98 lines
4.5 KiB
Markdown
98 lines
4.5 KiB
Markdown
file:: [MODELS23-DS_paper_18_1690904320624_0.pdf](../assets/MODELS23-DS_paper_18_1690904320624_0.pdf)
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file-path:: ../assets/MODELS23-DS_paper_18_1690904320624_0.pdf
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- that semantic and structure design
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id:: 64ddab3c-57e5-46b0-a7cd-0e0c5d2e9bf3
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- We propose a robust framework on which tools will be built to support and ease the development and management of data specifications mapped to semantically or structurally richer models and keep them consistent through evolution
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hl-color:: purple
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id:: 64ddab6c-2221-4765-b1f4-17df4238a054
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- The structure determines how the data are represented, whereas semantics defines meaning and how the concepts should be interpreted
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hl-page:: 1
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hl-color:: green
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id:: 64ddadaf-bf8e-4894-8f50-98540825060e
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- In the case of small domains, the data itself can implicitly describe its structure, and the structure can describe the semantics if the person knows the domain well.
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hl-page:: 1
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hl-color:: green
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id:: 64ddadcc-2bea-460c-b3d4-e012835712d8
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- The whole package describing the data will then be called the data specification.
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hl-page:: 1
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id:: 64ddae06-b592-468b-96de-1fba81713ad6
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- Some domains may benefit from additional documents, such as application skeletons, API specifications, tests, etc
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hl-page:: 1
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hl-color:: blue
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id:: 64ddae4c-c1dc-4022-847a-02a40ac5a92b
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- he latter task can be handled by numerous tools automatically generating various documents. For the first task, numerous tools have emerged, t
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ls-type:: annotation
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hl-page:: 1
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hl-color:: yellow
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id:: 64ddae83-6a2d-4a23-b3cf-4abde651a529
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- The lack of separation often results in poor-quality conceptual models that do not reflect reality.
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id:: 64ddaed3-fe8d-4153-ab5b-73559e084775
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- semantic mode
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id:: 64ddaf04-bba4-4071-ac2e-9da1a9b3678c
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- J. Peckham and F. Maryanski, “Semantic data models,” ACM Computing Surveys (CSUR), vol. 20, no. 3, pp. 153–189, 1988
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hl-page:: 6
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hl-color:: green
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id:: 64ddaf0e-75d7-4bb8-926d-3e6fff2288d2
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- However, for mutual communication, it is necessary to ensure semantic mapping between shared concepts and mutual propagation of changes if the semantics of concepts in the domain change
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hl-page:: 2
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id:: 64ddafa2-f95f-4dad-bd87-ff7affa0ba2d
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- omain expert
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id:: 64ddafe8-d9a4-46ab-bc8f-abb1d6a52b77
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- Designing a data specification in larger domains is not just designing a simple data schema or semantic model.
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hl-page:: 2
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hl-color:: green
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id:: 64ddb337-9e49-434f-8854-eb49b7478af1
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- What is needed is a tool that allows users, when designing their data specifications, to build on existing semantic and structural models, reuse them, combine and modify them, and ultimately derive data structure models from them, if necessary, tied to the original semantics, but without constraining them in any way. Managing all this manually is hard. The tool will make it easier by automating as many steps as possible, managing the dependencies between models and their elements, and through these dependencies, also supporting propagation.
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hl-page:: 2
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id:: 64ddb367-8c64-4ba7-a35a-26fc4b69317d
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- Research question: Is it feasible to design a framework and build a set of tools on it for the management of semantic and structural models, which would be practically applicable and lead to an improvement in the process of data specifications development?
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id:: 64ddb3ce-e11d-435b-95c0-d06527073156
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- hange propagation
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hl-page:: 3
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id:: 64ddb454-4612-455a-a183-7d67bdecd5bb
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- model derivation from more general models,
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hl-page:: 3
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hl-color:: green
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id:: 64ddb45d-fdb3-449f-b968-4cad2a483df9
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- model management
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id:: 64ddb468-29f3-4e1e-bf2b-56f20244d72b
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- Proposed decomposition of the project into logical units with a generic framework on which semantic modeling and schema modeling tools will be built
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hl-page:: 3
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id:: 64ddb4d0-f96b-4742-abf8-79f87b39228c |