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The data format of the results as published on the website hasn't changed significantly in comparison to OpenProblems v1. Each benchmark's outputs is eventually translated into json files named task_info.json, method_info.json, metric_info.json, results.json,
However, there are several issues with this format:
Naming inconsistencies: e.g. some columns have a prefix of the specific data type, e.g. metric info data has metric_id but also maximize
Does not allow for different parameterisations of datasets, methods, or metrics -- other than creating a unique id for each parameterisation. The normalisation_id is an exception to this, as this is effectively a parameterisation of the dataset processing steps and has a separate field in the results.
This only allows for very linear Dataset -> Method -> Metric graphs. However, several tasks involve many more steps in the processing:
In some tasks, running a method is split up into multiple steps in the form of a subworkflow. This results in it being harder to track the resources used to run a specific method
In the task_ist_preprocessing benchmark, it's not just one method being evaluation, but a combination of computational steps
There is more metadata available in the Viash components than is currently shown here. Look into which fields are missing.
All references should be updated to doi: string[]?, bibtex: string[]?.
The new data format should allow task leader to specify how the results should be rendered on the website by default. For instance, the task_spatially_variable_genes has too many datasets, thus making the default results heatmap hard to interpret.
Versioning of datasets, components (methods, metrics) and benchmarking results
The data format of the results as published on the website hasn't changed significantly in comparison to OpenProblems v1. Each benchmark's outputs is eventually translated into json files named
task_info.json,method_info.json,metric_info.json,results.json,classDiagram class TaskInfo{ task_id: String commit_sha: String? task_name: String task_summary: String task_description: String repo: String authors: Author[] } class MethodInfo{ task_id: String method_id: String method_name: String method_summary: String method_description: String is_baseline: Boolean paper_reference: String[]? code_url: String[] implementation_url: String? code_version: String? commit_sha: String? } class MetricInfo{ task_id: String metric_id: String metric_name: String metric_summary: String metric_description: String paper_reference: String[]? implementation_url: String? code_version: String? commit_sha: String? maximize: Boolean } class DatasetInfo { task_id: String dataset_id: String dataset_name: String dataset_summary: String dataset_description: String data_reference: String[]? data_url: String? date_created: Date file_size: Long } class Results { task_id: String dataset_id: String method_id: String normalization_id: String? metric_values: Map[String, Double | NA] scaled_scores: Map[String, Double] mean_score: Double resources: Resources } class Resources { exit_code: Integer duration_sec: Integer cpu_pct: Double peak_memory_mb: Double disk_read_mb: Double disk_write_mb: Double } class Author { name: String roles: String[] info: AuthorInfo } class AuthorInfo { email: String? github: String? orcid: String? } class QualityControl { task_id: String category: String name: String value: Double severity: Integer severity_value: Double code: String message: String } TaskInfo --> Author Author --> AuthorInfo Results --> Resources Results --> MetricInfo Results --> MethodInfo Results --> DatasetInfoHowever, there are several issues with this format:
metric_idbut alsomaximize