scholarly journals Phenotypes in insect biodiversity research

2015 ◽  
Author(s):  
Andrew R Deans ◽  
Istvan Miko
Keyword(s):  
Semantic Representation ◽  
Real Data ◽  
Comparative Morphology ◽  
Biodiversity Research ◽  
Representation Systems ◽  
Ontology Language ◽  
Insect Biodiversity ◽  
Phenotype Data ◽  
Multiple Domains ◽  
Knowledge Representation Systems

Recent advances in Web technology and information sciences, especially the development of knowledge representation systems---ontology languages (Web Ontology Language) and syntaxes (Manchester syntax)---are now infiltrating the world of insect biodiversity research. Data generated from taxonomic revisions, comparative morphology studies, and other enterprises now have the potential to be shared broadly and to be computed across---i.e., they are rendered semantic---in order to address questions relevant to multiple domains in the life sciences. In this chapter we describe the philosophy behind these new tools, the mechanisms by which they operate, and the real and future benefits of the semantic representation of phenotype data (e.g., standardization of terminology). We provide examples using real data and describe some limitations of semantic phenotype annotations.

scholarly journals Semantic data mapping technology to solve semantic data problem on heterogeneity aspect

2017 ◽  
Vol 3 (3) ◽  
pp. 161 ◽  
Author(s):  
Arda Yunianta ◽  
Omar Mohammed Barukab ◽  
Norazah Yusof ◽  
Nataniel Dengen ◽  
Haviluddin Haviluddin ◽  
...  
Keyword(s):  
Real Data ◽  
Database Systems ◽  
Data Mapping ◽  
Semantic Data ◽  
Ontology Language ◽  
Data Problem ◽  
Mapping Technology ◽  
Application Data ◽  
Semantic Aspect ◽  
Mapping File

The diversity of applications developed with different programming languages, application/data architectures, database systems and representation of data/information leads to heterogeneity issues. One of the problem challenges in the problem of heterogeneity is about heterogeneity data in term of semantic aspect. The semantic aspect is about data that has the same name with different meaning or data that has a different name with the same meaning. The semantic data mapping process is the best solution in the current days to solve semantic data problem. There are many semantic data mapping technologies that have been used in recent years. This research aims to compare and analyze existing semantic data mapping technology using five criteria’s. After comparative and analytical process, this research provides recommendations of appropriate semantic data mapping technology based on several criteria’s. Furthermore, at the end of this research we apply the recommended semantic data mapping technology to be implemented with the real data in the specific application. The result of this research is the semantic data mapping file that contains all data structures in the application data source. This semantic data mapping file can be used to map, share and integrate with other semantic data mapping from other applications and can also be used to integrate with the ontology language.

scholarly journals Formal Definition and Modeling Language of Association-Oriented Database Metamodel (AssoBase)

2019 ◽  
Vol 06 (02) ◽  
pp. 91-145 ◽  
Author(s):  
Marek Krótkiewicz
Keyword(s):  
Semantic Knowledge ◽  
Modeling Language ◽  
Degree Programs ◽  
Graphical Modeling ◽  
Fully Integrated ◽  
Representation Systems ◽  
Key Features ◽  
Semantic Knowledge Base ◽  
Knowledge Representation Systems

The paper provides a concise discussion of the most important theoretical aspects of the Association-Oriented Database (AODB) Metamodel. Even though the model has been practically verified, the author has focused on its formal aspects and modeling language. The AODB Metamodel has been developed for the purposes of building the knowledge representation systems. Basically, such systems are structurally and functionally complex, hence they require advanced solutions to be applied for the purpose of data modeling. The modeling language enables designing database structures in the AODB Metamodel, taking into account various features of this database metamodel. The language in question is fully integrated and compatible with AODB Metamodel. It has been developed for the purposes of this metamodel, it operates with categories specific to it and, as such, it constitutes neither a version nor an extension of any of the existing languages. The second part of the paper provides the definition and discussion concerning the graphical modeling language — Association-Oriented Modeling Language (AML). The last section of the paper introduces the case-study that presents the key features of the metamodel, as well as the use of modeling language. The topics of presented examples comprise a simplified model of degree programs for universities and the model of Ontological Core, the main module of Semantic Knowledge Base (SKB).

Function Semantic Representation (FSR): A Rule-Based Ontology for Product Functions

2010 ◽  
Vol 10 (3) ◽  
Author(s):  
Seung-Cheol Yang ◽  
Lalit Patil ◽  
Debasish Dutta
Keyword(s):  
Semantic Web ◽  
Semantic Representation ◽  
Functional Model ◽  
Consistency Checking ◽  
Formal Representation ◽  
Rule Based ◽  
Modeling And Analysis ◽  
Ontology Language ◽  
Web Standards ◽  
Product Function

Defining or understanding a product in terms of its functions facilitates a wide variety of tasks such as design synthesis, modeling, and analysis. However, the lack of a semantically correct formal representation of product functions creates a barrier to their effective capture, exchange, and reuse. This paper presents Function Semantics Representation, a rule-based ontological formalism that is consistent with the Semantic Web standards to capture different components of a product function. In particular, the Semantic Web Rule Language is used to overcome limitations in using the basic Web Ontology Language ontology to explicitly capture advanced semantics essential to completely represent product functions. This enables support for an effective reasoning mechanism to develop and validate the product function (or functional model). We present examples that demonstrate consistency checking and the ability to retrieve functionally similar products from a repository.

Knowledge Extraction from Domain-Specific Documents

2017 ◽  
pp. 106-123
Author(s):  
Ram Kumar ◽  
Shailesh Jaloree ◽  
R. S. Thakur
Keyword(s):  
Knowledge Representation ◽  
Knowledge Base ◽  
Knowledge Bases ◽  
Domain Ontology ◽  
Knowledge Based Systems ◽  
Domain Specific ◽  
Knowledge Based ◽  
Representation Systems ◽  
Terminological Confusion ◽  
Knowledge Representation Systems

Knowledge-based systems have become widespread in modern years. Knowledge-base developers need to be able to share and reuse knowledge bases that they build. As a result, interoperability among different knowledge-representation systems is essential. Domain ontology seeks to reduce conceptual and terminological confusion among users who need to share various kind of information. This paper shows how these structures make it possible to bridge the gap between standard objects and Knowledge-based Systems.

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