# Interlinking Heterogeneous Data for Smart Energy Systems

## TL;DR

This paper presents a standardized approach using Web and Linked Data technologies to convert heterogeneous solar energy datasets into a unified RDF format, facilitating data integration and analysis across distributed sources.

## Contribution

It introduces a novel method for representing diverse PV and weather data as RDF graphs, enabling better interoperability and comparison of energy datasets.

## Key findings

- RDF conversion improves data interoperability.
- Facilitates distributed analysis of heterogeneous datasets.
- Supports comparison and reproducibility of energy data analysis.

## Abstract

Smart energy systems in general, and solar energy analysis in particular, have recently gained increasing interest. This is mainly due to stronger focus on smart energy saving solutions and recent developments in photovoltaic (PV) cells. Various data-driven and machine-learning frameworks are being proposed by the research community. However, these frameworks perform their analysis - and are designed on - specific, heterogeneous and isolated datasets, distributed across different sites and sources, making it hard to compare results and reproduce the analysis on similar data. We propose an approach based on Web (W3C) standards and Linked Data technologies for representing and converting PV and weather records into an Resource Description Framework (RDF) graph-based data format. This format, and the presented approach, is ideal in a data integration scenario where data needs to be converted into homogeneous form and different datasets could be interlinked for distributed analysis.