scholarly journals Quantitative evaluation of ontology design patterns for combining pathology and anatomy ontologies

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Sarah M. Alghamdi ◽  
Beth A. Sundberg ◽  
John P. Sundberg ◽  
Paul N. Schofield ◽  
Robert Hoehndorf
Keyword(s):  
Quantitative Evaluation ◽  
Design Patterns ◽  
Ontology Design

scholarly journals Quantitative evaluation of ontology design patterns for combining pathology and anatomy ontologies

2018 ◽  
Author(s):  
Sarah M. Alghamdi ◽  
Beth A. Sundberg ◽  
John P. Sundberg ◽  
Paul N. Schofield ◽  
Robert Hoehndorf
Keyword(s):  
Semantic Similarity ◽  
Quantitative Evaluation ◽  
Design Patterns ◽  
Data Driven ◽  
Anatomic Pathology ◽  
Ontology Design ◽  
Data Driven Approach ◽  
Rich Information ◽  
The Subject ◽  
Multiple Ontologies

ABSTRACTData are increasingly annotated with multiple ontologies to capture rich information about the features of the subject under investigation. Analysis may be performed over each ontology separately, but, recently, there has been a move to combine multiple ontologies to provide more powerful analytical possibilities. However, it is often not clear how to combine ontologies or how to assess or evaluate the potential design patterns available. Here we use a large and well-characterized dataset of anatomic pathology descriptions from a major study of aging mice. We show how different design patterns based on the MPATH and MA ontologies provide orthogonal axes of analysis, and perform differently in over-representation and semantic similarity applications. We discuss how such a data-driven approach might be used generally to generate and evaluate ontology design patterns.

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.

Modular Ontology Modeling: A Tutorial

2020 ◽  
Author(s):  
Cogan Shimizu ◽  
Pascal Hitzler ◽  
Adila Krisnadhi
Keyword(s):  
Design Patterns ◽  
Ontology Engineering ◽  
Web Ontology Language ◽  
Ontology Language ◽  
Ontology Modeling ◽  
Ontology Design ◽  
Modular Ontology ◽  
The Web

We provide an in-depth example of modular ontology engineering with ontology design patterns. The style and content of this chapter is adapted from previous work and tutorials on Modular Ontology Modeling. It offers expanded steps and updated tool information. The tutorial is largely self-contained, but assumes that the reader is familiar with the Web Ontology Language OWL; however, we do briefly review some foundational concepts. By the end of the tutorial, we expect the reader to have an understanding of the underlying motivation and methodology for producing a modular ontology.

A Trajectory Ontology Design Pattern for Semantic Trajectory Data Warehouses

2019 ◽  
pp. 83-104 ◽  
Author(s):  
Marwa Manaa ◽  
Thouraya Sakouhi ◽  
Jalel Akaichi
Keyword(s):  
Case Studies ◽  
Design Pattern ◽  
Design Patterns ◽  
Domain Knowledge ◽  
Data Warehouses ◽  
Trajectory Data ◽  
Semantic Approach ◽  
Mobility Data ◽  
Ontology Design ◽  
Ontology Design Pattern

Mobility data became an important paradigm for computing performed in various areas. Mobility data is considered as a core revealing the trace of mobile objects displacements. While each area presents a different optic of trajectory, they aim to support mobility data with domain knowledge. Semantic annotations may offer a common model for trajectories. Ontology design patterns seem to be promising solutions to define such trajectory related pattern. They appear more suitable for the annotation of multiperspective data than the only use of ontologies. The trajectory ontology design pattern will be used as a semantic layer for trajectory data warehouses for the sake of analyzing instantaneous behaviors conducted by mobile entities. In this chapter, the authors propose a semantic approach for the semantic modeling of trajectory and trajectory data warehouses based on a trajectory ontology design pattern. They validate the proposal through real case studies dealing with behavior analysis and animal tracking case studies.

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
Sign in / Sign up

Export Citation Format

Share Document