Creating Cognitive Frames Based on Ontology Design Patterns for Ontology Visualization

2014 ◽  
pp. 90-104 ◽  
Author(s):  
Pavel Lomov ◽  
Maxim Shishaev
Keyword(s):  
Design Patterns ◽  
Cognitive Frames ◽  
Ontology Design ◽  
Ontology Visualization

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

scholarly journals Ontological Representation of Smart City Data: From Devices to Cities

2018 ◽  
Vol 9 (1) ◽  
pp. 32 ◽  
Author(s):  
Paola Espinoza-Arias ◽  
María Poveda-Villalón ◽  
Raúl García-Castro ◽  
Oscar  Corcho
Keyword(s):  
Information Systems ◽  
Smart City ◽  
Design Patterns ◽  
Core Model ◽  
Ontological Commitments ◽  
Related Data ◽  
Ontology Design ◽  
Different Types ◽  
Core Concepts

Existing smart city ontologies allow representing different types of city-related data from cities. They have been developed according to different ontological commitments and hence do not share a minimum core model that would facilitate interoperability among smart city information systems. In this work, a survey has been carried out in order to study available smart city ontologies and to identify the domains they are representing. Taking into account the findings of the survey and a set of ontological requirements for smart city data, a list of ontology design patterns is proposed. These patterns aim to be easily replicated and provide a minimum set of core concepts in order to guide the development of smart city ontologies.

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