I am please to announce the first full release of Tawny-OWL, my library for fully programmatic development of OWL ontologies. The library now has a fairly large feature set:
Complete support for OWL2
Integrated support for reasoning with HermiT or ELK
Fixtures and support macros for unit testing
Use of external ontologies available only as OWL files
Rendering of OWL API objects to Tawny code.
Support for generating and using ontologies with numeric IDs.
Support for multilingual labels.
Additionally, I now have initial integration with Protege, described later.
Feedback is welcome at email@example.com.
A little over a year ago, I first described my experiments with building a programmatic environment for ontology construction [@url:www.russet.org.uk/blog/2214] The need arose out of frustration with existing ontology tools; Protege, for example, provides a nice graphical environment, but it has many limitations. It does not easily allow automated generation of ontology entities, for example, and it also does not provide access to tools which are common place in an IDE: versioning tools, diffs, test cases and so forth. While ontology specific variations of these tools do exist, they were not as good as the ones I was used to use when programming.
Tawny seeks to bridge this gap, by using a full programmatic environment to generate OWL ontologies. I chose Clojure because of its syntactic plasticity; at its simplest, when using tawny, it does not feel like a programming language, just a syntax and evaluation engine for writing ontologies. However, the full power of the programming language is there and can be used when necessary [@url:www.russet.org.uk/blog/2366]
Since the first blog post, there have now been a further 8, as well as three papers, describing tawny itself [@url:www.russet.org.uk/blog/2366] the karyotype ontology [@url:arxiv.org/abs/1305.3758] and our use of patterns, higher-level abstractions within the karyotype ontology and applied to SIO. From an initial experiment, tawny has become a useful tool which we are using on a daily basis.
- In Early Release
Included in this release is our initial integration with Protege. Tawny builds on the OWL API, which is also the basis for Protege. I always assumed that Protege would be used to view OWL files generated by Tawny, but it is actually possible to integrate them much more comprehensively than this. It is now possible to directly manipulate the data structures of Protege using Tawny; in short, Protege can display what ever tawny has generated immediately, and without a file in between.
We have achieved this in two ways; firstly with protege-tawny which provides a command line environment directly inside Protege. This is useful, but does not provide the rich programmatic IDE that I want. However, the protege-nrepl environment allows exactly this; protege launches Clojure, and launches a NREPL server to which you connect with Emacs, Eclipse or any of the other Clojure IDEs. Finally, lein-sync allows syncing classpaths and dependencies with an existing Clojure project. The practical upshot can be seen in screencast; tawny can be used as normal, with Protege following.
Currently, Protege and Tawny use different versions of the OWL API, so while the protege-nrepl can be used with the current release of Protege, periodic crashes happen. In the meantime, a hand-built distribution of Protege is available including nrepl.
- For the Future
I have three main aims for the next few releases of Tawny. First, we need to provide access to explanation code; currently, this has to be accessed within Protege, which is less than ideal for a process than can take many minutes to run. I wish to integrate this with the Clojure unit test environment so that explanations will be generated by failing test cases.
Second, tawny currently allows the development of ontologies, but does not allow easy querying over them. I have several possibilities here: including integration of a SPARQL engine; the current rendering engine, combined perhaps with core.match, or, finally, fully-fledged support for core.match directly.
Finally, I wish to experiment with and add support for connection points [@url:www.russet.org.uk/blog/2955] to better enable modular ontology development.