talk · Thursday 24 September · 09:35–⁠09:47 · FORUM

Canada’s need for synthesis for Adaptation and Resilience to Climate Change

James Macklin · Sustaining the Geo- and Biodiversity Data Ecosystem: Standards-Driven Approaches to Long-Term Resilience

Recording time 1:24:25–1:36:43Open on Vimeo ↗

Summaries and key moments are machine-produced. Check the recording for the speaker’s exact words.

The short versionGenomic data can only support climate adaptation synthesis if metadata are captured with standards from the start and linked to discoverable infrastructures like GBIF.

Overview

What this was about

James Macklin drew lessons from GenARCC, a large Canadian cross-departmental project using genomics to assess, predict and adapt to climate change, which will add about 20,000 whole genomes across 30 species largely from existing samples and specimens. He showed how the DINA research data management system captures standards-based metadata linked to material samples and sequences, and new pipelines push data semi-automatically to ENA and then associate ENA records with rich metadata in GBIF, compensating for poor metadata searchability in INSDC repositories. He stressed that relied-upon repositories carry funding risk, and that researchers undervalue the 'boring' work of connecting and standardising metadata needed for reuse and decision-ready results.

Why it matters. Environmental genomic data are growing rapidly, and the talk shows a practical pipeline (DINA to ENA to GBIF) for making sequence data findable while highlighting cultural barriers to reuse.

Key ideas

In the room

  • Public genomic data are estimated at 70+ petabytes; environmental metagenomics is a rapidly growing, highly diverse slice.
  • Canada has genome-level data for about 0.5% of its 80,000 species, biased toward economically and culturally important species.
  • GenARCC will add about 20,000 whole genomes across 30 terrestrial, marine and freshwater species, using existing samples via MTAs.
  • DINA captures a standards-based metadata snapshot with flexible managed attributes for terms not covered by standards.
  • About 740 salmon genomes were pushed from DINA to ENA via a semi-automatic pipeline.
  • INSDC repositories hold only core metadata searchably; a new workflow links ENA records to rich metadata in GBIF.
  • Researchers prioritise novel sequencing and analyses over metadata curation, reproducible code and reusable pipelines.
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Notable moments

In their words

Transcript

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Programme abstract

Canada’s need for synthesis for Adaptation and Resilience to Climate Change

James Macklin

The exponential growth of genomic data presents an unprecedented opportunity to mitigate the ecological impacts of climate change. Genomic data is estimated at 30 petabytes available publicly, with likely at least half as much unpublished. The Genomic Research and Development Initiative’s (GRDI) Genomic Adaptation and Resilience to Climate Change (GenARCC) will amass nearly a petabyte of data. Consequently, we may already have the raw genomic data required to address some of the most pressing ecological problems that can be solved using genomics.

To fully realize this potential, a paradigm shift towards systematic reuse of data and synthesis is essential. Synthesis centres have previously demonstrated the value of reanalyzing existing assets to accelerate discovery. This requires realigning incentives to prioritize data reuse over data generation such as by recognizing algorithms, associated pipelines and applications, and the data itself like long term scientific infrastructure. This involves standardization of data, processes, and products, which can only be realized by the community’s will and/or incentivized through funding-related obligations. With improved access and curation of shared scientific resources, researchers can develop novel data management architectures and leverage artificial intelligence, to integrate diverse datasets and reveal cross-system patterns of resilience that isolated studies overlook. To achieve this goal, future efforts should work towards FAIR data, and validation, maintenance, and automation of code and underlying algorithms. Together, these efforts can enhance how scientific data is shared and utilized in conservation and ecology. Prioritizing synthesis will ensure we get the highest return on our collective investment.

Submitted to the conference programme before the talk, so the talk itself may differ.