odML - Terminologies

This repository contains Terminologies; odML facilitates and encourages standardization of scientific metadata by providing such terminologies. An odML-file can be based on such a terminology. In that case one does not need to provide definitions since they are part of the linked terminology. This page hosts all currently available odML Terminology files.

A general introduction to odML and its usage can be found at the main odML page. A brief introduction can be found at the bottom of the page.

If you would like to contribute and provide additions to the terminology collection to be shared with and used by the community, please open an issue or even create a Pull Request with your terminology on the corresponding github repository.

Terminology collection

A brief introduction to odML and metadata

odML (open metadata Markup Language) is a framework, proposed by Grewe et al. (2011), to organize and store experimental metadata in a human- and machine-readable, XML based format (odml). In this tutorial we will illustrate the conceptual design of the odML framework and show hands-on how you can generate your own odML metadata file collection. A well organized metadata management of your experiment is a key component to guarantee the reproducibility of your research and facilitate the provenance tracking of your analysis projects.

What are metadata and why are they needed?

Metadata are data about data. They describe the conditions under which the actual raw-data of an experimental study were acquired. The organization of such metadata and their accessibility may sound like a trivial task, and most laboratories developed their home-made solutions to keep track of their metadata. Most of these solutions, however, break down if data and metadata need to be shared within a collaboration, because implicit knowledge of what is important and how it is organized is often underestimated.

While maintaining the relation to the actual raw-data, odML can help to collect all metadata which are usually distributed over several files and formats, and to store them unitedly which facilitates sharing data and metadata.

Key features of odML

• open, XML based language, to collect, store and share metadata
• Machine- and human-readable
• Python-odML library
• Interactive odML-Editor