Distributed Data Infrastructures in Energy Systems Analysis

Abstract

Modeling in energy systems analysis needs a lot of data from a variety of different sources: Meteorological time series for renewable power generation, electricity demand from the transparency platforms, technology data, socio economic data, etc. The first step in modeling is usually a longer research exercise in data gathering. There are a lot different sources available, but they are sometimes hard to find and each has different ways of accessing the data and different ways how data fields are defined. Similar problems arose in earth observation about two decades ago. The answer was the development of a distributed data infrastructure for Earth Observation data, the Global Earth Observation Systems of Systems (GEOSS). Data could be found through data catalogs, where providers registered their metadata and ways of data access could be discovered though standardized interface descriptions as e.g. WSDL (Webservice Description Language). For energy systems analysis we want to learn from this experience and started a project for the development of a distributed data infrastructure for energy systems analysis. The project is about the development of networked data base concept based on the ideas of linked open data and the semantic web for input and output data of energy system models in energy systems analsis