Over much of Ireland, long-term sea-level records are limited, yet a wealth of historical data exists in archives, often as paper marigrams. This thesis recovered, digitised, and integrated selected historical marigrams to produce a robust national dataset for assessing mean sea-level (MSL) change and coastal vulnerability. Data rescue focused on methodological accuracy, correcting distortions in paper charts—bends, skews, and grid misalignments—that could bias digitised records. Using Dún Laoghaire (1925–1931) as a case study, a correction framework quantified offsets between digitised traces and underlying grids at hourly intervals, improving accuracy to 1 cm, consistent with Global Sea Level Observing System standards. Validation against independent historical surveys and modern observations confirmed that tidal amplitudes, phase lags, and mean sea levels were accurately reproduced within expected observational uncertainties. Building on this foundation, a structured training framework enabled students and citizen scientists to contribute high-quality digitised data, with case studies highlighting common error sources and quality assurance measures. This method is applicable to students, citizen scientists, and educators, and may facilitate future machine-learning development, currently limited by the complex visual nature of marigrams. The thesis’ central contribution is the first nationally consistent reconstruction of MSL change across Ireland from 1925 to 2024, achieved by integrating newly digitised southwestern records with existing datasets. Regional variability was identified, with long-term mean modelled instantaneous rates ranging from 0.40 mm yr⁻¹ at Belfast in the north to 3.29–3.59 mm yr⁻¹ at Cork and Tarbert in the south and southwest. The regional mean modelled instantaneous sea-level rise rate over 1925–2024 was 2.30 ± 0.29 mm yr⁻¹ (95% CrI: 1.72–3.01). Modelled instantaneous sea-level rates accelerated after 2000, exceeding 4 mm yr⁻¹ and reaching ~6–7 mm yr⁻¹ by 2024 at several sites. Residual uncertainties from observational gaps, digitisation errors, and short-term variability were quantified using Bayesian credible intervals—a statistical method providing a range of plausible values for sea-level trends. By combining historical data rescue, correction methods, and Bayesian modelling, this thesis provides a nationally consistent framework for reconstructing sea-level change. This framework supports citizen science and adaptation planning, while placing Ireland’s sea-level trends in a global context.