Inventory Database for Environmental Analysis (IDEA)

IDEA, which stands for "Inventory Database for Environmental Analysis", is the standard equipment inventory database for MiLCA LCA software. 3000 datasets are available in both gate to gate and cradle to gate type

Summary
Name of source	IDEA
Provider	AIST/JEMAI
Summary text	IDEA is the standard equipment inventory database for MiLCA LCA software. IDEA, which stands for "Inventory Database for Environmental Analysis" has been jointly developed since FY2008 by the National Institute of Advanced Industrial Science and Technology (AIST) and Japan Environmental Management Association for Industry (JEMAI). 3000 datasets are available in both gate to gate and cradle to gate type.
Contact	[e-mail]
Licensing	Free in MiLCA software
Language(s)	English/Japanese
Website	http://www.milca-milca.net/ download-files/MiLCAguidebook_En.pdf

Access – data formats and accessibility
File type	IDEA format (based on ISO TS 14048)
Software needs	MiLCA

Contents – breadth and depth of datasets
Age	Released in 2010
Geography	Global
Original Data Source(s)	Made from Japanese and global statistics, modeling of production process and industry associations
Other Databases Included
Life cycle stages	All
Modeling approach	Attributional approach
Emissions results	GHGs and about 50 elementary flows
Number of datasets	Approx. 3000
Main topics	Agriculture and fisheries, mining, construction and civil construction and other non-manufacturing, food and beverages, textiles, chemicals, ceramics and building materials, metals, machinery, and other manufacturing, electricity gas, water and sanitation, etc.
Other topics

Data transparency – what metadata is provided for each dataset?
System boundaries	From cradle to grave
Data Types	Gate to Gate and Cradle to Gate
Allocation Methods	Mass based allocation is basically used
Technology	Current
Data year	2000 to 2010
Original source
Uncertainty	Depends on dataset. Each dataset is evaluated by modified pedigree matrix.

Quality – is information provided on data quality?
Data quality score
Quality assurance	Internal review
Standards compliant	Based on ISO 14040/14044