Traditional, semantic, and hypersemantic approaches to data modeling

Potter, Walter D.; Trueblood, Robert P.

doi:10.1109/2.950

Cited by 52 publications

(13 citation statements)

References 6 publications

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“…Work in the fi eld of semantic data modelling (Hull and King 1987 ;Peckham and Maryanski 1988 ;Potter and Trueblood 1988 ) , ontologies (Leppänen 2005 ) and semantic networks (Findler 1979 ) has lead to the identi fi cation of four standard hierarchical relations:…”

Section: Standard Hierarchical Abstraction Mechanismsmentioning

confidence: 99%

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Model-Based Development and Evolution of Information Systems

Krogstie¹

2012

126

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Section: Standard Hierarchical Abstraction Mechanismsmentioning

confidence: 99%

“…The four constructs have the following de fi nitions, going back to the de fi nitions provided in Potter and Trueblood ( 1988 ) :…”

Section: Standard Hierarchical Abstraction Mechanismsmentioning

confidence: 99%

Model-Based Development and Evolution of Information Systems

Krogstie¹

2012

126

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“…In addition to these two elements, a semantic net type semantic data model has constructs for high-level application domain concepts, and rules that govern the description of the domain concepts [Potter and Trueblood 1988;Parsaye et al 1989;Schnase et al 1993]. The semantic data model of the structured hypertext H s is defined as…”

Section: Semantic Net Representationmentioning

confidence: 99%

Structured hypertext with domain semantics

Wang¹,

Rada

1998

ACM Trans. Inf. Syst.

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One important facet of current hypertext research involves using knowledge-based techniques to develop and maintain document structures. A semantic net is one such technique. However, most semantic-net-based hypertext systems leave the linking consistency of the net to individual users. Users without guidance may accidentally introduce structural and relational inconsistencies in the semantic nets. The relational inconsistency hinders the creation of domain information models. The structural inconsistency leads to unstable documents, especially when a document is composed by computation with traversal algorithms. This work tackles the above problems by integrating logical structure and domain semantics into a semantic net. A semantic-net-based structured-hypertext model has been formalized. The model preserves structural and relational consistency after changes to the semantic net. The hypertext system (RICH) based on this model has been implemented and tested. The RICH system can define and enforce a set of rules to maintain the integrity of the semantic net and provide particular support for creating multihierarchies with the reuse of existing contents and structures. Users have found such flexible but enforceable semantics to be helpful.

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“…Procedural aspects rarely are, and instead are encoded as software with certain branching point values (parameters) possibly defined as data. Semantic, hypersemantic, object-oriented, and functional conceptual data modeling approaches are evolving to represent "business knowledge" such as heuristic rules and temporal characteristics of objects as data [7,10]. We agree that far more information about a system can usefully be represented in data rather than in software, but believe there is a fundamental need to identify new conceptual structures that are more stable than objects, relationships, rules, or processes and are therefote mote appropriate as the basis for lepresenting and comprehenditig complex systems.…”

mentioning

confidence: 99%

Ultra-structure

Long

Denning

1995

Commun. ACM

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he physicist and Nobel laureate Ilya Prigogine states that "our understanditig of nature is undetgoitig a tadical change towatd the multiple, the temporal, and the complex. Curiously, the itnexpected complexity f'oitnd in nature has not led to a slowdown in the progress of science, but on the contrary to the emergence of new conceptual structures that now appear as essential to our understanding of the physical world" [11]. We believe the challenges posed by complex systems arise primarily from the use of conceptual structures that wotked well for static systems but do not work as well for more dynamic systems. We therefore propose new conceptual structures based on a different metaphysical view of the nature of complex systems.In this article we use the word system to denote a system in the t eal world (for example, a corporation, a biological system, a legal system), and application to denote the representation of a system. Object and entity are used interchangeably, and may refer to an object, classifications of objects, or relatiotiships between objects.Current approaches to complexity presume an ontology of objects and relationships, sometimes explicitly including processes and, in science, sometimes explicitly including observers. They reptesent these in various ways. Objects and their relationships are usually declared in data. Procedural aspects rarely are, and instead are encoded as software with certain branching point values (parameters) possibly defined as data. Semantic, hypersemantic, object-oriented, and functional conceptual data modeling approaches are evolving to represent "business knowledge" such as heuristic rules and temporal characteristics of objects as data [7,10]. We agree that far more information about a system can usefully be represented in data rather than in software, but believe there is a fundamental need to identify new conceptual structures that are more stable than objects, relationships, rules, or processes and are therefote mote appropriate as the basis for lepresenting and comprehenditig complex systems.Ultra-Structure is a general theory regarding the improved representation of complex rules. It was originally derived from the linguist Noam Chomsky's work on transfortiiational grammar. In applying Chomsky's theory over the past nine years to businesses and other complex systems, we have substantially modified his theory. Ultra-Structure is based oti two key hypotheses:1) The Ruleform Hypothesis: Complex system structures and behaviors are generated by not-necessarily-complex processes; these processes are generated by the animation of operating rules. Operating rules can be grouped into a small number of classes, whose form is prescribed by ruleforms. While the operating rules of a system change over time, the ruleforms remain constant, A well-designed collection of ruleforms can anticipate all logically possible operating rules th^ir coMMUHlCATiails ov THI ACM |aiuiarv 199.'i/Vnl..1H. No. I 103

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Traditional, semantic, and hypersemantic approaches to data modeling

Cited by 52 publications

References 6 publications

Model-Based Development and Evolution of Information Systems

Model-Based Development and Evolution of Information Systems

Structured hypertext with domain semantics

Ultra-structure

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