The Open Biological and Biomedical Ontologies (OBO) provide a suite of high-quality, interoperable, free and open source tools for sharing scientific knowledge and making new discoveries.
This tutorial reflects the lessons that I've learned using OBO ontologies to work with scientific data. You'll learn how to use OBO ontologies to communicate more clearly, to integrate data, and to improve search and analysis.
We use a single running example to keep things concrete: a spreadsheet of data about histology observations. Starting with this data, we build an application ontology, transform the data into linked data, and then apply an automated reasoner and query over it. All using open source code and tools.
- Introduction
- Names and Naming
- Open Biological and Biomedical Ontologies (OBO)
- Using and Reusing Ontologies
- Processing Data with Ontologies
- Updating, Testing, and Releasing Ontologies
NOTE: This is still a work in progress. Not all of the sections are complete.
Here are some links to other resources for learning about OBO:
To read through the tutorial and look at most of the files, all you need is a web browser. To view the OWL files you should use the desktop version of Protégé.
If you want to dig deeper, see code/README.md.
Here's a quick overview of the repository:
docs: the tutorial content in Markdown formatexamples: data and code files referred to in the tutorialimages: supporting imagescode: more elaborate code examples to support the tutorialbin: other code for working with the tutorial
Corrections, improvements, suggestions, bug reports, etc. are all very much appreciated! Please:
- add an issue to our tracker
- create a pull request
- or email me at [email protected]
Copyright © 2017, James A. Overton
Distributed under the CC-by 3.0 License: https://creativecommons.org/licenses/by/3.0/