Energy system models are vital for planning the transition of energy systems. Conversion and storage technologies are major model building elements and their parameterization impacts the model results significantly. Sill technology data is often scattered, inconsistent, and hard to trace. Researchers currently spend significant time manually adapting parameters from reports, databases, and model-specific files making the process slow, error-prone, and difficult to reproduce. The MOTEL project tackled this challenge by developing a structured workflow to collect, and share open technology data for energy models. We created a prototype workflow that transforms raw data into harmonised, linked records, connecting technology parameters to their sources and assumptions. These records are then mapped to ontologies (standardised frameworks for organising information), enabling seamless integration into knowledge graphs and downstream applications. By the end of the project, MOTEL had delivered a functional prototype with an end-to-end workflow from raw data to a web-based interface allowing users to explore, compare, and reuse technology assumptions transparently. This work demonstrates how open research data can improve the transparency, interoperability, and reproducibility of energy system models. The methods and tools developed can be extended to include more technologies, additional ontologies, and richer validation processes, supporting future model-ready applications. Planned next steps include internally testing this workflow across different projects, followed by efforts to encourage broader use by the research community.