IT concept and glossary

This page introduces the Open Power System Data platform IT framework. If you have questions or suggestions, please contact Ingmar Schlecht.

Our “IT philosophy”

We have seen many IT projects come and go because of lacking user support. We want an IT enviroment that is simple, easy to maintain, decentralized, and scalable. This is why we are using a light weight, decentralized structure rather than a central database server. Rather than re-inventing the wheel with proprietary solutions, we build on existing open-source software solutions (Jupyter Notebooks and Python), collaborative software development tools (Git and GitHub), and established industry standards for open data (Data Packages).

Data Packages

We follow a standard defined by Open Knowledge and compile all information in Data Packages, that is: one or more CSV files for data, a JSON-file for metadata, and a readme-file. Data Packages allow easy integration into existing IT frameworks: an Excel macro, a Python module, and many more interfaces are readily available.

Data: CSV files (and more)

Data is provided in CSV files. This allows for easy and fast download, as no database is required. CSV files are human-readable and can be used by almost any software. Note that we follow the international standard of actually using commas as separators (not semi-colons). In addition, Excel (XLSX) and SQLite files are provided.

Scripts and documentation: Jupyter Notebooks

The scripts that we use to automatically download, process, and aggregate data are written in Python. We use Jupyter (iPython) Notebooks as a single file for coding and documentation. Jupyter Notebook is an application that allows you to create and share documents that contain live code, equations, visualizations and explanatory text. The Notebooks created in this project are available under the open-source MIT license on GitHub.

Metadata: JSON files

All metadata is published in JSON format and follows the Data Package, Tabular Data Package and JSON Table Schema specifications by Open Knowledge International.

Version control

Old versions of data and scripts are available. All previous versions of Data Packages are available at a stable URL on our data platform. The Jupyter Notebook scripts are versioned through GitHub.