Open water-data platforms can make monitoring information easier to find, combine, and use, but open access alone does not establish policy value. This study compares the Hamilton Harbour and Toronto and Region Areas of Concern (AOCs), using Great Lakes DataStream as the common open-data infrastructure examined across the two cases. We extracted DataStream data for these two cases, reviewed their spatial and temporal coverage, mapped frequently monitored parameters to AOC policy responsibilities, and held practitioner workshops in Hamilton and Toronto to gain insights into both contributions and use related to water policy priorities. The Hamilton extract contains 233,634 observations from 11 datasets, 226 monitoring-location identifiers, and 138 unique characteristics. The Toronto regional extract contains 841,785 observations from 21 datasets, 623 location identifiers, and 109 unique characteristics. Government water quality monitoring programs provide most records in both extracts, although the Royal Botanical Gardens has a substantial place-based role in Hamilton and community and partnership programs add localized coverage in Toronto. The parameters are relevant to nutrient, habitat, sediment, salinity, contaminant, and recreational-water questions. Workshop participants, however, indicate that routine use of open data through DataStream was limited in AOC reporting and decisions. They identified incomplete awareness, uneven metadata, analytical capacity, uncertainty about quality-assurance responsibilities, and the absence of formal links to policy workflows as practical constraints. The findings indicate it is important to distinguish data availability and policy relevance from documented policy use. DataStream improves discoverability and interoperability but stronger policy integration is required with clear alignment with AOC monitoring needs, transparent information about methods and quality, and continuing collaboration among public agencies, Indigenous partners, community organizations, and academic researchers.
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Saadi et al. (2026) studied this question.
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