Owlready2 0.9 has been released!

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

This new version allows the use of PostgresQL instead of SQLite3 (however, performances are usually lower). It also facilitate the access to SOME restrictions on classes, using the dotted notation "class.property".

Here are the changes in version 0.9:

  • PostgresQL backend (in addition to SQLite3)

  • Add 'exclusive = False' option for SQLite3 backend (slower, but allows multiple uses)

  • Use unique index in sqlite3 quadstore on resources table

  • Optimize sqlite3 quadstore by caching IRI dict (5% faster)

  • Add == support for class construct

  • Add get_namespace() support on World

  • Add 'existential restrictions as class properties' feature

  • Bugfixes: - Fix imported ontologies - Fix saving ontologies in onto_path - Fix clear() on CallbackList - Fix bug in Class IRI in ontologies whose base IRI ends with a / - Fix imported ontologies in ontologies whose base IRI ends with a /

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

The great table of ontologies

This big table summarize 5 notations used with formal ontologies in OWL: description logics, the syntax of the Protégé editor, the syntax of Owlready2 in Python, and the semantics in first-order logic and in set formula. Keep on hand when working on formal ontologies!

You can download the great table of ontologies.

Owlready2 0.8 has been released!

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 in versions 0.6, 0.7 and 0.8 (the first two have lasted only a few hours):

  • Add set_datatype_iri() global function for associating a Python datatype to an IRI

  • Add nquads ontology format (useful for debugging)

  • Add support for dir() on individuals

  • Add support for ontology using https: protocol (thanks Samourkasidis Argyrios)

  • Add observe module (for registering callback when the ontology is modified)

  • Improve docs

  • Bugfixes: - Align Python floats with xsd:decimal rather than xsd:double, finally, because decimal accepts int too - Fix Class.instances() so as it returns instances of subclasses (as indicated in the doc) - Fix direct assignation to Ontology.imported_ontologies - Fix a bug in reasoning, when adding deduced facts between one loaded and one non-loaded entity - Fix search(prop = "value") when value is a string and the ontology uses localized string

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

New journal paper "Using preference learning for detecting inconsistencies in clinical practice guidelines"

I have published a new journal paper:

journalif [j40] Tsopra R, Lamy JB, Sedki K. Using preference learning for detecting inconsistencies in clinical practice guidelines: methods and application to antibiotherapy. Artificial Intelligence in Medicine 2018;89:24-33, IMIA Yearbook 2019 best paper in decision support

Presentation at MIE 2018 on VCM icons

I presented my works about the design of a mapping between VCM icons and the MedDRA terminology at the MIE 2018 conference.

The paper "Combining Semantic and Lexical Methods for Mapping MedDRA to VCM Icons" is abailable here and the presentation there.

New chapter "Artificial Feeding Birds (AFB)"

I have published a new book chapter:

other [x18] Lamy JB. Artificial Feeding Birds (AFB): a new metaheuristic inspired by the behavior of pigeons. Advances in nature-inspired computing and applications 2019;43-60, Springer

Happy new year 2018!

_images/voeux_2018.png

Owlready2 0.5 has been released!

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

This new version is mostly a bugfix release.

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

EditObj 3 0.1 is out !

This is the first stable release of EditObj 3.

It is a full rewrite of EditObj 2, and it now supports Qt and HTML.

It is available on PyPI (Python Package Index).

Songwrite 3 0.1

_images/icones.png

Songwrite 3 0.1 is out ! This version is a full rewrite with Python 3 and Qt. Enjoy!

It is available on PyPI (Python Package Index) and can be installed under Linux with pip:

pip3 install songwrite3

Before that, do not forget to install Python3, pip and PyQt5 from your Linux distribution.

Owlready2 0.4 has been released!

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

The main new features of version 2 - 0.4 are:

  • the defined relations can be queried for a given individual (using the .get_properties(), .get_inverse_properties() and .get_relations() methods)

  • improvement of the .search() method, which now takes into account inheritance and inverse relations

  • optimisation of recursive request in SQL

  • several bug fixes

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

PyPI download statistics available!

No official download statistics are available for PyPI (the Python Package Index).

I've managed to extract the download statistics for all Python modules, on a per-month basis, since may 2016.

The method is described here, and the entire dataset can be downloaded as a CSV file.

New journal paper "Formalization of the semantics of iconic languages"

I have published a new journal paper:

journalif [j37] Lamy JB, Soualmia LF. Formalization of the semantics of iconic languages: An ontology-based method and four semantic-powered applications. Knowledge-Based Systems 2017;135:159-179

New journal paper "Rainbow boxes"

I have published a new journal paper:

journalif [j36] Lamy JB, Berthelot H, Capron C, Favre M. Rainbow boxes: a new technique for overlapping set visualization and two applications in the biomedical domain. Journal of Visual Language and Computing 2017;43:71-82