programs that use that ontology element must correctly reflect the behavior (insofar as it is affected by that ontology element) that the ontologist and programmer both intend for that program. • Any change in an ontology that affects the logical specification of an ontology element must not change either the meaning as intended by the ontologist, or the behavior of the ontology-based application, unless that change is understood and accepted by the ontologist and programmer.

12. Mapping versus Translation • Automated mapping without a common foundation ontology is too inaccurate for mission-critical automated decisions • Semiautomated mapping without a common interlingua ontology is too expensive - order of n2 effort; however, mapping to a common ontology reduces the effort to integrate multiple ontologies, including those initially developed without reference to the common ontology. • Domain ontologies developed from the start by using the common foundation Ontology to describe the domain terms will be automatically translatable into each other, with no need for post-hoc mapping to any other ontology.

13. Mapping and Translation • Whenever careful mappings are created between different ontologies, the elements appearing in the mappings will be either primitive elements or elements than can be expressed as an FOL composition of primitives. Identifying the common elements in such mappings could provide one method for identifying the fundamental primitives that are required for describing the meanings of the domain elements. Those primitives can then be used for translation among many ontologies. • One ontology mapping project (“COLORE”) may provide a source of candidates for inclusion in the FO. • See: http://ontolog.cim3.net/file/work/OOR-Ontolog-Panel/2009-02-19_OOR-Development-II/colore-ontolog-oor--MichaelGruninger_20090219.pdf

14. The FO and COLORE • The FO as described here could be the “given ontology” that is referenced in one of the COLORE use cases: COLORE example use case: • retrieving ontologies with respect to particular relationships e.g. all ontologies that are interpretable by a given ontology

15. The Translation Tactic:Everybody Gets Everything They Want By supporting Translation among different local knowledge representations • Nobody has to stop doing anything they want to, they can do it exactly the way they want to do it • When applications need to communicate, the developers only need to learn the common defining language (or collaborate with someone who already knows it) and map to it • Learning and using the common language of the foundation ontology is time-consuming, but can be made easier by utility programs – commercial and open-source, and a Natural Language interface.

16. Alternatives to a Common Foundation Ontology? Mapping post-hoc vs. ab initio • The relations between types in two different ontologies may be: • Synonymy (same intended meaning) • Specialization (one type may be a subtype of the other) • The added constraint(s) by which the specialized type differs from the parent type must be specified, and that specification may require adding new types or relations • Overlap (there may be parts of the meaning of one type similar, and other parts different)

17. Difficulties with Mapping Ontologies Developed Completely Independently • Representations often combine fundamental components of meaning in different ways • Elements of different ontologies may overlap, rather than map directly or be in a hierarchical relation • The areas of overlap and non-overlap may require creation of new types or relations, more basic than the composite types. • Dissecting the components of each overlapping representations requires human-level intelligence • Creation of new basic types and relations requires human-level intelligence; cannot be done automatically • The documentation rarely has sufficient information even for a human to resolve the ambiguities • Mapping legacy ontologies to a common Foundation Ontology will reduce the efort from order of n2 to n.

18. Benefits of Mapping to a Common FO • Ontologies or Database Schemas newly created using the basic “conceptual vocabulary” of the FO will be automatically interoperable from their creation. • Retroactive integration of ontologies or DBs can benefit from mapping (semiautomated or by hand) to a common FO. • The effort for mapping to a common FO is order of n, rather than order of n2 for mapping between domain ontologies

19. More Difficulties with Mapping • Discovering the relations requires human inspection, though some automated methods can assist by suggesting relations, derived from text. It is not possible to automatically specifying the meaning of a relation by axioms expressing the inferences derivable from that relation holding. • Unless the original developers of two ontologies are available for consultation, the documentation will often be inadequate to resolve ambiguity of meaning of the elements • Creating a mapping may take more time than creating a new common ontology for the two applications

20. Difficulties with Mapping Ontologies (continued) • If two ontologies are accurately mapped (e.g. manually or semiautomatically), then the result will be in effect a common merged ontology. This can be used for interoperability, BUT: • (1) The net effect will be the same as having started with a common ontology, but the merger will be useful only for the ontologies mapped, and not for others. Mapping to additional ontologies will be increasingly complex. • (2) The effort to create this kind of mapping will only be cost-effective for the most important problems. • (3) The cost of such a process on multiple ontologies will be much greater than the cost of defining the domain ontologies by use of a common FO, unless the domain ontologies are very simple (few semantic relations and an accurate inheritance hierarchy)

21. How Can Incompatible Theories be Included? • The basic concepts that are required to specify meanings are generally agreed on. Differing viewpoints will usually be expressible in terms of a common vocabulary, and assertions in different terminologies or syntaxes will be directly translatable into each other. • One example: the often mentioned ‘incompatibility’ between 3-D (endurantism) and 4-D (perdurantism) views of objects in time. The actual assertions of each viewpoint are accurately translatable into assertions in the other viewpoint: • Pat Hayes (email to UOM-forum Aug. 8, 2009): “But, for the record, I reach the conclusion from the observation that anything that can be said in a 4D ontological framework can be transcribed into a 3D framework based on the continuant/occurrent distinction, and vice versa. The differences between them, I have concluded, are really nothing more than a matter of notational choice. “

22. 3D-4D Translation Axioms (Pat Hayes) From Pat Hayes: (forall (x (t Time) P)(iff (P x t)(P (x during t)) )) “Think of this as a 'bridging' axiom, part of a translation specification, if you like” . . . And later; • There are a variety of notational options in combining a simple timeless assertion with a temporal parameter. One is to treat the time as a context, in effect attaching it to the entire sentence (or in IKL, proposition):  (ist t (P x y)) (ist t (that (P x y))) • another is as an extra relational argument, giving the 'fluent' style which goes naturally with continuants: (P x y t) • and a third is to connect it to the object(s) being related, the relation then being naturally understood as a relation between time-slices: (P (x at t)(y at t)) • But in fact, these are really all just notational variations on a single theme. They amount to choosing where in the parse tree of the simple _expression_ to attach the parameter, is all. If we simply FORGET the philosophy for a second, then we can treat this as an arbitrary conventional choice, and think of them as all meaning exactly the same thing, and therefore equivalent.

23. 3D-4D Translation Axioms (COSMO) • {PH  isanInstanceOf  Object} • {PH4D  isanInstanceOf  Object4D} • {t1 isanInstanceOf TimePoint} • {t2 isanInstanceOf TimePoint} • {t1t2 isanInstanceOf TimeInterval} • {t1t2 hasStartingTimePoint t1} • {t1t2 hasEndingTimePoint t2} • {PH4D isTheWholeLife4dVersionOf PH} • {PHt1t2 isaTimeSliceOf PH4D from t1 to t2} ;; If we included a ‘during’ similar to the one Pat Hayes uses, it might look like: • {(PH during t1t2) isIdenticalTo PHt1t2} ;; The bridging axiom for a specific assertion would be: • {{PH isLocatedAt IHMC from t1 to t2}  iff  {PHt1t2 isLocatedAt IHMC}} ;; And, redundantly, given the above: • {{PH isLocatedAt IHMC from t1 to t2}  iff  {(PH during t1t2} isLocatedAt IHMC} • The above explicitly has a 4D entity PH4D as TheWholeLife4dVersionOf  the ‘dimension neutral’ object PH. NOTE: The bridging axioms can be generalized by using row variables.

24. Bridging Axioms in General • More detail for bridging axioms for various scenarios translating different styles of representation were presented in: IKRIS Scenarios Inter-Theory (ISIT) • Jerry Hobbs with the KRIS Scenarios Working Group • http://nrrc.mitre.org/NRRC/Docs_Data/ikris/ISIT_spec.pdf • Mirrored at: http://micra.com/COSMO/HobbesEtalBridgingAxioms.pdf

25. How Can Incompatible Theories be Included?(continued) • When representation of genuinely logically incompatible theories, not merely different viewpoints, are desirable in the FO or in some extension, the theories can be represented as theories using the defining elements of the FO. The assertions in theories are not themselves directly part of the ontological commitment of the FO, and describing incompatible theories does not make the FO itself inconsistent.

26. Representation of Incompatible Theories Does not Make the FO Self-contradictory • A logical contradiction in the FO would have some pair of statements of the form: • (P ?x) and (not (P ?x)) • But theories are represented in the FO as separate contexts: • (isTrueIn (P ?x) Theory1) and (isTrueIn (not (P ?x)) Theory2) • Logically contradictory theories can be described in the FO but not asserted to be true in the FO itself.

27. Similar Approaches • H. Wache, T. Vogele, U. Visser, H. Stuckenschmidt, G. Schuster, H. Neumann, and S. Hübner, "Ontology-based Integration of Information -- a Survey of Existing Approaches," Proceedings of the IJCAI-Workshop Ontologies and Information Sharing, Seattle, WA: 2001, pp. 108-117 Accessed at: http://www.let.uu.nl/~Paola.Monachesi/personal/papers/wache.pdf • H. Wache, "Towards Rule-Based Context Transformation in Mediators," in Proceedings of the International Workshop on Engineering Federated Information Systems (EFIS), 1999, pp. 107-122. http://citeseer.ist.psu.edu/cache/papers/cs/9658/http:zSzzSzwww.informatik.uni-bremen.dezSz~wachezSzPaperszSzefis-99-wache.pdf/wache99towards.pdf

28. Will Translation Among Logically Incompatible Ontologies Always be Possible? • Not necessarily. BFO is (for example) a single-inheritance ontology, and it is possible that trying to translate assertions from multiple-inheritance ontologies would cause a logical contradiction. • This might be avoided if the single-inheritance axioms of BFO are only used during the development of the classes of BFO-dependent ontologies, and not during data (instance) entry or query time . • There may or may not be workarounds for other cases of logical incompatibility. The Foundation Ontology (FO – see below) project would have to determine whether there are practical workarounds for true irreconcilable inconsistencies. • Groups that develop ontologies too inconsistent with the FO to use the translation mechanism , may develop a special FO for their own community with whom they must interoperate.

29. Integration of Diverse Information • Multiple diverse views of the same information will always be present • Integration requires a method to translate from one terminology and format to others • Overlap of meanings requires dissection of complex meanings into component primitives • For integrating multiple diverse views, a foundation ontology having representations of all of the primitives is required; a common syntax and bare logical functions are insufficient to resolve ambiguity and meaning overlap.

30. Integration of Knowledge SourcesVia Semantic Interoperability • Representation of knowledge using a logical-based ontology allows automated inferences using multiple data sources – “connecting the dots” rapidly and accurately, based on rules created by the domain experts • Automated reasoning that is reliable enough to be trusted to make important decisions without human intervention requires accurate information. • Information transferred from other systems can be used reliably only if the information is interpreted accurately. 99% accuracy is insufficient. • Accurate automated interpretation requires a common foundation ontology among information sources.

31. Why is 99% Accuracy Insufficient? The number of inferences deduced in the course of proving a test theorem can be greater than 10,000. (See: Owen L. Astrachan and Mark E. Stickel, Caching and Lemmaizing in Model Elimination Theorem Provershttp://www.cs.duke.edu/~ola/papers/cade92.pdf. If the likelihood of error in each step is as low as 1%, the chance of reaching a correct conclusion is 0.9910000 = 2 -44 If the number of inference steps in solving a problem is 68, there is a 50-50 chance of arriving at the correct conclusion with 99% accuracy in translation.

32. Can a Foundation Ontology be Generated Automatically by Extraction From Text? • Semantic relations are the heart of the meaning of an ontology. • Some relation labels among elements can be extracted with modest accuracy (<50%) from text; • BUT: The logical implications of relations, which are the basis for the meanings, are extremely difficult to specify without human-level understanding • Therefore an automatically generated ontology will be of low quality and need human editing to be useful for accurate reasoning.

33. Is there any Benefit to Extract an FO Automatically From Text? • Automatic ontology generation may be helpful in new and specialized domains, where no existing relevant ontology covers the field; BUT • (1) there are already several FOs from which to draw candidate basic concept representations; • (2) if there are in fact a limited number of primitives, the effort at hand-crafting an FO will not be prohibitive, since it will only have to be done once, with low maintenance cost. • Therefore there is no benefit in attempting to extract an FO automatically, even if that process helps with some domain ontologies.

34. Foundation Ontology • Generically, a Foundation Ontology is an ontology containing logical representations of the most general (abstract) entities (types, relations) that are used in constructing more specialized or domain-specific representations. Existing examples are OpenCyc, SUMO, BFO, DOLCE, ISO15926 and others. • For practical convenience, more specific extensions can be maintained to avoid unnecessary recreation of existing ontology elements; these extensions can form a hierarchy of ontologies (logical theories) • If logically inconsistent ontologies are included in the set of reference ontologies, they may be represented as a lattice of theories. • An FO used to support interoperability of any set of domain ontologies will have all of the basic concepts required to represent

35. What A Common Foundation Ontology Isn’t • A controlled vocabularyEach community can choose its own words to refer to concepts, and map those to the FO • A mandated standardUsers can use any common ontology or none, as their own needs dictate. A common FO isrequiredonly for accurate communication among multiple independent applications. • A Restriction on expressivenessAn individual user can use any local application with any language or technology. What must be expressed using the FO is only that information that needs to be shared with other communities.

36. Primitive Concept Representations A used here, a primitive ontology element is an ontology element whose intended meaning cannot be represented as a FOL combination of other elements in the FO. An FO that is intended to function to translate elements from one ontology to another should have all of those primitives that are used to represent the ontelms in either of the ontologies; the primitives may be in the FO itself, or in some mid-level or domain-level ontology used by both communicating ontologies.

37. Are There a Fixed number of Primitives? • It is possible that there may be no limit to the number of primitive ontology elements required to construct other ontology elements in all other domains. For the FO principle to serve for translating multiple ontologies, it is only necessary that all of the primitive elements required to construct all those ontologies are represented in the FO or in some extension common to the communicating ontologies. • Therefore it is not necessary that there be a fixed number of primitive ontelms in order for the FO tactic to support accurate interoperability. • However, evidence from linguistic experience suggests that the number of primitives required for broad applicability of an FO may be small. This evidence may provide some participants with additional motivation to explore the FO tactic. Primitives are discussed further below.

38. Are There a Fixed number of Primitives?Arguments from communication • The number of primitive concepts people use internally for their own thinking cannot be easily determined. • What is important for interoperability is the number of primitives used for communication. • Accurate communication depends on agents using symbols whose meaning is understood by all – this in turn depends on the meanings being associated with common perceptual experiences. The number of such distinguishable common experiences is limited. • By age 18, most people can understand definitions of new terms based on the fundamental concepts they have already learned. • This is the basis for the use of a limited defining vocabulary in dictionaries like Longman’s.

39. The Chemistry Analogy(not to be taken seriously) • Primitive Concepts can be viewed as the atoms of thought – the smallest units of information manipulated in human thinking and automated reasoning • Complex concepts are like molecules, composed of two or more primitives. • Natural language is like cooking – composing useful mixtures of molecules to create an interesting medley of concepts. Linguistic expressions are “food for thought”.

40. How Is Semantic Interoperability Achieved by a Common Foundation Ontology? (overview) • The elements of domain ontologies or databases are represented as First-Order-Logic (FOL) combinations of ontology elements (types, relations, axioms, functions – for short, “ontelms”) already present in the Foundation Ontology. • When information is to be communicated between systems using different domain ontologies, each system communicates, in addition to the data, the logical descriptions (axioms) for ontelms not already in the Foundation Ontology (or public extensions) that are required to understand the meanings of the data. • Each system, able to interpret both FOL and the ontelms used to describe the meanings, will be able to produce the same inferences from the same data, when both use the same or a functionally equivalent FOL inferencing engine. • If the reasoning used in each local system is restricted to logical inference on the represented knowledge, interoperability will be optimal. Local procedures may be created for efficiency purposes, provided that they use the knowledge in ways compatible with the logical meaning .

41. Semantic Interoperability via an FO (more detail: 1) The goal: An FO that can support the goal of “broad, general, accurate semantic interoperability” can be viewed as:  a system of agreed data structures and programs that allow *any* local group using this common system to place information **on any topic** on the internet or some other public place, or to transmit it directly to another system, and have the information interpreted in the sense intended by its creators, regardless of whether the transmitting and receiving systems have any prior contact. Proper interpretation requires that both transmitting and receiving systems reach the same inferences from the same data, and have the same real-world referents for each term. Any system that has more relations, will of course be able to reach additional inferences, but these will not be logically contradictory to the inferences that the less complete system reaches. A system that has more data may also reach additional inference, but the inferences should not be logically contradictory to the inferences reached by the less-informed system, unless the additional data itself is contradictory to that in the less-informed system.

42. Semantic Interoperability via an FO (more detail: 2) The FO would be used in this manner: •   The ontelms in the FO all have a meaning agreed to by the participants, and the logical specifications and linguistic documentation is unambiguous enough to satisfy all participants that they agree on the intended meanings, • The ontelms in domain ontologies or upper ontologies are identical to or logically specified as FOL combinations of ontelms in the FO (or in extensions of the FO).  • The computations performed with ontology-specified data in applications (other than simple input-output, or computations not affecting data communicated among applications) are performed either (a) using an agreed common implementation of FOL; or (b) the procedural code that is part of some element in the FO. Thus the calculations performed on data in communicating systems should be identical, and produce identical inferences.

43. Semantic Interoperability via an FO (more detail: 3) 4. When any two programs that want to interoperate and have separately developed domain ontologies need to communicate, then in addition to the data that is to be transmitted, the transmitting system must send all the logical descriptions of the domain elements needed to describe the data that are not already in the FO or in some extension used in common between those two applications.   There then needs to be an integrating program that (on the receiving side) takes the new descriptions of previously unknown elements, and integrates them into the local ontology, to arrive at an ad-hoc (temporary)  merged ontology that is sufficient to properly interpret the data communicated.  The merger should be accurate because all of the new ontology descriptions use only FO elements in FOL combinations, and the FOL implementation is common among all communicating systems.

44. Semantic Interoperability via an FO (more detail: 4) 5. Any application that can properly interpret elements of the FO should be able to properly and consistently interpret elements described as FOL combinations of those elements. 6. Therefore the computations performed by all applications using the FO should all arrive at the same inferences from the same data.  That is all one can demand for programs  that are intended to be interoperable. 7. If any procedural code is used locally that manipulates the data other than for input output or presentation, there may be a risk of misinterpretation.  The local programmers need to be aware of the risk, and avoid misuse of the data so as to change its intended meaning.

45. Semantic Interoperability via an FO (more detail: 5) 8. For information not transmitted to other systems, of course local systems have complete freedom to use them as they consider optimal.  It is only the information transmitted to other systems that has to be interpretable by means of the FO specification. 9. Recall that the FO will be able to have procedural code labeled as functions.  Any systems that require procedural code for proper interpretation of transmitted data, that is not adequately mimicked by FOL, can add it as a primitive function to the FO or to a domain extension ontology used within some community. 10.  The FO, in order to accommodate newly mapped systems that require new primitives, should have an expeditious procedure for rapidly adding new primitives, after review by the technical committed agrees that the new element is not FOL specifiable using existing FO ontelms, and is not redundant or logically contradictory to the existing FO.

46. Semantic Interoperability via an FO (more detail: 6) Potential issues (1):  There is one potential problem in he manner o f using newly specified ontology elements required to interpret transmitted information. I may not always be possible to recognize when the intended meanings of elements in separately developed domain ontologies are identical.  Since the FO allows alternate structures to represent the same meanings, but has  translation axioms among them , the various alternatives can in principle be calculated and compared for identity.   But unless the system can develop some normal form into which all elements can be converted, identical meanings may not always be recognized as such.  It will have to be investigated by the FO consortium whether it is possible to develop a normal form for the FO, or if not, whether failure to recognize identity would have significant negative effects. 

47. Semantic Interoperability via an FO (more detail: 7) Potential issues (2): An additional issue is whether newly added axioms could change the interpretations of existing FO ontelms.   To minimize that potential, it would seem important to try to identify all axioms necessary to specify the intended meanings of the FO primitives as fully as possible at the earliest stage, so that few if any need to be added after the initial shake-down period of a few years.  Additions of new subtypes or relations that are only conservative extensions of the FO may not be problematic in the same way. For stability, it is important that the intended meanings of FO ontelms remains constant, so that the logical interpretations of elements does not change over time. When elements representing new concepts are needed, they are added to the FO or some extension. Extensions should not create any logical conflict with the FO. Systems that have local data or local ontology extensions may derive additional inferences from the same data, but these should not be logically contradictory to those derivable by other systems.

48. Other Advantages of the Common FO • The FOL rules that can be created within a domain ontology can represent not only the data combining operations that are performed in procedural programming, but can also implement checking for consistency and accuracy of the input and results. • If some procedural code is nevertheless required for local data processing, the use of an FO will still reduce the number of data elements that need to be interpreted carefully and processed according to the common interpretation; as a result, the chance of inadvertently using an interpretation different from that used by others will be reduced. • Procedural code that is useful for more than a few local uses, if representable as a function, may be included in the FO or a mid-level extension as a new primitive element.

49. The Integrating Function of the Foundation Ontology Foundation Ontology GenericObligation Domain Ontology 2 Domain Ontology 1 SameAs SameAs Obligation Duty

50. The Ontology for Integrating Databases Foundation Ontology (FO) Provides defining concepts to specify conceptual message Content Knowledge Base uses FO For Definitions Database Translating Interfaces Patient Data Customers Inventory Commercial Products Regulations Intelligence General Knowledge Data Collection Interfaces