Ontologies with Python: Programming Owl 2.0 Ontologies with Python and Owlready2

ISBN-13: 9781484265512 / Angielski / Miękka / 2020 / 344 str.

Jean-Baptiste Lamy

Spis treści

Chapter 1: Introduction

1. Who is this book for?

2. Why ontologies?

3. Why Python?

4. Why Owlready?

5. Book outline

6. Acknowledgements

Chapter 2: Python Language: Adopt a Snake! 

1. Installing Python

2. Starting Python

3. Syntax 

4. Main datatypes

5. Conditions (if)

6. Loops (for) 

7. Generators

8. Functions (def) 

9. Classes (class) 

10. Python modules

11. Installing Owlready2

12. Summary

Chapter 3: OWL Ontologies 

1. An ontology... what does it look like?

2. Creating ontologies manually with the Protégé editor

3. Example: An ontology of bacteria

4. Creating a new ontology

• Classes

• Disjoints

• Partitions 

• Data properties

• Object properties 

• Restrictions 

• Union, intersection, and complement

• Definitions (equivalent to relations)

• Individuals 

• Other constructs 

5. Automatic reasoning

6. Modeling exercises

7. Summary

Chapter 4: Accessing Ontologies in Python 

1. Importing Olwready

2. Loading an ontology 

3. Imported ontologies

4. Listing the content of the ontology 

5. Accessing to entities 

• Individuals 

• Relations 

• Classes

• Existential restrictions 

• Properties 

6. Searching for entities 

7. Huge ontologies and disk cache 

8. Namespaces 

9. Modifying entity rendering as text 

10. Local directory of ontologies 

11. Reloading an ontology in the quadstore 

12. Example: Creating a dynamic website from an ontology

13. Summary

Chapter 5: Creating and Modifying Ontologies in Python 

1. Creating an empty ontology 

2. Creating classes 

3. Creating properties 

4. Creating individuals 

5. Modifying entities: Relations and existential restrictions

6. Creating entities within a namespace

7. Renaming entities (refactoring)

8. Multiple definitions and forward declarations

9. Destroying entities 

10. Destroying an ontology

11. Saving an ontology

12. Importing ontologies 

13. Synchronization 

14. Example: Populating an ontology from a CSV file

15. Summary

Chapter 6: Constructs, Restrictions, Class Properties 

1. Creating constructs 

2. Accessing constructs parameters 

3. Restrictions as class properties 

4. Defined classes 

5. Example: Creating the ontology of bacteria in Python

6. Example: Populating an ontology with defined classes

7. Summary

Chapter 7: Automatic Reasoning 

1. Disjoints 

2. Open-world assumption

3. Reasoning in a closed world, or in a local closed world

4. Inconsistent classes and inconsistent ontologies

5. Restriction and reasoning on numbers and strings 

6. SWRL rules 

7. Example: An ontology-based decision support system

8. Summary

Chapter 8: Annotations, Multilingual Texts and Full Text Search 

1. Annotating entities

2. Multilingual texts

3. Annotating constructs

4. Annotating properties and relations 

5. Creating new annotation classes

6. Ontology metadata 

7. Full text search 

8. Example: Using DBpedia in Python 

• Loading DBpedia 

• A search engine for Dbpedia

9. Summary

Chapter 9: Using Medical Terminologies with PyMedTermino and UMLS 

1. UMLS 

2. Importing terminologies from UMLS 

3. Loading terminologies after initial importation 

4. Using ICD10 

5. Using SNOMED CT

6. Using UMLS unified concepts (CUI)

7. Transcoding between terminologies

8. Manipulating sets of concepts 

9. Importing all terminologies in UMLS

10. Example: Linking the ontology of bacteria with UMLS

11. Example: A multi-terminology browser

12. Summary

Chapter 10: Mixing Python and OWL 

1. Adding Python methods to OWL classes 

2. Associating a Python module to an ontology

• Manual import 

• Automatic import 

3. Polymorphism with type inference 

4. Introspection 

5. Reading restrictions backward 

6. Example: using Gene Ontology and managing part-of relations

7. Example: A “dating site” for proteins

8. Summary

Chapter 11: Working with RDF Triples and Worlds 

1. RDF triples

2. Manipulating RDF triples with RDFlib 

3. Performing SPARQL requests 

4. Accessing RDF triples with Owlready

5. Interrogating the SQLite3 database directly

6. Creating several, isolated, world

7. Summary

Annex A: Description logics

Annex B: Notations for formal ontologies

Annex C: Reference manual

O autorze

Lamy Jean-Baptiste is a senior lecturer at Paris 13 University and a member of the LIMICS, a research lab focused on biomedical informatics. He is also the developer of the Owlready2 Python module that allows access to OWL ontologies. He has developed many research prototypes, and one of them (VCM iconic medical language) has been patented in the US, with three licenses sold to industrial partners.

Lamy speaks regularly at artificial intelligence and medical informatics conferences, has written over 50 journal papers, and is a moderator on the Owlready forum on Nabbles. He was awarded the best paper award at MEDINFO 2019, the largest international conference in medical informatics.

Blurb

Use ontologies in Python, with the Owlready2 module developed for ontology-oriented programming. You will start with an introduction and refresher on Python and OWL ontologies. Then, you will dive straight into how to access, create, and modify ontologies in Python. Next, you will move on to an overview of semantic constructs and class properties followed by how to perform automatic reasoning. You will also learn about annotations, multilingual texts, and how to add Python methods to OWL classes and ontologies. Using medical terminologies as well as direct access to RDF triples is also covered.

Python is one of the most used programming languages, especially in the biomedical field, and formal ontologies are also widely used. However, there are limited resources for the use of ontologies in Python. Owlready2, downloaded more than 60,000 times, is a response to this problem, and this book is the first one on the topic of using ontologies with Python.

You will:

• Use Owlready2 to access and modify OWL ontologies in Python
• Publish ontologies on dynamic websites
• Perform automatic reasoning in Python
• Use well-known ontologies, including DBpedia and Gene Ontology, and terminological resources, such as UMLS (Unified Medical Language System)
• Integrate Python methods in OWL ontologies