Industrial ecology data commons (IEDC) data template validator
Validate your data formatting and classifications against a general standard
Datasets in industrial ecology and socio-metabolic research typically have between 1 and 10000 data points and are frequently stored in xlsx spreadsheets. The industrial ecology data commons (IEDC) offers a general data model, a set of classifications,
and spreadsheet templates to consistently format such data in order to facilitate data updating, archiving, and exchange across projects.
The IEDC data model and formatting standard requires datasets to properly formatted, including a consistent description of the data, sufficient metadata,
a proper formatting of the data themselves, and the use of consistent classifications.
This page provides a web-based tool to validate datasets formatted as spreadsheets against the IEDC data model, data formatting, and classifications.
Detailed info on the data model can be found on the https://www.database.industrialecology.uni-freiburg.de/.
The following material is available: a working example for list-shaped data 3_LT_Vehicles_LIST_Sample.xlsx,
and an example for list-based data with multiple errors included 3_LT_Vehicles_LIST_Sample_Errors.xlsx;
a working example for table-shaped data 3_MC_VehicleArchetypes_TABLE_Sample.xlsx,
and an example for table-based data with multiple errors included 3_MC_VehicleArchetypes_TABLE_Sample_Errors.xlsx.
A tutorial video https://youtu.be/XcUBUaWhKUc shows how to format the data according to the IEDC specifications and how to use the data template validator.
Note: When formatting your data to the IEDC format, please make an effort to use labels for materials, products, regions, etc. that are already defined in one of the IEDC classifications
listed on the https://www.database.industrialecology.uni-freiburg.de/classifications.aspx.
In particular, wherever possible with reasonable effort, please use the following classifications: 1 (chemical_elements) for chemical elements, 2 (regions_iso_iedc) for countries,
3 (time (list of years)), 14 (time_ranges (list of different time ranges)) for time, 4 (generic_materials_waste) for materials, 6 (broad_industry_groups) for processes,
7 (general_product_categories) for commodities and products, 10 (general_energy_carries) for different types of energy,
20 (LCI_data_layers) for indicating the layer of measurement in the ‘layer’ aspect, and 8 (basic_scenario_alternatives) for indicating different scenarios.