Owlready is a Python module for ontology-oriented programming. It can load OWL 2.0 ontologies and manipulate them transparently in Python.

This new release includes a few new features, and bugfixes.

Here are the changes:

• Allow the declaration of custom datatypes with declare_datatype()

• Support the annotation of annotations (e.g. a comment on a comment)

• search() now support the "subproperty_of" argument

• search() now support the "bm25" argument (for full-text searches)

• Bugfixes: - Fix Concept.descendant_concepts() in PymedTermino2 - Update already loaded properties when new ontologies are loaded - Now accept %xx quoted characters in file:// URL - Improve error message on punned entities - Property.get_relations() now considers inverse properties - Fix "AttributeError: 'mappingproxy' object has no attribute 'pop'" error - Fix Thing.instances()

The new version be downloaded from PyPI (Python Package Index): https://pypi.python.org/pypi/Owlready2

I have published a new journal paper:

[j64] Mbaye F, Lamy JB, Sembene M. Identifying the mitochondrial DNA mutations that cause cancer. Research Outbreak 2020;117:50-53

I have published a new journal paper:

[j63] Marcilly R, Douze L, Ferré S, Audeh B, Bobed C, Lillo-Le Louët A, Lamy JB, Bousquet C. How to interact with medical terminologies? Formative usability evaluations comparing three approaches for supporting the use of MedDRA by pharmacovigilance specialists. BMC Medical Informatics and Decision Making 2020;20:261

I presented my works at the Information Visualisation (iV) 2020 conference.

The paper is entitled "Comparison of four visual analytics techniques for the visualization of adverse drug event rates in clinical trials" and is available here and the presentation there or in video below:

iv2020_video.mp4

I presented my works on the use of rainbow boxes for determining synergies between drugs, at ICIMTH 2020.

My paper was entitled "Visualization of potential drug synergies". It is available here and the presentation just below in video:

icimth_video.mp4

And I obtained a Best paper award!

My students and colleagues also presented four papers:

• Saab A, Saikali M, Lamy JB: Comparison of machine learning algorithms for classifying adverse-event related 30-day hospital readmissions: Potential implications for patient safety

• Diallo AH, Camara G, Lo M, Diagne I, Lamy JB: Iconic visualization of sickle cell patients current and past health status

• Mouazer A, Sedki K, Tsopra R, Lamy JB: Visualization of drug interactions for supporting medication review

• Sedki K, Lakrafli C, Lamy JB, Tsopra R: An approach based on preference learning for identifying experts reasoning in antibiotic treatment

I have published a new journal paper:

[j60] Bouaud J, Pelayo S, Lamy JB, Prébet C, Ngo C, Teixeira L, Guezennec G, Séroussi B. Implementation of an ontological reasoning to support the guideline-based management of primary breast cancer patients in the DESIREE project. Artificial Intelligence in Medicine 2020;108:101922

I have published a new preprint:

[p1] Lamy JB. A data science approach to drug safety: Semantic and visual mining of adverse drug events from clinical trials of pain treatments. Arxiv preprint arxiv:2006.16910 2020

Owlready is a Python module for ontology-oriented programming. It can load OWL 2.0 ontologies and manipulate them transparently in Python.

This new release includes several small changes and bugfixes. It now uses the Git versionning system, instead of Mercurial.

Here are the changes:

• Support intersection of searches (e.g. World.search(...) & World.search(...))

• Add owlready2.reasoning.JAVA_MEMORY

• Move development repository to Git

• Bugfixes: - Fix parsing of NTriples files that do not end with a new line - Fix KeyError with Prop.python_name when several properties share the same name - Fix get_ontology() calls in Python module imported by ontologies in a World that is not default_world - Fix use of PyMedTermino2 in a World that is not default_world - Fix World.as_rdflib_graph().get_context(onto) for ontology added after the creation of the RDFLIB graph - Fix destroying SWRL rules - Fix disjoint with non-atomic classes

The new version be downloaded from PyPI (Python Package Index): https://pypi.python.org/pypi/Owlready2

I have published a new journal paper:

[j54] Lamy JB, Sedki K, Tsopra R. Explainable decision support through the learning and visualization of preferences from a formal ontology of antibiotic treatments. Journal of Biomedical Informatics 2020;104C:103407

I have published a new journal paper:

[j50] Toure S, Mbaye F, Gueye MD, Fall M, Dem A, Lamy JB, Sembene M. Somatic mitochondrial mutations in oral cavity cancers among senegalese patients. Asian Pacific journal of cancer prevention (APJCP) 2019;20(7):2203-2208

Owlready is a Python module for ontology-oriented programming. It can load OWL 2.0 ontologies and manipulate them transparently in Python.

This new release includes several small changes and bugfixes.

Here are the changes:

• Add get_parents_of(), get_instances_of(), get_children_of() methods to ontology, for querying the hierarchical relations defined in a given ontology

• Use Thing as default value for restrictions with number, instead of None

• Add 'filter' parameter to save(), for filtering the entities saved (contributed by Javier de la Rosa)

• Bugfixes: - Fix value restriction with the false value - Fix blank node loading from different ontologies - Fix constructs reused by several classes - Fix 'Class.is_a = []' was not turning the list into an Owlready list - Fix destroy_entity() - was not destroying the IRI of the entity - Improve setup.py: ignore Cython if Cython installation fails

The new version be downloaded from PyPI (Python Package Index): https://pypi.python.org/pypi/Owlready2

I have published a new journal paper:

[j53] Tsopra R, Courtine M, Sedki K, Eap D, Cabal M, Cohen S, Bouchaud O, Mechaï F, Lamy JB. AntibioGame®: A serious game for teaching medical students about antibiotic use. International Journal of Medical Informatics 2020;136:104074

Owlready is a Python module for ontology-oriented programming. It can load OWL 2.0 ontologies and manipulate them transparently in Python.

Here are the changes:

• Add support for disjoint unions (Class.disjoint_unions)

• Add deepcopy support on class constructs, and automatically deep-copy constructs when needed (i.e. no more OwlReadySharedBlankNodeError)

• Support the creation of blank nodes with RDFlib

The new version be downloaded from PyPI (Python Package Index): https://pypi.python.org/pypi/Owlready2