scholarly journals Applying the LOT Methodology to a Public Bus Transport Ontology aligned with Transmodel: Challenges and Results

Semantic Web ◽  
2021 ◽  
pp. 1-19
Author(s):  
Edna Ruckhaus ◽  
Adolfo Anton-Bravo ◽  
Mario Scrocca ◽  
Oscar Corcho
Keyword(s):  
Design Patterns ◽  
Reference Model ◽  
Data Driven ◽  
Transport Systems ◽  
Ontology Design ◽  
Rdf Data ◽  
Mapping Language ◽  
Uml Specification ◽  
Validation Stage ◽  
Bus Transport

We present an ontology that describes the domain of Public Transport by bus, which is common in cities around the world. This ontology is aligned to Transmodel, a reference model which is available as a UML specification and which was developed to foster interoperability of data about transport systems across Europe. The alignment with this non-ontological resource required the adaptation of the Linked Open Terms (LOT) methodology, which has been used by our team as the methodological framework for the development of many ontologies used for the publication of open city data. The ontology is structured into three main modules: (1) agencies, operators and the lines that they manage, (2) lines, routes, stops and journey patterns, and (3) planned vehicle journeys with their timetables and service calendars. Besides reusing Transmodel concepts, the ontology also reuses common ontology design patterns from GeoSPARQL and the SOSA ontology. As part of the LOT data-driven validation stage, RDF data has been generated taking as input the GTFS feeds (General Transit Feed Specification) provided by the Madrid public bus transport provider (EMT). Mapping rules from structured data sources to RDF were developed using the RDF Mapping Language (RML) to generate RDF data, and queries corresponding to competency questions were tested.

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 Optimal Design of Electric Bus Transport Systems With Minimal Total Ownership Cost

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 119184-119199
Author(s):  
Mohamed Lotfi ◽  
Pedro Pereira ◽  
Nikolaos G. Paterakis ◽  
Hossam A. Gabbar ◽  
Joao P. S. Catalao
Keyword(s):  
Optimal Design ◽  
Transport Systems ◽  
Electric Bus ◽  
Bus Transport

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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