Peter D. Karp, "The design space of frame knowledge representation systems", Technical Report 520, SRI International AI Center, 1992.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....information structures in multiple ways as unary, binary, as well as n ary facts. It has a sophisticated object type system that distinguishes between representations of lexical and non lexical objects, and has strict is a relationships with clean multiple inheritance as in frame systems ([PK92]) ORM has an a priori given set of static and certain dynamic constraint types and derivation rules that turned out to be suitable and expressive enough to cover a significant part of the needs emerging from enterprise modeling. Such constraints and rules include classical ones such as uniqueness ....

Peter D. Karp, "The design space of frame knowledge representation systems", Technical Report 520, SRI International AI Center, 1992.

....that only partially overlap. In order to allow more flexible variations we have to investigate the design space of ontology languages. There are many options to be taken into account. We could rely on previous work on comparing frame based and terminological knowledge representation systems [Karp, 1993; Heinsohn et al. 1994] As our concerns are rather application driven than of a theoretical nature, we have to abstract from the technical details of the languages that are mainly concerned in the work mentioned above. We therefore concentrate on the following questions: What kinds of ....

Peter D. Karp. The design space of frame knowledge representation systems. Technical Note 520, AI Center SRI International, May 5 1993.

....how large KBs should be supported. At the leaves of the class hierarchy are the instances of each concept, which represent the actual facts reported in the literature. There are many other possible choices for the KB framework, and the choice is somewhat arbitrary at this prototyping stage [16]. The ONTOLINGUA KB always has the object Thing at the root. We define five major subclasses of concepts for our KB. The first three subclasses organize how we think about the physical objects involved in the domain, and the next two organize how we think about data and publications. 1. We ....

Karp, P.D., The design space of frame knowledge representation systems, . 1992, SRI International Artificial Intelligence Center.

....the introduction of axioms and constraints that are currently missing in the ontologies. Key words : frame based system, knowledge acquisition, knowledge representation 1. AXIOMS IN FRAME BASED SYSTEMS Frame based representation systems (FRS) are a popular choice for knowledge representation [6]; their taxonomic categorization of canonical concepts often bears close resemblance to the way humans describe knowledge and is easy to understand. Because of this cognitive simplicity, FRSs serve as effic ient tools for knowledge representation and acquisition. Even though ....

Karp, P.D., The design space of frame knowledge representation systems, SRI AI Center: Menlo Park, CA, 1993.

....schema that captures the hierarchical nature of biological concepts. For our initial prototype, we built a knowledge representation tool called VKB (Virtual Knowledge Base) using the PERL language. VKB is a frame based knowledge representation system similar to CLIPS, CLASSIC or ONTOLINGUA [9] that allows us to define a schema of concepts and their attribute names and types. Most entries in the knowledge base are instances of these objects associated with specific attribute values. VKB can be accessed in read write mode both through direct procedure calls and through a webaccessible ....

Karp, P.D., The design space of frame knowledge representation systems, 1992, SRI International Artificial Intelligence Center.

....the best features of existing ontology toolkits in order to provide a simple, powerful and yet broadly usable tool. Ontology Builder uses a frame based representation based on the OKBC Knowledge Model [3] OKBC was developed recognizing the wide general acceptance of frame based systems [13] and provides an API (Applications Programming Interface) for frame like systems. Written entirely in Java, Ontology Builder can run on multiple platforms. It is based on the J2EE (Java 2 Enterprise Edition) platform (http: java.sun.com j2ee) which is a standard for implementing and deploying ....

Peter D. Karp, "The design space of frame knowledge representation systems", Technical Report 520, SRI International AI Center, 1992.

....us to represent, without modi cation, HTML and XML documents, data in Stanford s OEM format, plain text and database relations. Furthermore, it is rich enough to model more complex relationships such as inheritance, and typing. This expressiveness allows it to simulate UML (Fowler 1998) and frame (Karp 1992) models. In this section we have presented the foundations necessary in order to present the use of the algebra in the creation and maintenance of an application speci c ontology. In the next section, we describe the dictionary ontology, as well as how to create and re ne it. We focus on one ....

Karp, P. D. 1992. The design space of frame knowledge representation systems. Technical report, SRI International Articial Intelligence Center.

....and co operation accordingly. This is illustrated through the design of a new implementation of the TROPES system. 1. WHY ARE OOL AND OBKR DIFFERENT There have been several works on the many possible OOL and OBKR based on the remark that OOL and OBKR are very similar at a conceptual level [16, 11, 12, 24, 4]. As a matter of fact, involved concepts include individual entities (hereby called objects) to which attributes are assigned, and generic entities (called classes) describing the structure of individual objects and organised through a relation (called specialisation) A possible source of ....

Peter Karp, The design space of frame knowledge representation systems, Technical note 520, SRI AI center, Menlo Park (CA US), 1993

.... ( concept filter 0 2) part of hierarchy is a hierarchy Plant Filter Basins Machine Figure 1: Parts of the domain structure of AMS This knowledge enables us to model the structure of the domain via is a and part of relations as in frame knowledge representation systems like KL ONE or KEE [5] 11 . With this kind of structure we can for example represent the fact that a milling machine is a kind of a machining tool, or that a pressure lter is a kind of lter. With the part of relation we can describe that a manufacturing plant has, among other, some basins for the cutting AEuid, ....

....is provided by the domain structure, in that we can generalize within the is a or part of hierarchy. The approach is best described by the rough de nition that similarity is equality on a more abstract (or general) level and corresponds to the set theoretic semantic of concepts in KL ONE [5]. This can overcome the limitation of AEat feature vectors when determining for example, that Relais 1 and Relais 2 are syntactically dioeerent attributes, but have semantically the same function in functionally and structural identical subparts of a machine [8] The speci cation of a ....

Peter D. Karp. The design space of frame knowledge representation systems. SRI AI Center Technical Note 520, SRI International, 1993.

....attributes. In the scenario described in Section 1 8 there is knowledge about the structure of the domain, i.e. about machines, plants or products to be supported. This knowledge enables us to model the structure of the domain as in frame knowledge representation systems like KL ONE or KEE [Kar93] 9 . 5.1 Concepts For example there is knowledge about the fact, that a milling machine is a special kind of machine or a pressure lter is a variant of a lter (see Figure 2) On the other side there is knowledge about the structure of the machines, for example that a manufacturing plant has, ....

....is provided by the domain structure, in that we can generalize within the is a or part of hierarchy. The approach is best described by the rough de nition that similarity is equality on a more abstract (or general) level and corresponds to the set theoretic semantic of concepts in KL ONE [Kar93] This 17 Note that this not necessary implies that the data entered conforms to a coherent time interval of the plant history, cause certain information about plant are gathered later than others etc. 18 Because some of the comparing relations are no equivalence relations (e.g. they are not ....

Peter D. Karp. The design space of frame knowledge representation systems. SRI AI Center Technical Note 520, SRI International, 1993.

....the single attributes. In the scenario described in 2.1 16 there is knowledge about the structure of the domain, i.e. about machines, plants or products to be supported. This knowledge enables us to model the structure of the domain as in frame knowledge representation systems like KL ONE or KEE[4] 17 . 13 concepts and instances as well as cases and protocols 14 including the most commercially available 15 We assume a certain familiarity with CBR, therefore the reader is referred to [9, 5, 1] for papers describing the state of the art in CBR. 16 and generally in the field of ....

....is provided by the domain structure, in that we can generalize within the is a or part of hierarchy. The approach is best described by the rough definition that similarity is equality on a more abstract (or general) level and corresponds to the set theoretic semantic of concepts in KL ONE[4]. This can overcome the limitation of flat feature vectors when determining for example, that Relais 1 and Relais 2 are syntactically different attributes, but have semantically the same function in functionally and structural identical subparts of a machine[7] The specification of a ....

Peter D. Karp. The design space of frame knowledge representation systems. SRI AI Center Technical Note 520, SRI International, 1993.

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Karp,P.D. (1992) The design space of frame knowledge representation systems. SRI International Artificial Intelligence Center.

....representation systems. The authors believed that any evaluation of languages for the exchange of ontologies must include this project. The semantics of Ontolingua are based on the frame knowledge representation systems developed by knowledge representation researchers (Fikes and Kehler 1985)(Karp 1992). CycL. Cyc is perhaps the best known of the knowledge representation systems and is significant in its scope and its longevity. Cyc was developed by Doug Lenat at MCC but has since spun off as a commercial entity, Cycorp. The underlying representation language for Cyc is called CycL, which ....

Karp, P.D. 1992. The design space of frame knowledge representation systems, SRI International AI Center, #520, URL ftp://www.ai.sri.com/pub/papers/ karp-freview.ps.Z.

....are the relational model used by relational DBMSs, and the object model that underlies object oriented DBMSs. Frame knowledge representation systems (FRSs) are an information management technology developed in the Artificial Intelligence community that use a variant of the object data model (Karp, 1992). The EcoCyc data are encoded within an FRS called OCELOT (Karp and Paley, 1996; Karp et al. In FRS terminology, objects are called frames. Frames come in two varieties: classes and instances. Class frames represent generic types of objects, such as the class of all genes and the class of all ....

Karp, P. (1992). The design space of frame knowledge representation systems. Technical Report 520, SRI International AI Center. URL ftp://www.ai.sri.com/pub/papers/karp-freview.ps.Z.

....of the GKB Editor is the ongoing use of the GKB Editor to edit real world KBs for OCELOT and LOOM. These two FRSs lie at fairly opposite ends of the FRS spectrum: LOOM is a KL ONE descendant that supports classification. OCELOT is in the UNIT Package family of FRSs, along with KEE, CYCL, and THEO (Karp 1992). It does not perform classification all class subclass and class instance relationships are specified by the user. It does support facets (both built in facets such as value type and cardinality, and user specified facets) and annotations, which LOOM does not. OCELOT supports multiple ....

Karp, P. 1992. The design space of frame knowledge representation systems. Technical Report 520, SRI International AI Center. URL ftp://www.ai.sri.com/pub/papers/ karp-freview.ps.Z.

....in this paper was done while the first and the third authors were at SRI International. i 1 Introduction Collaborative knowledge base (KB) authoring environments allow multiple, geographically distributed users to collaborate in the development of large KBs. The first generation of FRSs (Karp 1992) provided only single user KB authoring environments whose engineering limitations constrained the size of the resulting KBs, and did not permit distributed KB access. This report describes a next generation, reusable environment for collaborative KB authoring that consists of the following ....

....4 FRS from its model. Another example of conflicts among our objectives is that to precisely specify the semantics of the GFP function that retrieves the values for a frame slot, we must specify the inheritance semantics to be used. However, different FRSs use different inheritance mechanisms (Karp 1992). Conformance with a specific semantics for inheritance would require either altering the inheritance mechanism of a given FRS (violating the nolegislation goal) or emulating the desired inheritance mechanism within the implementation of the protocol (violating performance and generality, since ....

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Karp, P. 1992. The design space of frame knowledge representation systems. Technical Report 520, SRI International, Artificial Intelligence Center. URL ftp://www.ai.sri.com/pub/papers/ karp-freview.ps.Z.

....of enhancement in OKBC: expanding the range of supported KRSs, and expanding the range of supported applications. We also discuss practical experiences in using OKBC. The OKBC Knowledge Model The OKBC knowledge model is designed to include representational features supported by several KRSs (Karp 1992). It includes constants, frames, slots, facets, classes, individuals, and knowledge bases. Classes and individuals form two disjoint partitions of a KB (see Figure 1) A class is defined as a set of entities. Each of the entities in a class is said to be an instance of that class. An individual is ....

Karp, P. 1992. The Design Space of Frame Knowledge Representation Systems. Technical Report 520, SRI International Artificial Intelligence Center.

....units of measurement. An ontology is a logical theory which gives an explicit, partial account of a conceptualization (Guarino and Giaretta, 1995) That logical theory must make use of a data model such as the object oriented model, the entity relationship model (Chen, 1976) or the frame model (Karp, 1992). 4 Two DB designers who happen to choose the same conceptualization may choose to express it using different data models (such as entity relationship versus object oriented) Or, they may choose different variants of the same model, such as the OPM (Chen and Markowitz, 1995) or Gemstone variant ....

Karp, P. (1992). The design space of frame knowledge representation systems. Technical Report 520, SRI International AI Center. URL ftp://www.ai.sri.com/pub/papers/ karp-freview.ps.Z.

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Peter D. Karp, "The design space of frame knowledge representation systems", Technical Report 520, SRI International AI Center, 1992.

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Peter D. Karp, The design space of frame knowledge representation systems, SRI AI center, Technical report; 1993.

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P. D. Karp. 1993. The Design Space of Frame Knowledge Representation Systems. Technical Note 520, Artificial Intelligence Center, SRI International.

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Karp P.D. The Design Space of Frame Knowledge Representation Systems. SRI AI Center Technical Note #520, 1993.

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2. Karp, P. (1992). The design space of frame knowledge representations systems, SRI International.

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Peter D. Karp: "The design space of frame knowledge representation systems", Technical Report 520, SRI International AI Center, 1992

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P. D. Karp, The Design Space of Frame Knowledge Representation Systems, Tech. Report 520, SRI Int'l Artificial Intelligence Center, Menlo Park, Calif., 1992.

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