Mr Erin Kenna1
1CSIRO, Brisbane, Australia
Biography:
Erin Kenna is a data engineer and geographer with CSIRO Environment, specialising in the design and implementation of data systems that support environmental research and operational decision-making. With over 20 years of experience across government, private sector, and research institutions, Erin works across the data lifecycle—from field instrumentation and sensor integration to cloud-based workflows, metadata management, and research software development.
His expertise spans spatial data, data management, environmental monitoring, software development, and the use of open standards and vocabularies to support interoperable research systems. Erin focuses on building reproducible, scalable, and portable systems that bridge the gap between researchers, field teams, and end users. His work supports the transformation of research outputs into production-ready tools and services, enabling data sharing, discovery, and long-term reuse.
Abstract:
Supporting environmental instruments that are still under development presents challenges for research data workflows. This poster shares practical lessons learned from integrating water quality sensors into a cloud-based research infrastructure—while the instruments themselves continue to evolve.
The workflow spans from field deployment and data ingestion to metadata registration, calibration, post-processing models, access control, and cloud-based dissemination for research and dashboards. However, the reality of working with in-development instruments meant dealing with shifting data formats, incomplete metadata, evolving calibration routines, and uncertain operational requirements.
We present a visual workflow diagram that highlights key stages of the data lifecycle, annotated with real-world “pain points” and the adaptive strategies used to address them. These include modular design, metadata scaffolding, logging, and close collaboration with instrument developers (hardware and firmware).
This case study offers insights for the broader eResearch community on how to build resilient, FAIR-aligned data systems that can accommodate uncertainty and change. Our experience underscores the importance of flexibility, iteration, and communication in supporting the transition from prototype to production in environmental research instrumentation. It also highlights how thoughtful workflow design can enhance reproducibility, enable portability across projects and platforms, and support scalability as sensor networks and data volumes grow.