scholarly journals Automation of the development of ontologies of scientific subject domains based on ontology design patterns

2021 ◽  
Vol 11 (4) ◽  
pp. 500-520
Author(s):  
Yu.A. Zagorulko ◽  
◽  
E.A. Sidorova ◽  
G.B. Zagorulko ◽  
I.R. Akhmadeeva ◽  
...  
Keyword(s):  
Design Patterns ◽  
Effective Means ◽  
Current Version ◽  
Ontology Design ◽  
Logical Modeling ◽  
Ontological Design ◽  
Number Of Publications ◽  
Scientific Subject ◽  
Frag Ments ◽  
Subject Domains

At present, ontologies are recognized as the most effective means of formalizing and systematizing knowledge and data in scientific subject domains (SSDs). However, the development of an ontology is a rather complicated and time-consuming process. All indications are that when developing SSDs ontologies, it is especially effective to use ontology design patterns (ODPs). This is due to the fact that the SSD ontology, as a rule, contains a large number of typical frag-ments, which are well described by the ODPs. In addition, due to the fact that the use of ODPs greatly facilitates the development of an SSD ontology, it is possible to involve experts in a modeled SSD not possessing the skills of onto-logical modeling. To obtain an ontology that adequately describes the SSD, it is necessary to process a huge number of publications relevant to the modeled SSD. It is possible to facilitate and accelerate the process of populating the ontolo-gy with information from such sources by using the lexical and syntactic patterns of ontological design. The paper pre-sents an approach to the automated development of SSDs ontologies based on a system of heterogeneous ODPs. This system includes both ODPs intended for ontology developers and lexical and syntactic patterns built on the basis of the above-mentioned types of the ODPs and the current version of the SSD ontology.

Approach to the Automated Development of Scientific Subject Domain Ontologies Based on Heterogeneous Ontology Design Patterns

2021 ◽  
pp. 248-263
Author(s):  
Yury Zagorulko ◽  
Elena Sidorova ◽  
Irina Akhmadeeva ◽  
Alexey Sery ◽  
Galina Zagorulko
Keyword(s):  
Design Patterns ◽  
Subject Domain ◽  
Ontology Design ◽  
Domain Ontologies ◽  
Scientific Subject

scholarly journals Approach to automatic population of ontologies of scientific subject domain using lexico-syntactic patterns

2021 ◽  
Vol 2099 (1) ◽  
pp. 012028
Author(s):  
Yu A Zagorulko ◽  
E A Sidorova ◽  
I R Akhmadeeva ◽  
A S Sery
Keyword(s):  
Design Patterns ◽  
Coreference Resolution ◽  
Subject Domain ◽  
Ontology Design ◽  
Ontology Population ◽  
Scientific Subject

Abstract This paper presents an approach to automatic population of ontologies of a scientific subject domain (SSD) using Lexico-Syntactic Patterns (LSPs) and a corpus of texts related to modeled domain. The main feature of this approach is that such patterns are automatically built based on Ontology Design Patterns of other types provided by the system for the automated development of SSD ontologies using heterogeneous Ontology Design Patterns. The implementation of the ontology population using constructed LSPs is described in detail. The results of the experiments on the SSD ontology population are presented. It is noted that there is a problem in establishing a subject of a relation when extracting facts. To address this problem, the authors are planning to employ the coreference resolution methods.

scholarly journals Pattern-based design applied to cultural heritage knowledge graphs

Semantic Web ◽  
2020 ◽  
pp. 1-45
Author(s):  
Valentina Anita Carriero ◽  
Aldo Gangemi ◽  
Maria Letizia Mancinelli ◽  
Andrea Giovanni Nuzzolese ◽  
Valentina Presutti ◽  
...  
Keyword(s):  
Cultural Heritage ◽  
Design Patterns ◽  
Lessons Learned ◽  
Knowledge Graph ◽  
Unit Testing ◽  
Domain Specific ◽  
Rigorous Testing ◽  
Ontology Design ◽  
Domain Specific Knowledge ◽  
Knowledge Graphs

Ontology Design Patterns (ODPs) have become an established and recognised practice for guaranteeing good quality ontology engineering. There are several ODP repositories where ODPs are shared as well as ontology design methodologies recommending their reuse. Performing rigorous testing is recommended as well for supporting ontology maintenance and validating the resulting resource against its motivating requirements. Nevertheless, it is less than straightforward to find guidelines on how to apply such methodologies for developing domain-specific knowledge graphs. ArCo is the knowledge graph of Italian Cultural Heritage and has been developed by using eXtreme Design (XD), an ODP- and test-driven methodology. During its development, XD has been adapted to the need of the CH domain e.g. gathering requirements from an open, diverse community of consumers, a new ODP has been defined and many have been specialised to address specific CH requirements. This paper presents ArCo and describes how to apply XD to the development and validation of a CH knowledge graph, also detailing the (intellectual) process implemented for matching the encountered modelling problems to ODPs. Relevant contributions also include a novel web tool for supporting unit-testing of knowledge graphs, a rigorous evaluation of ArCo, and a discussion of methodological lessons learned during ArCo’s development.

scholarly journals The Implementation of Credit Risk Scorecard Using Ontology Design Patterns and BCBS 239

2020 ◽  
Vol 20 (2) ◽  
pp. 93-104
Author(s):  
Jalil Elhassouni ◽  
Abderrahim El qadi ◽  
Yasser El madani El alami ◽  
Mohamed El haziti
Keyword(s):  
Credit Risk ◽  
Information And Communication Technologies ◽  
Financial Institutions ◽  
Design Patterns ◽  
Decisive Role ◽  
Credit Risk Management ◽  
Technology Infrastructure ◽  
Ontology Design ◽  
Information And Communication ◽  
The 2008 Financial Crisis

AbstractNowadays information and communication technologies are playing a decisive role in helping the financial institutions to deal with the management of credit risk. There have been significant advances in scorecard model for credit risk management. Practitioners and policy makers have invested in implementing and exploring a variety of new models individually. Coordinating and sharing information groups, however, achieved less progress. One of several causes of the 2008 financial crisis was in data architecture and information technology infrastructure. To remedy this problem the Basel Committee on Banking Supervision (BCBS) outlined a set of principles called BCBS 239. Using Ontology Design Patterns (ODPs) and BCBS 239, credit risk scorecard and applicant ontologies are proposed to improve the decision making process in credit loan. Both ontologies were validated, distributed in Ontology Web Language (OWL) files and checked in the test cases using SPARQL. Thus, making their (re)usability and expandability easier in financial institutions. These ontologies will also make sharing data more effective and less costly.

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