Oral Presentation Australian Society for Fish Biology & Australian Freshwater Sciences Society Conference 2026

Reconstructing legacy data to support ecohydrological analysis of long-term datasets and water management (142320)

Patrick D Driver 1 , James Petrovic 2 , Jennifer Kirton 3 , Alison Specht 4
  1. Surface Water Science, NSW Department of Climate Change, Environment & Water, Orange, New South Wales, Australia
  2. Corporate & Enabling Services - Data Administration, NSW Department of Climate Change, Environment & Water, Wollongoing, NSW, Australia
  3. Corporate & Enabling Services - Library, NSW Department of Climate Change, Environment & Water, Wollongbar, New South Wales, Australia
  4. University of Queensland., Brisbane, Queensland, Australia

This work is a collaboration across science, data administration, and library functions within the NSW Government, Australia, focused on developing a framework for the recovery, standardisation, documentation, and reuse of historical ecological data. Using datasets from the Integrated Monitoring of Environmental Flows (IMEF) program, a former long‑term ecological monitoring program in regulated river systems, as a case study, including Macquarie Marshes vegetation monitoring (2000–2010) and flow–algal bloom datasets from the Barwon–Darling and Gwydir systems (NSW DCCEEW, 2026, a–c), the approach combines data recovery and archival reconstruction with structured data curation. This includes making associated reports, previously unpublished or difficult to access, available alongside datasets, restoring critical context required for reuse.

A key feature of this work is the contrast in interpretability across datasets. The algal bloom datasets were fragmentary and poorly documented, requiring substantial effort to reconstruct context, interpret structure, and develop supporting metadata (NSW DCCEEW, 2026, b). This involved linking disparate files and inferring sampling design and analytical intent from incomplete documentation. Despite this, some contextual information may remain missing, limiting reuse. In contrast, with the Macquarie Marshes vegetation dataset, familiarity with original data collection enabled high-confidence reconstruction (NSW DCCEEW, 2026, a), and has been provided to supporting Flow‑MER activities.

These activities adopt open science practices beyond jurisdictional policy, drawing on Belmont Forum DDOMP guidance, which treats data management as a full lifecycle process (Stall & Specht, 2025). While reuse is increasingly expected, this work demonstrates it is neither simple nor time-light, requiring substantial effort to reconstruct context, restore documentation, and structure data for analysis.

References
NSW DCCEEW (2026, a–c). IMEF datasets published via SEED (Macquarie Marshes vegetation; Barwon–Darling and Gwydir algal bloom datasets).
Stall, S., & Specht, A. (2025). Belmont Forum Data and Digital Outputs Management Plan (DDOMP): Course introduction. AGU & TERN.