The rapid advancement of soft materials with integrated sensing capabilities finds applications in wearables, healthcare, and soft robotics. Soft sensors replicate human skin's ability to sense strain, force, temperature, and humidity, uniting robotics, materials science, and data science. Developing soft sensors poses challenges due to interlinked mechanical and sensing features, necessitating concurrent data reporting for improvement. To tackle this, accessible datasets are essential for comparing different sensors. Existing data collection methods, reliant on costly equipment and post-processing, impede progress. A low-cost 3D printer-based hardware solution is proposed to facilitate and encourage this open research data (ORD) practice. This project aims to contribute openly available hardware designs and software, enabling data curation aligned with ORD best practices. The goal is to ensure designs and software are discoverable under FAIR principles with easily updatable documentation. The software scripts will generate output data that complies with FAIR principles and best supports ORD practices. Another project aspect involves promoting these enabling technologies through participation in key workshops on 'open hardware.'