15 User Stories × Use Cases

How to read these columns

A ✓ means the story and the use case share a requirement.

User story	UC01	UC02	UC03	UC04	UC05	UC06	UC07	UC08
US-AD-01 As an ecologist, I want to adapt an existing indicator workflow to a new ecosystem type without rewriting the full analysis, so that I can reuse established methods and save weeks of rework. Satisfies: AD03	✓	✓				✓
US-AD-02 As a data analyst, I want to understand which parts of a workflow are ecosystem-specific vs generic, so that I know exactly what to change when switching context. Satisfies: AD01	✓	✓	✓			✓	✓
US-AD-03 As a government analyst, I want to switch the assessment purpose (e.g. risk to recovery) without needing a new workflow from scratch, so that I can serve multiple reporting needs with one underlying system. Satisfies: AD04	✓		✓			✓		✓
US-AD-04 As an ecologist, I want to receive guidance on reconciling global and local data sources for the same ecosystem, so that my workflow is defensible, reproducible, and transparent. Satisfies: AD05		✓
US-AD-26 As an RSE, I want each workflow structured as numbered, self-contained notebooks (e.g. 01-data-download, 10-data-preparation, 20-calculate-indicator), so that individual steps can be re-run or replaced without re-running the entire pipeline. Satisfies: AD01	✓	✓	✓			✓	✓
US-AD-27 As an RSE, I want a single workflow template (Quarto .qmd or R Markdown .Rmd) enforcing a consistent structure (metadata block, data sources, methods, outputs, known limitations), so that all workflows are comparable and cataloguable. Satisfies: AD03, RE01	✓	✓	✓	✓	✓	✓	✓	✓
US-AD-33 As an ecologist, I want workflows to calculate indicator values aligned to specific IUCN RLE criteria (A: extent decline; B: restricted distribution; C: abiotic condition; D: biotic condition), so that outputs are directly usable in risk assessment documentation. Satisfies: AD04, VO01	✓	✓	✓		✓	✓		✓

User story	UC01	UC02	UC03	UC04	UC05	UC06	UC07	UC08
US-RE-05 As a data scientist, I want to run a workflow developed by someone else on a new dataset without modifying the code, so that I can validate and replicate published assessments independently. Satisfies: RE06		✓	✓	✓		✓	✓	✓
US-RE-06 As a research software engineer, I want to containerise the workflow environment with pinned dependencies, so that software versions don’t break the workflow when R or packages change. Satisfies: RE04				✓
US-RE-31 As a platform administrator, I want each workflow to declare its software environment (R/Python version, package list with versions) in a machine-readable format (renv.lock or requirements.txt), so that the environment is reproducible anywhere. Satisfies: RE04				✓
US-RE-35 As a government reporting officer, I want each workflow run to produce a reproducibility record (timestamp, software environment snapshot, parameter values, input checksums), so that results can be independently verified. Satisfies: RE01, RE02, RE03	✓	✓	✓	✓	✓	✓	✓	✓
US-RE-38 As an RSE, I want each workflow registered in the indicator catalogue with a DOI and codemeta.json, so that workflows are citable as research software outputs. Satisfies: RE07				✓		✓

User story	UC01	UC02	UC03	UC04	UC05	UC06	UC07	UC08
US-VO-07 As an ecologist, I want to map local ecosystem classifications to global typologies (e.g. IUCN GET), so that my assessments align with international standards. Satisfies: VO02		✓			✓	✓
US-VO-08 As a data manager, I want a curated vocabulary mapping between national and global ecosystem classifications, so that others don’t have to reconcile it themselves each time. Satisfies: VO02, VO04		✓		✓	✓	✓
US-VO-09 As an indicator developer, I want vocabulary mapping to be machine-readable for workflow metadata, so that classification alignment can be automated rather than manual. Satisfies: VO04				✓
US-VO-10 As a policy officer, I want ecosystem types linked to authoritative identifiers (IBRA, IUCN GET IDs), so that reporting references are unambiguous and citable. Satisfies: VO03					✓	✓
US-VO-37 As an RSE, I want workflows to use GET vocabulary identifiers for ecosystem types in all metadata fields, so that outputs are semantically interoperable with other Australian and global ecosystem datasets. Satisfies: VO01, VO03	✓	✓			✓	✓		✓

User story	UC01	UC02	UC03	UC04	UC05	UC06	UC07	UC08
US-DD-11 As a platform user, I want to know where ecosystem distribution data comes from and when it was last updated, so that I can assess its fitness for purpose before committing to an analysis. Satisfies: DD02	✓	✓						✓
US-DD-12 As an analyst working with restricted data, I want to run the workflow within the platform where the data lives, so that I can comply with data governance requirements while still doing the analysis. Satisfies: DD05, AC04				✓				✓
US-DD-13 As a wetland ecologist, I want to integrate aerial survey data with satellite water extent time series, so that I can build a more complete picture of ecosystem condition. Satisfies: DD04					✓
US-DD-14 As a data scientist, I want guidance on transitioning from HPC preprocessing to cloud/local analysis, so that I’m not locked into one computing environment. Satisfies: DD05				✓				✓
US-DD-15 As a marine ecologist, I want to apply consistent indicator calculations across regions with uneven survey coverage, so that results remain comparable despite data gaps. Satisfies: DD03	✓				✓
US-DD-16 As an indicator developer, I want templates for harmonising heterogeneous survey datasets, so that I don’t rebuild harmonisation logic for every new workflow. Satisfies: DD03	✓				✓
US-DD-17 As a data analyst, I want clear documentation of data sources and known limitations embedded in each workflow, so that I can make informed fitness-for-purpose decisions before investing in an analysis. Satisfies: DD06					✓			✓
US-DD-24 As an ecologist, I want to access named datasets (DEA data cube, NARCliM2.0, TASVEG, CRU TS) via documented API calls or download scripts, so that data provenance is captured from the first pipeline step. Satisfies: DD01, RE02	✓	✓		✓	✓			✓
US-DD-25 As a data scientist, I want an assessment check for each input dataset, so that I know which datasets are ready for use and which require transformation before entering a workflow. Satisfies: DD02	✓	✓						✓

User story	UC01	UC02	UC03	UC04	UC05	UC06	UC07	UC08
US-DO-18 As a non-coder ecologist, I want step-by-step guidance with plain-language explanations at every stage, so that I can run the workflow without needing programming expertise. Satisfies: DO01	✓			✓		✓	✓
US-DO-19 As a mid-career data scientist, I want documentation explaining what each workflow function does and why it exists, so that I can modify components confidently for new use cases. Satisfies: DO04	✓		✓	✓		✓	✓
US-DO-20 As a senior scientist, I want documentation of how uncertainty is quantified and communicated in the outputs, so that I can defend the workflow’s results to government decision-makers. Satisfies: DO05, VA03	✓		✓		✓	✓	✓	✓
US-DO-21 As a workshop participant, I want worked examples covering common Australian ecosystem types, so that I can use the workflow as a template rather than starting from scratch. Satisfies: DO02						✓	✓
US-DO-22 As a team leader, I want training materials that accommodate different learning levels within the same team, so that everyone can contribute regardless of technical background. Satisfies: DO06							✓
US-DO-23 As a platform administrator, I want workshops supported by published, reusable data and code outputs, so that participants have concrete materials to reference after the session ends. Satisfies: DO03				✓		✓	✓
US-DO-29 As an RSE, I want each workflow to include a data flow diagram (.dot or Mermaid) showing inputs, transformation steps, and outputs, so that I can understand the pipeline structure before running or modifying it. Satisfies: DO04	✓		✓	✓		✓	✓
US-DO-34 As a government reporting officer, I want indicator outputs delivered as standardised tabular summaries (CSV with a defined column schema) and spatial layers (cloud-optimised GeoTIFF), so that I can ingest them into reporting pipelines without reformatting. Satisfies: DO07, AC05	✓				✓		✓	✓

User story	UC01	UC02	UC03	UC04	UC05	UC06	UC07	UC08
US-AC-30 As an ecologist, I want to run a workflow on EcoCommons (cloud notebook) and locally (R/RStudio or Python) without modifying any code, so that I am not dependent on a single platform. Satisfies: AC01, RE06		✓	✓	✓		✓	✓	✓
US-AC-32 As a platform administrator, I want compute and memory requirements specified per workflow, so that I can provision appropriate resources on Nectar or NCI without trial and error. Satisfies: AC07				✓
US-AC-39 As a government reporting officer, I want to access the catalogue and filter by ecosystem type (GET level), IUCN RLE criterion, or state/territory, so that I can identify available workflows for my reporting jurisdiction. Satisfies: AC06		✓	✓			✓		✓

User story	UC01	UC02	UC03	UC04	UC05	UC06	UC07	UC08
US-VA-28 As an ecologist, I want workflows to validate input data against minimum quality thresholds (spatial coverage, completeness, temporal resolution) before running calculations, so that invalid inputs are caught early with informative error messages. Satisfies: VA01	✓	✓	✓		✓			✓
US-VA-36 As an ecologist, I want indicator values to include uncertainty estimates where methodologically appropriate, so that outputs communicate confidence for decision-making contexts. Satisfies: VA03, VA05	✓				✓			✓

15.1 Coverage

Category	Stories	Use case links	Use cases covered
Adaptability	7	32	8
Reproducibility and transparency	5	18	8
Classification and vocabularies	5	15	6
Data discovery	9	22	5
Documentation and training	8	30	7
Accessibility	3	11	6
Validation	2	8	5

Status

Pending review.