Environmental Law and Climate Change

This dataset compiles structured information on climate litigation cases and associated analytical variables used in the study. The data are organized into two main files: an Excel dataset (Complete_Data.xlsx) and a CSV dataset (climate_litigation_results.csv). Together, they provide a comprehensive representation of the variables, classifications, and analytical outputs derived from the systematic review and/or empirical analysis conducted.

The dataset includes variables related to case identification, jurisdiction, legal basis, actors involved, litigation type, outcomes, and temporal characteristics. Additionally, derived variables are incorporated to support statistical analysis, trend identification, and comparative evaluation across cases and regions. Each observation corresponds to an individual litigation case or analytical unit, depending on the structure defined in the study.

The Excel file (Complete_Data.xlsx) contains the primary dataset, including raw and processed variables. It is structured in tabular format with clearly labeled columns representing categorical, ordinal, and numerical variables. The CSV file (climate_litigation_results.csv) includes processed outputs, such as summarized indicators, statistical results, or filtered datasets used for reporting and visualization purposes.

Data collection was conducted through systematic identification of relevant cases using predefined inclusion and exclusion criteria aligned with the study objectives. Sources may include legal databases, institutional repositories, and academic literature. Data cleaning and preprocessing involved standardization of categories, removal of duplicates, and verification of data consistency.

All variables are documented to ensure reproducibility. Missing values are explicitly indicated, and categorical variables follow consistent coding schemes. The dataset is suitable for replication, secondary analysis, and comparative research in climate law, public policy, and environmental governance.

The data are provided in open formats (XLSX and CSV) to facilitate accessibility and interoperability. No personal or sensitive data are included. The dataset complies with ethical research standards and is intended for academic and non-commercial use.