In the process of migrating data to the current DDL platform, datasets with a large number of variables required splitting into multiple spreadsheets. They should be reassembled by the user to understand the data fully. This is the second spreadsheet of two in the Feed The Future Interim Population-Based Assessment of Cambodia-Module E2, Non-food Expenditures Over Past 7 Days.

In the process of migrating data to the current DDL platform, datasets with a large number of variables required splitting into multiple spreadsheets. They should be reassembled by the user to understand the data fully. This is the fourth spreadsheet of five in the Feed The Future Interim Population-Based Assessment of Cambodia, Modules F-G, Hunger Scale and Women's Empowerment.

This dataset captures information about food shared with others during the 7 days before the survey from the first interim assessment of Feed the Future's population-based indicaors for the ZOI in Cambodia. It has 1019 rows and 14 columns. The ZOI is the Pursat, Battambang, Kampong Thom, and Siem Reap Provinces. The sampling design called for a two-stage cluster sample. In the first stage, 84 villages were selected; in the second stage, households were selected within each sampled village. The sampling of villages was stratified by province, with the number of villages in each stratum proportional to the population in the stratum and with villages selected with probability proportional to size, based on the 2013 Commune Database. The data is split into survey modules. Modules A through C includes location information, informed consent, and the household roster. Module D includes household characteristics. Module E is the expenditures module broken up into 8 different parts. Modules F and G include the hunger scale data and WEIA index data. Data in modules H and I include mother and child dietary diversity.

This dataset captures the non-food expenditures over the past 7 days for each household surveyed during the first interim assessment of Feed the Future’s population-based indicators for the ZOI in Cambodia. It has 1019 rows and 579 columns. The ZOI is the Pursat, Battambang, Kampong Thom, and Siem Reap Provinces. The sampling design called for a two-stage cluster sample. In the first stage, 84 villages were selected; in the second stage, households were selected within each sampled village. The sampling of villages was stratified by province, with the number of villages in each stratum proportional to the population in the stratum and with villages selected with probability proportional to size, based on the 2013 Commune Database. The data is split into survey modules. Modules A through C includes location information, informed consent, and the household roster. Module D includes household characteristics. Module E is the expenditures module broken up into 8 different parts. Modules F and G include the hunger scale data and WEIA index data. Data in modules H and I include mother and child dietary diversity. In the process of migrating data to the current DDL platform, datasets with a large number of variables required splitting into multiple spreadsheets. They should be reassembled by the user to understand the data fully.

Helping Address Rural Vulnerabilities and Ecosystem Stability (Cambodia-HARVEST) was a five-year program (2011-2016) supported under the Global Hunger and Food Security Initiative (GHFSI) and the Global Climate Change (GCC) and Biodiversity program. Cambodia-HARVEST set strategic goals to improve food security, strengthen natural resource management and resilience to climate change, and increase the capacity of the public and private sectors and civil society to support agricultural competitiveness. Implemented in four targeted provinces of Cambodia -- Kampong Thom, Siem Reap, Pursat, and Battambang -- Cambodia-HARVEST had five major components: Agribusiness Value Chains; Aquaculture and Fisheries; Natural Resource Management; Biodiversity, and Climate Change, Social Inclusion, Business Development Services; and Capacity Development. Cambodia-Harvest worked with local partners and government to initiate policy reforms and eliminate obstacles to development. This data asset enables the evaluation of the program. It is comprised of a baseline, endline and community level survey. This is the endline survey.

Feed the Future Nepal Interim Survey in the Zone of Influence: This dataset (n=800, var=163) is the first of two datasets needed to calculate the WEAI-related measures. It is a household-level file and contains the records for Module G data from the primary adult (18+) female decisionmaker within each household (for the sub-sample of households with a primary adult female decisionmaker).

Feed the Future Zambia Interim Survey in the Zone of Infuence: This dataset (n=13,203, vars=111) is the second of two datasets needed to calculate the WEAI-related measures. It includes the 24-hour time allocation data from Module G6, the time use module, and thus each respondent on Module G has multiple records, one for each of the 18 time use activities (13,301 records divided by 18 activities = 739 Module G respondents with time use data in the file.)

본 데이터는 2025년 기준 고창군 읍·면별 영양플러스사업 수혜인원 현황을 집계한 자료로, 각 행정구역별 영양플러스사업 수혜 규모를 파악할 수 있도록 제공됩니다. 데이터는 읍·면 단위로 영양플러스사업에 참여하는 수혜 인원 수를 기준으로 구성되어 있으며, 지역별 영양지원 수요 분석 및 모자보건 정책 수립을 위한 기초자료로 활용할 수 있습니다.데이터 구성은 연번, 행정동, 영양플러스사업 수혜인원 항목으로 이루어져 있으며, 행정구역별 수혜 인원 현황을 확인할 수 있습니다. 해당 자료는 보건사업 수행 과정에서 집계된 행정자료를 기반으로 작성되었습니다.본 데이터는 지역별 영양취약계층 분포를 공시적으로 분석하거나, 특정 지역의 영양지원 수요 변화를 파악하는 데 활용할 수 있습니다. 또한 공공데이터를 활용하여 다음과 같은 분석 및 연구에 활용이 가능합니다.단순 예시 사례이니 참고 바랍니다.○ 지역별 분포 분석: 읍·면별 영양플러스사업 수혜인원 현황을 통해 지역 간 영양지원 수요 차이를 파악하고 정책 수립에 활용할 수 있습니다.○ 수혜 대상자 규모 파악: 영양플러스사업 참여 인원 규모를 분석하여 향후 지원 계획 수립에 활용할 수 있습니다.○ 취약계층 영양지원 분석: 임산부 및 영유아 등 대상자 분포를 기반으로 영양지원 사각지대 해소를 위한 기초자료로 활용할 수 있습니다.

이 데이터는 충청남도 금산군의 대표적 특산물인 인삼에 대하여, 정확한 통계를 기초로 하는 통합정보관리 체계를 구축함으로써 효율적인 관리와 합리적인 의사 결정을 지원하고자 2023년도에 실시한 "농업유산 보전관리를 위한 인삼재배정보 DB 현행화" 조사의 인삼경작지 현황 데이터로 읍면별, 행정리별, 지목별, 경작연도별 경작면적(ha)와 실제면적(ha)에 대한 데이터를 제공합니다. 본 데이터는 고부가가치 약용작물인 인삼 산업의 기초자료로 활용되어, 인삼의 재배 추세 분석, 농가 경영계획 수립, 정책적 지원 근거 마련 등에 중요한 역할을 합니다. 또한 지역별 재배 특성, 면적 변화 추이를 비교·분석함으로써 인삼산업의 지속가능한 발전 전략 수립, 수급 안정화 및 수출 경쟁력 강화에 기초자료로 활용될 수 있습니다.