ontoweaver 0.2.3

Exports from tables to Semantic Knowledge Graphs, with a simple declarative mapping.

OntoWeaver

OntoWeaver is a tool for transforming tabular data in Semantic Knowledge Graphs (SKG) databases.

OntoWeaver allows writing a simple declarative mapping to express how columns from a table should be converted as typed nodes, edges, or properties in an SKG.

SKG databases allow for an easy integration of very heterogeneous data, and OntoWeaver brings a reproducible approach to building them.

With OntoWeaver, you can very easily implement a script that will allow you to automatically reconfigure a new SKG from the input data, each time you need it.

OntoWeaver has been tested on large scale biomedical use cases, and we can guarantee that it is simple to operate by anyone having a basic knowledge of programming.

Basics

OntoWeaver provides a simple layer of abstraction on top of Biocypher, which remains responsible for doing the ontology alignment, supporting several graph database backends, and allowing reproducible & configurable builds.

With a pure Biocypher approach, you would have to write a whole adapter by hand, with OntoWeaver, you just have to express a mapping in YAML, looking like:

row: # The meaning of an entry in the input table.
   map:
      column: <column name in your CSV>
      to_subject: <ontology node type to use for representing a row>

transformers: # How to map cells to nodes and edges.
    - map: # Map a column to a node.
        column: <column name>
        to_object: <ontology node type to use for representing a column>
        via_relation: <edge type for linking subject and object nodes>
    - map: # Map a column to a property.
        column: <another name>
        to_property: <property name>
        for_object: <type holding the property>

metadata: # Optional properties added to every node and edge.
    - source: "My OntoWeaver adapter"
    - version: "v1.2.3"

OntoWeaver can read anything that Pandas can load, which means a lot of tabular formats.

Installation

The project is written in Python and uses Poetry. You can install the necessary dependencies in a virtual environment like this:

git clone https://github.com/oncodash/ontoweaver.git
cd ontoweaver
poetry install

Poetry will create a virtual environment according to your configuration (either centrally or in the project folder). You can activate it by running poetry shell inside the project directory.

Theoretically, the graph can be imported in any [graph] database supported by BioCypher (Neo4j, ArangoDB, CSV, RDF, PostgreSQL, SQLite, NetworkX, … see BioCypher's documentation).

Usage Documentation

Detailed documentation with tutorials and a more detailed installation guide is available on the OntoWeaver website.

Tests

Tests are located in the tests/ subdirectory and may be a good starting point to see OntoWeaver in practice. You may start with tests/test_simplest.py which shows the simplest example of mapping tabular data through BioCypher.

To run tests, use pytest:

poetry run pytest

Contributing

In case of any questions or improvements feel free to open an issue or a pull request!