=Paper=
{{Paper
|id=Vol-2293/paos2018-passcr2018_paper7
|storemode=property
|title=
Knowledge Graph Considered Harmful for Ontology
|pdfUrl=https://ceur-ws.org/Vol-2293/paos2018-passcr2018_paper7.pdf
|volume=Vol-2293
|authors=Seiji Koide
|dblpUrl=https://dblp.org/rec/conf/jist/Koide18
}}
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Knowledge Graph Considered Harmful for Ontology
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Knowledge Graph Considered Harmful for Ontology Seiji Koide1 Ontolonomy, LLC., Minami-ku Yokohama 232-0066, Japan, koide@ontolonomy.co.jp, WWW home page: http://ontolonomy.co.jp/ Abstract. The time of knowledge graph has come. Linked Data is now rephrased to knowledge graph, and no one has doubt on the future of it. However, will the time of ontology come in the next step? There exists a long history of ontology ever since the ancient Greece, and now the terminology has become popular with the advent of OWL. Nevertheless, the ontology does not seem to happen so as Linked Data did. There is a serious gap on the semantic representation between the ontology and the knowledge graph, and the gap originates semantic networks. In this paper, we pursue the history of knowledge representation, point out the serious semantic gap contained in knowledge graph. We propose an al- ternative representation language for ontological knowledge in Semantic Webs. Keywords: New KM, RDF, OWL, knowledge graph, knowledge repre- sentation, Frame-based, Case-based 1 Introduction The purpose of this essay is to cause a stir in the community of Semantics Webs just as Dijkstra did in software engineering.1 It seems that the time of Linked Open Data (LOD) has come. Ones have become to rephrase “Linked Data” to “knowledge graph”, since knowledge graph has been used as technical terminology in the domain of semantic search by Google, IBM, etc.. Because the both is roughly the same technology from the technical viewpoint. On the other hand, the term of “ontology” exists ever since the age of ancient Greece, and the engineering of ontologies has been pursued since 1970s as a part of computer science and Artificial Intelligence, then it has become popular today with OWL. However, we have yet a serious gap between the representation of knowledge graph and ontology. More precisely, we have theoretical, practical, and socio- technological difficulties such as how to understand the subsumption concept described in RDF Semantics [2] with respect to the ambiguous IS-A concept [3, 4], how to represent structural link [3, 5] in the form of knowledge graph, and how to discriminate the notion of class and individual in human mind. 1 See, https://en.wikipedia.org/wiki/Considered_harmful The following is a fallible example which novices easily fall into erros.2 Wine a owl:Class ; rdfs:subClassOf food:PotableLiquid ; *madeFromGrape WineGrape . Instead, it should be exactly coded in turtle as follows. Wine a owl:Class ; rdfs:subClassOf food:PotableLiquid , [ a owl:Restriction ; owl:onProperty madeFromGrape ; owl:allValuesFrom WineGrape ] . The cause of this mistake is three fold; firstly, the abstract syntax of RDF (namely RDF graph) does not fit to the description of ontologies; secondly, it it hard to understand the concept of subsumption and property inheritance; thirdly, most people are sluggish to study hard, some one tends to take an easier way even if it is impossible to reach the final goal. Contrary to the error sentence mentioned above, the following code is com- pletely correct with respect to individuals. ElyseZinfundel a Zinfundel ; hasMaker Elyse ; hasSugar Dry. In this case, Zinfundel is a class, but ElyseZinfundel, Elyse, and Dry are individuals. There is no inheritance on properties. Actually, at the error case shown above, it should be coded with the meanings that every wine (as instance) is made from some wine-grape (as instance), and it must be described at the class level on wine. Otherwise, it is forced to describe the property values on every instances. It should be here noticed that Wine and WineGrape are classes. Such a kind of problems was involved in the beginning of semantic networks. Woods [3] pointed out the semantical ambiguity of network links and introduced the distinction of assertional link and structural link. At the final step of KL-ONE family, Clark developed a knowledge representation language, KM (Knowledge Machine) [9, 10]. According to the style in KM-like representation, the error sentence mentioned above may be paraphrased into the followings. Wine is a owl:Class and rdfs:subClassOf food:PotableLiquid . every Wine is madeFromGrape a WineGrape . Note that these sentences are not English, rather an artificial knowledge repre- sentation language. It is a sort of syntax sugar of the turtle syntax and preserves 2 This example is taken from Wine Ontology [6], and where an asterisk is attached to the head of wrong lines. RDF and OWL semantics. We can translate KM-like sentences into turtle sen- tences, just as turtle sentences can be translated into RDF/XML format without the loss of information. It is conceived that Description Logics inherited the heritage of semantic networks and frame systems [4]. In fact, many features of KL-ONE family came into OWL. In this paper, we pursue the history of knowledge representation, specifically focusing on the development of class notion and subsumption con- cept, then point out the problem of knowledge graph representation for OWL. Finally, we propose a new representation language, the New KM, a successor of KM by Clark and SWCLOS (Semantic Web processor on top of Common Lisp Object System) [11, 12]. The rest of this paper is organized as follows. In section 2, we present a brief history of the knowledge representation on semantic networks and frame systems, focusing on class-instance notions and the inheritance concept. section 3 presents an idea of New KM, which is a unified successor of KM by Clark and our own Semantic Web Processor, SWCLOS. Finally, we conclude some remarks and the future work. 2 Historical Views on Knowledge Representation 2.1 Semantic Networks to Description Logic and OWL The study of semantic networks was started as an associative link network at 1966 by Quillian’s work [7, 8], for the purpose of making artificial memory for words and meanings. At the time, such an associative link structure was taken as a firm base in modeling human memory. However, many problems that were in- volved in such simple networks were soon exposed by many researchers.3 Human epistemology is more complex than the association. Woods [3] analyzed the semantics of semantic networks and introduced the distinction between structural links, which present propositional statements on things, and assertional links on assertional relation among things. He addressed the following network structure. N12368 SUPERC TELEPHONE MOD BLACK The meanings of this sentence may be interpreted in two ways. In OWL, it would be written distinctively as follows, into a proposition in TBox (left side) or an assertion in ABox (right side). N12368 N12368 a TELEPHONE ; owl:intersectionOf hasColor BLACK . ( TELEPHONE 3 The original by Quillian was not so simple as the successors. The original had devices of type, token, plane, and notions of class, subclass, and modification. [13] [ a owl:Restriction ; owl:onProperty hasColor ; owl:hasValue BLACK ] ) . The former insists the class of black-colored telephone, but the latter asserts the existence of a telephone whose color is accidentally black. On the idea that the notation must be specified more precisely, he started the discussion on the problem involved in semantic networks. However, the issues, in the viewpoints at the present, were confused and spread out widely in distinct levels, from semantics to pragmatics, from denotational levels to logical levels. Up to the mid of 1970s, semantic networks constitute the primer knowl- edge representation and many attempts revealed that they never lived up to researcher’s expectations. Brackman [13] demonstrated complex semantic net- works that contain both conceptual networks and their particulars, and showed special existences a set of links that allows the specification of a concept as a set of attribute definitions in conjunction with a structural interrelation between those attributes, see details in [13]. At 1979, Brackman [14] presented a comprehensive survey on semantic net- works. He investigated the work by Quillian, Woods, Brackman, Collins, Car- bonell, Winston, expanding to Fillmore, Simmons, Hendrix, Rumelhart, Schank, Heidom, Anderson, Shapiro, Cercone, Phillip Hayes, Norman, and Szolovits, then clarified five levels of characteristics on semantic networks, “implementational,” “logical,” “epistemological,” “conceptual,” and “linguistic” levels. Due to limita- tions of space, we summarize the result at Table 1. Note that we can capture that Table 1. Characteristics Levels of Semantic Networks Level Primitives description Implementational atoms, pointers A Link is a pointer and a node is a destination. Logical propositions, predicates, Logical primitives with a structured logical operators index like AND, SUBSET, EXISTS Epistemological concept types, subpieces, Formal structure of conceptual units inheritance, and interrelationships as them. structuring relations Independent of any knowledge edge Conceptual semantic relations, Language-independent conceptual primitive objects and actions primitives and case structure. Linguistic arbitrary concepts, words, Networks whose primitives expressions are language-specific. RDFS and OWL fall into epistemological level, which was discovered by Brack- man as a missing level in his comprehensive investigation. Usual ontologies that are built using RDFS and OWL are at conceptual level. As an instantiation of such an epistemological level, he advocated more elaborated “Structured Inher- itance Networks”, in which Role/Filler Description and Structural Description are derived. Eventually, Brackman [15] published KL-ONE at 1985, and after that many KL-ONE-ish systems succeeded. They are, as a whole, called KL-ONE family. All systems of KL-ONE family, except KM [9, 10] is listed at [16]. The class-instance notion gradually emerged in the development of KL- ONE family. In the original KL-ONE, the notion of class was the produc- tion of a classifier, and did not provide any explicit primitives for the class- instance indication. This situation is carried over Description Logics and OWL. In CLASSIC [17], the operators for individuals were identical to that for classes, but the function cl-create-ind was provided to create an individual under a CLASSIC-description. Moreover, LOOM [18] prepared 17 operators (func- tions/macros/slots) for instances. Ideas of objects and mixin classes were bor- rowed from CLOS (Common Lisp Object System) and provided the mixin- inheritance functionality. KM [9, 10] is, which is not regarded so, the last system in the line of KL-ONE family in thought. It has a frame-like syntax as well as CLASSIC and LOOM. However, it presented an easier way to encode the inheritance attributes for instances at classes. The following is actual programming code in KM of Buy event. (every Buy has (buyer ((a Agent))) (object ((a Thing))) (seller ((a Agent))) (money ((the cost of (the object of Self)))) (subevent1 ((a Give with (agent ((the buyer of Self))) (object ((the money of Self))) (rcpt ((the seller of Self)))))) (subevent2 ((a Give with (agent ((the seller of Self))) (object ((the object of Self))) (rcpt ((the buyer of Self))))))) This code axiomatize that two agents appear as buyer and seller, every event of Buy is accompanied by two distinctive Give events in which one event for a buyer the money is received by the buyer, in the other event for a seller the object is received by seller. In the above example, the event money is instantiated as the cost of the event. KM denotes two fundamental types, instances and classes. A class has the extension of the individuals, and properties of individuals of a class are expressed of the form: (everyhas ( ( ... )) ( ( ... )) ... ) Thus, “(every ...” form describes properties for individuals of a class to be inherited in accordance with superclass-subclass relation. On the other hand, the form without “every” but with “superclasses” attribute for classes denotes superclasses of a subjective class with other properties for the class per se. ( has (superclasses ( ... )) ( ( ... )) ( ( ... )) ... ) This grammar greatly reduces the burden of awkward expression in knowledge graph. We propose such a grammar for RDF and OWL in Section 3. 2.2 Frames to RDFS Minsky [19] published the idea of framework of human cognitive mechanisms at 1974. We can think of a frame as a network of nodes and relations. The top levels of a frame are fixed, and represent things that are always true about the supposed situation. The lower levels have many terminals – slots that must be filled by specific instances or data. [. . . ] Collections of related frames are linked together into frame-systems. The effects of important actions are mirrored by transformations between the frames of a system. [Minskey, 1974] As Minsky mentioned in his paper, the basic idea of frame is not his invention and his presentation was not complete, but he pointed out several important notions of frame systems such as sharing terminals, a frame and subframes, variables, attachments, default assignment, and so on. He talked the image of frame-based cognition in many scenes, vision, linguistics, memory acquisition, retrieval of knowledge, and control. Minsky’s prevision had become the source of many frame systems after that. KRL and FRL were the first two systems embodied Minsky’s idea. Espe- cially, Bobrow’s KRL[20] gave some inspiration to KL-ONE family, where the appearance of network disappeared and frame-like forms, e.g., UNIT, appeared. The followings are an example of event description described in KRL. [Event234 UNIT Individual ] [Give UNIT Specialization