{"query_echo":{"q":"","filters":{"analysis_type":["dataset documentation"]},"warnings":[{"code":"facet_value_not_in_vocabulary","message":"Value 'dataset documentation' for facet 'analysis_type' is not in the controlled vocabulary."}]},"total":{"value":2,"relation":"eq"},"page":1,"page_size":20,"self":"https://climateinsightsdirectory.org/api/v1/search?analysis_type=dataset+documentation","stability":"beta","ai_marking":{"digital_source_type":{"uri":"http://cv.iptc.org/newscodes/digitalsourcetype/trainedAlgorithmicMedia","name":"Created using Generative AI"},"notice":"Summary and key insights are generated using artificial intelligence."},"results":[{"id":"prio-001320","url":"https://climateinsightsdirectory.org/document/prio-001320","title":"THE DIAMOND DATASET CODEBOOK","publisher":{"name":"Peace Research Institute Oslo","organization":"peace-research-institute-oslo"},"document_type":"guide","language":"en","date_published":null,"source_url":"https://cdn.cloud.prio.org/files/3600c16d-1c66-42c0-bcf7-8b3733acca5b/DIADATA Codebook.pdf?inline=true","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","geography_discussed","analysis_type"],"summary":{"text":"The document describes the DIADATA dataset, which lists diamond occurrences worldwide, including geographic coordinates, geological forms, and dates of discovery and production. It details the data collection process from academic, governmental, and industry sources, and explains the coding structure for variables such as geological form (primary, secondary, or marine) and production status. Additionally, it describes a 'compact version' of the dataset where sites within 50 km are aggregated into multipoints to reduce missing temporal data. The document includes detailed country profiles for 53 countries, outlining their diamond discovery and production histories.","ai_generated":true,"unit":"prio-001320#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The DIADATA dataset contains 1,175 entries for diamond occurrences across 53 countries, with 33 of those countries having some form of production.","ai_generated":true,"unit":"prio-001320#insight-1","date_modified":"2026-10-23"},{"text":"To address missing discovery and production dates in the original dataset, a compact version was created by aggregating sites within 50 km into multipoints, which significantly improved the completeness of temporal data.","ai_generated":true,"unit":"prio-001320#insight-2","date_modified":"2026-10-23"},{"text":"Data collection relied on a variety of sources, including the GeoRef database, the USGS Minerals Yearbook, the Mineral Resource Data System (MRDS), and the commercial database Infomine.","ai_generated":true,"unit":"prio-001320#insight-3","date_modified":"2026-10-23"},{"text":"The authors identify several biases in the data, including the falsification of records and the unwillingness of some countries to disclose information, particularly in conflict-affected regions like Angola, Sierra Leone, Liberia, and the Democratic Republic of Congo.","ai_generated":true,"unit":"prio-001320#insight-4","date_modified":"2026-10-23"},{"text":"The dataset distinguishes between 'lootable' (secondary) and 'non-lootable' (primary) diamonds, a distinction used to generate specific subsets for conflict research.","ai_generated":true,"unit":"prio-001320#insight-5","date_modified":"2026-10-23"}],"climate_tags":[],"geography_discussed":["Angola","Australia","Botswana","Brazil","Canada","Central African Republic","People's Republic of China","Democratic Republic of the Congo","Ghana","Guinea","Guyana","India","Indonesia","Lesotho","Liberia","Namibia","Russia","Sierra Leone","South Africa","Tanzania","United States","Venezuela","Zimbabwe"],"frame_perspective":[],"analysis_type":["dataset documentation","methodological guide"]},{"id":"prio-001849","url":"https://climateinsightsdirectory.org/document/prio-001849","title":"Water-Related Intrastate Conflict and Cooperation (WARICC): A New Event Dataset Codebook","publisher":{"name":"Peace Research Institute Oslo","organization":"peace-research-institute-oslo"},"document_type":"guide","language":"en","date_published":null,"source_url":"https://cdn.cloud.prio.org/files/4a847ac9-c852-4955-8741-e5f601a6626a/WARICC codebook v10.pdf?inline=true","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The WARICC codebook details the construction of a dataset designed to analyze the frequency and intensity of domestic water-related conflict and cooperation. Using BBC Monitoring as its primary source, the project employs an 11-point Water-Events Scale (WES) to categorize events from substantial national improvements (+5) to overt physical violence or national deterioration (-5). The methodology addresses potential data biases related to urban areas, regime types, and extreme events, while providing a comprehensive system of country and actor codes for standardized reporting.","ai_generated":true,"unit":"prio-001849#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The dataset focuses on the time-period 1997–2009 and covers all riparian countries of the Mediterranean Sea and all countries in the Sahel.","ai_generated":true,"unit":"prio-001849#insight-1","date_modified":"2026-10-23"},{"text":"The researchers selected BBC Monitoring over Factiva as the primary news source because Factiva produced an unmanageable volume of irrelevant hits and exhibited language bias due to limited translation of foreign-language articles.","ai_generated":true,"unit":"prio-001849#insight-2","date_modified":"2026-10-23"},{"text":"The Water-Events Scale (WES) is an 11-point system where +5 represents substantial national improvements in water quality or quantity, and -5 represents national-level deterioration or physical violence over water resources.","ai_generated":true,"unit":"prio-001849#insight-3","date_modified":"2026-10-23"},{"text":"The methodology identifies three primary sources of potential data error: urban bias (over-reporting of high-density areas), regime type bias (state censorship in non-democratic regimes), and extreme event bias (disproportionate coverage of very large projects or severe conflicts).","ai_generated":true,"unit":"prio-001849#insight-4","date_modified":"2026-10-23"},{"text":"The dataset distinguishes between the source level of action (scale) and the target level of action (impact), ranging from grass-roots individuals (1) to national governments (4).","ai_generated":true,"unit":"prio-001849#insight-5","date_modified":"2026-10-23"}],"climate_tags":["water management","climate change","water quality"],"geography_discussed":["Spain","Ethiopia","Albania","North Macedonia","Gaza Strip","Somalia"],"frame_perspective":[],"analysis_type":["methodology","dataset documentation"]}]}