LibOmexMeta is a library aimed at providing developer-level support for reading, writing, editing and managing semantic annotations for biosimulation models. The COMBINE modeling community has developed consensus around how best to annotate models and how to package these models into archives (OMEX files) that include the modeling source code, the annotations, files that describe parameters and settings needed for simulations (in a SEDML file), and potentially the data used for these modeling efforts. This consensus was initially described in the publication "Harmonizing semantic annotations for computational models in biology" (Briefings in Bioinformatics, 2018).
The goal of semantic annotations are to make explicit the biology that underlies the semantics of biosimulation models. By using standard knowledge resources about biology and biological processes (such as CheBI, Uniprot, and ontologies of anatomy), we can make the models more understandable, reusable and reproducible. More information can be found at the OMEX Metadata Specification web page.
LibOmexMeta is a C++ library with a C interface that is used to build a Python front end (pyomexmeta). LibOmexMeta uses RDF as a framework for representing these annotations. At the core of libOmexMeta are the Redland libraries:
- raptor2 for parsing RDF syntax into RDF graphs and serializing the output
- rasqal for querying RDF graphs
- librdf as a front end to raptor2 and rasqal and for triple stores.
An interactive demonstration of pyomexmeta via Jupyter notebook is available via the launch binder badge above or by following this direct link. When you get to the binder site, select the file called "notebook.ipynb" to start the demo. Remember that notebooks are made of cells containing code. To execute code in a particular cell, select the cell and then pick the run button in the tool bar. The source for this live demonstration is available here: https://github.com/sys-bio/pyomexmeta-binder-notebook.
- rdfxml, ntriples, turtle, trig, rss-tag-soup, grddl, guess, rdfa, nquads, guess
- ntriples, turtle, rdfxml-xmp, rdfxml-abbrev, rdfxml, rss-1.0, atom, dot, json-triples, json, nquads, html
- Query result formats:
- xml, json, table, csv, mkr, tsv, html, turtle, rdfxml,
- hashes, memory, file, mysql, sqlite, uri, tstore (may be supported on request), postgresql (supported but not tested), virtuoso (may be supported on request),
- Linux Ubuntu 18.04
- ManyLinux 2014
$ pip install pyomexmeta
# verify its worked
$ ipython -c "import pyomexmeta"
Python 3 only - if you're not using Python 3, I recommend you upgrade.
You can get a docker image using
$ docker pull ciaranwelsh/libomexmeta
This is an Ubuntu 18.04 based container that has libOmexMeta prebuilt and installed under
/libOmexMeta/install-docker. See dockerfile for full set of commands to build libOmexMeta on ubuntu.
Conda is preconfigured and pyomexmeta is installed.
You can download binaries from the releases tab
Building from source
See the azure-pipelines.yml file to see how we build libOmexMeta on Azure Pipelines.
We use vcpkg for acquiring the dependencies that we need on all platforms. Therefore, the following works on windows, linux and macOS. Note that on linux you need gcc-9 or greater. libOmexMeta was developed with gcc-10.2.
# set variable to hold vcpkg location:
git clone https://github.com/microsoft/vcpkg.git $VCPKG_INSTALL_PREFIX
vcpkg integrate install
vcpkg install curl pcre openssl yajl sqlite3 liblzma
Now build libOmexMeta
git clone https://github.com/sys-bio/libOmexMeta.git
cmake -DVCPKG_ROOT=$VCPKG_INSTALL_PREFIX -DCMAKE_INSTALL_PREFIX="/full/path/to/where/you/want/to/install/libomexmeta" -DBUILD_TESTS=ON -DCMAKE_BUILD_TYPE=Release -DBUILD_PYTHON=ON ..
cmake --build . --target install --config Release -j 12