cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.60507/fk2/lfs5vy
title: Survey on WATSAN in Fogera and Mecha districts of Amhara regional state, Ethiopia, 2014

description: The WATSAN module questionnaire was used to collect information on characteristics of housing, water supply sources, continuity of water supply and seasonal change, water storage, handling and treatment, community management, toilet facility, waste management, and irrigated agriculture practices.
description: This dataset was first published on the institutional Repository "Zentrum für Entwicklungsforschung: ZEF Data Portal" with ID={0e44207e-b0d1-4ef2-8766-73b928c1fa8d}.
DOI: 10.60507/fk2/kzojdg
title: Crop calender of Maize & Cassava in Ghana, 1950-.2005

description: The table includes sowing, harvesting dates, sowing/planting rates of Maize and Cassava in different Agro-ecological zones in Ghana.

Quality/Lineage: FAO (http://www.fao.org/agriculture/seed/cropcalendar/welcome.do).
description: This dataset was first published on the institutional Repository "Zentrum für Entwicklungsforschung: ZEF Data Portal" with ID={76b09d89-d60f-4d4b-83ad-cc82b4321377}.<br>
Spatial resolution: zonal
DOI: 10.60507/fk2/bbp6gg
title: Probability of Habitat Suitability for Stem Borer Pests and Natural Enemies in Kenya and Tanzania Under Current Climatic Conditions (1970-2000) and Different Climate Change Scenarios (2041-2060, 2081-2100)

description: The research within the scope of which the presented data was generated was part of the funding initiative ‘Knowledge for Tomorrow-Cooperative Research Project in sub-Saharan Africa on Resource, their Dynamics, and Sustainability’ funded by the Volkswagen Foundation. The overall study aimed at investigating the uncertainties in the effectiveness of biological control of stem borers under different climate change scenarios in Kenya and Tanzania. Using the species distribution modelling approach MaxEnt, the research predicts the current and future distribution of three important lepidopteran stem borer pests of maize in eastern Africa, i.e., Busseola fusca (Fuller, 1901), Chilo partellus (Swinhoe, 1885) and Sesamia calamistis (Hampson, 1910), and two of their parasitoids used for biological control, i.e., Cotesia flavipes (Cameron, 1891) and Cotesia sesamiae (Cameron, 1906). Based on these potential distributions and data collected during household surveys with local farmers in Kenya and Tanzania, future maize yield losses are predicted considering three different Global Circulation Models (GCMs) for four different Shared Socioeconomic Pathway (SSP) scenarios (SSP1-2.6, SSP2-4.5, SSP 3-7.0, SSP5-8.5) and two time periods, i.e., 2041-2060 and 2081-2100. 
A raster in which probability of habitat suitability is separately specified for each grid cell is the immediate output from species distribution modelling with MaxEnt. Probability of habitat suitability for the respective species hereby is expressed as probability value ranging between 0 (unsuitable habitat) to 1 (perfectly suitable habitat). Probability of habitat suitability was modelled for five species for current climatic conditions, as well as for four SSPs and two time periods.

Quality/Lineage: The generated data is based on a collection of presence points from different sources and environmental data from WorldClim. Species Distribution Models (SDMs) have been built using the 'kuenm' package in RStudio. The data on probability of habitat suitability are an immediate output from SDM in R. Habitat suitability is here given as multi-model average of predictions for three Global Circulation Models (GCMs) from CMIP6: CanESM5, CNRM-CM6-1 and MIROC6
description: Version 6.2 (Build 9200) ; Esri ArcGIS 10.7.1.11595
description: This dataset was first published on the institutional Repository "Zentrum für Entwicklungsforschung: ZEF Data Portal" with ID={36105b57-ae76-4433-b0ea-8b224af13ac4}.<br>
The naming of files follows the syntax: first letter species name_SSP_time period_mme average (= multi-model ensemble average)
DOI: 10.60507/fk2/bnomsu
title: Follow-up survey on under-five children in Fogera and Mecha districts of Amhara regional state, Ethiopia, 2014

description: The follow-up surveys were administered between April and July 2014 after completing the baseline survey by the end of March 2014. The aim of the survey was to collect information on under-five children heath status—such as diarrhea, fever, vomiting, constant cough, stomach pain/cramps and skin infections in the preceding two weeks. This data collection process requires multiple successive visits to the households, and each household has been visited every fortnightly for a period of three months to record the health status of the children. For this purpose, one-page child health calendar questionnaire was developed to record information about symptoms of a particular illness; how long the symptoms stay; and what treatment they seek for if any. The data collection was done by health and agriculture extension workers who work in the selected kebeles. Training was given to the enumerators during the field organization for the follow-up household survey. In most cases, the data collectors ask the child’s primary caretaker—usually the mother or another adult woman household member.

Purpose: To examine the longitudinal diarrheal prevalence among under-five children in the study areas.
description: This dataset was first published on the institutional Repository "Zentrum für Entwicklungsforschung: ZEF Data Portal" with ID={39c8886d-9388-48a8-b02a-0436113d1577}.
DOI: 10.60507/fk2/asxjsh
title: Marginality Hotspots and Poverty Mass in Sub-Saharan Africa, 2005-2010

description: This map is included in a global study on mapping marginality focusing on Sub-Saharan Africa and South Asia. The Dimensions of Marginality are based on different data sources representing different spheres of life. The dataset used for this approach (Marginality Hotspots) can also be found here: (link to datasett???). Five different dimenstion of marginality were defined and based on their thresholds overlayed to identify those areas where more than only 1 or 2 dimensions occur but several once which make these areas more marginal. With regard to the project MARGIP especially those people are at risk who are marginalized and poor and are thereby lacking possibilities due to missing access to capital and resources but also by being remote. The number of poor are the once we want to make visible. Therefore data by HarvestChoice on Poverty Mass representing the number of people living in poverty were overlayed with dimensions of marginality to give an impression on how many people are living in these spots and are thereby being poor and marginal.
See also:
http://www.zef.de/fileadmin/webfiles/downloads/zef_wp/wp88.pdf .

Quality/Lineage: Poverty Data was provided and generated by Harvest Choice GIS lab. Marginality hotspots are based on the approach by Graw, V. using five dimensions of marginality. 
In ArcGIS thresholds were defined based on percentages and overlapping dimensions. Using raster data this data was reclassified and overlayed to build a new classification with regard to the here presented purpose.
description: This dataset was first published on the institutional Repository "Zentrum für Entwicklungsforschung: ZEF Data Portal" with ID={edee879a-5e3e-40b0-aa18-1f33d9fba015}.<br>
Marginality Dimensions
I. Economy (GNI)
II. Quality of Life (Stunting)
III. Landscape Design (Accessibility)
IV. Ecosystems (Soil Constraints)
V. Governance (Political Stability)
DOI: 10.60507/fk2/yyfnjb
title: A Holistic Sustainability Assessment of Smallholder Farms in Kenya, 2016 - Dataset 1

description: In our research we assess the sustainability performance of 400 smallholder farms practicing organic (i.e. certified or non-certified) and non-organic agriculture (i.e. conventional or other) using the Sustainability Monitoring and Assessment RouTine (SMART)-Farm Tool and examine differences between these farm categories using multivariate analyses. We also identify general gaps in sustainability performance for all farms.
Murang'a County, Kajiado County.

Quality/Lineage: Multivariate data analyses
Purpose: The results are important to provide a basis for informed decision-making in design of future policy measures and other interventions aiming at sustainable smallholder farming which is significant for sustainable development in Kenya and other countries of sub-Saharan Africa.
description: This dataset was first published on the institutional Repository "Zentrum für Entwicklungsforschung: ZEF Data Portal" with ID={b3ac7dec-d1e8-40c6-a905-45e09d040dd8}.<br>
Sustainability Assessment of Food and Agriculture systems (SAFA) dimensions, themes, subthemes and author derived variables.
DOI: 10.60507/fk2/jy93ey
title: High Potential Areas for Agricultural Development in Kenya, 2005, 2006

description: Using the methodology developed by Graw and Husmann (2014), the map overlays three indicators (high agricultural potential, high poverty mass and high yield gaps) to identify areas with high potential for agricultural development and poverty reduction in Kenya.

Data sources and thresholds:

Agricultural potential: Suitability of currently available land area for rainfed crops, using maximising crop and technology mix, FGGD map 6.61 (2005), High: top 3 suitability classes (medium high, high and very high) 
Poverty mass: Number of poor people in Kenya (by district), KIHBS (2005/06), High: &gt;300,000 per district 
Yield gap: Yield gap for a combination of major crops, FAO/IIASA - GAEZ (2000/05), High: &lt; 0.25 (on a scale from 0-1, with the highest value in Kenya ca. 0.44) 
District boundaries: Kenya Central Bureau of Statistics (2003)

Purpose: The map was generated for PhD research. The dissertation is available online:

Baumüller, H. 2015. Agricultural innovation and service delivery through mobile phones: Analyses in Kenya. Thesis at Faculty of Agriculture, University of Bonn. http://hss.ulb.uni-bonn.de/2015/4046/4046.htm.
description: This dataset was first published on the institutional Repository "Zentrum für Entwicklungsforschung: ZEF Data Portal" with ID={441ec051-f066-4129-ac8e-129fb53eb5a8}.
DOI: 10.60507/fk2/jy93ey/6cbyrd
title: metadata.xml
DOI: 10.60507/fk2/jy93ey/zpuxym
title: Kenya_highpotentialareas.lpk
DOI: 10.60507/fk2/jy93ey/3uprfb
title: csm_TIGA_logo_01_5f5f67c173.png
DOI: 10.60507/fk2/jy93ey/oe9xe4
title: Kenya_Map.png
DOI: 10.60507/fk2/qwwqon
title: Environmental Democracy Index (Rank) 2014

description: Environmental Democracy Index (EDI) consists of 75 legal indicators developed under 23 of the UNEP Bali Guidelines that are concerned with the development and implementation of legislation. In addition to the legal indicators, EDI includes 24 supplemental indicators that assess whether there is evidence that environmental democracy is being implemented in practice. The EDI legal indicators assess laws, constitutions, regulations and other legally binding, enforceable rules at the national level.

Quality/Lineage: The data is downloaded from the above link http://environmentaldemocracyindex.org/rank-countries#all and manipulated only table format keeping the value same for all the countries as the requirement of the Strive database. The map is created based on the values of the country using rworldmap package in R.
description: This dataset was first published on the institutional Repository "Zentrum für Entwicklungsforschung: ZEF Data Portal" with ID={b1ec6d14-090a-405a-9e82-dc4ea6da7f3f}.
DOI: 10.15468/dl.bxnb63
title: Occurrence Download

description: A dataset containing 63 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is Spain",
 "Geometry POLYGON((-7.01489 38.16602,-7.58861 37.52513,-7.4067 37.19145,-6.45517 36.86749,-6.10534 36.26058,-5.43366 36.01196,-4.04834 36.78909,-2.47826 36.78844,-2.01119 36.7925,-1.73325 37.27496,-2.88237 38.09136,-4.29265 38.05023,-5.13539 37.8017,-5.3363 37.67756,-7.01489 38.16602))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Quercus pyrenaica Willd."
 ]
}

 The dataset includes 63 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0072993-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.60507/fk2/nyudc3
title: Trading across Borders, Ranking of Economy, 2017

description: Economies are ranked on their ease of doing business, from 1–186. A high ease of doing business ranking means the regulatory environment is more conducive to the starting and operation of a local firm. The rankings are determined by sorting the aggregate distance to frontier scores on 10 topics, each consisting of several indicators, giving equal weight to each topic. The rankings for all economies are benchmarked to June 2017.

Quality/Lineage: The data is downloaded from the above link http://www.doingbusiness.org/rankings and manipulated only table format keeping the value same for all the countries as the requirement of the Strive database. The map is created based on the values of the country using rworldmap package in R.
description: This dataset was first published on the institutional Repository "Zentrum für Entwicklungsforschung: ZEF Data Portal" with ID={a3e1a0c9-201f-4b04-9903-7147b6af9a70}.
DOI: 10.60507/fk2/hurzbt
title: Agronomic Fertilizer Use Efficiency (FUE) in Maize stover biomass in Ethiopia (Map) under three fertilizer application rates i.e., 20 kg/ha Nitrogen and 6.6 kg/ha Phosphorus; 90 kg/ha Nitrogen and 30 kg/ha Phosphorus; 225 kg/ha Nitrogen and 75 kg/ha Phosphorus application rate, 2004-2010

description: Agronomic Fertilizer Use Efficiency (FUE) for maize stover biomass across the Ethiopia has been estimated using crop model LINTUL5 embedded into the modeling framework SIMPLACE (Scientific Impact Assessment and Modelling Platform for Advanced Crop and Ecosystem Management.

Purpose: To increase food production, identifying the regions with untapped production capacity is of prime importance and can be achieved by quantitative and spatially explicit estimates of Agronomic Fertilizer Use Efficiency, thus considering the spatial variation in environment and the production system.
description: This dataset was first published on the institutional Repository "Zentrum für Entwicklungsforschung: ZEF Data Portal" with ID={e2f6050e-123e-4d95-9e2f-fd651f85d2db}.<br>
The Agronomic fertilizer use efficiency under three different fertilizer application rates in maize stover biomass plotted in the map was calculated as the average values of 7 years (the year 2004 -2010). The unit is kilogram per kilogram (kg/kg).
Agronomic fertilizer Use Efficiency (FUE)= (Maize stover biomass under fertilized condition - Maize stover biomass under unfertilized condition) (in kg)/ Fertilizer application rate (in kg)

The climate data at the national scale was made available from the National Aeronautics and Space Administration (NASA), Goddard Institute of Space Studies(https://data.giss.nasa.gov/impacts/agmipcf/agmerra/), AgMERRA.The dataset is stored at 0.25°×0.25° horizontal resolution (~25km).

Soil parameter values were extracted from the soil property maps of Africa at 1 km x 1 km resolution 
(http://http://www.isric.org/projects/soil-property-maps-africa-1-km-resolution).
DOI: 10.60507/fk2/kqeyga
title: Ecological Changes and Local Knowledge Shifts in an Indigenous Honey Gathering Community in the Philippines. Poster on Tropentag 2017

description: One of the traditional livelihood practices of indigenous Tagbanuas in Palawan, Philippines is wild honey gathering from the giant honey bee. In order to analyse the linkages of the social and ecological systems involved in this indigenous practice, we conducted spatial, quantitative, and qualitative analysis on field data gathered through GPS mapping, community surveys, focus group discussions, and key informant interviews. We found that only 24% of the 251 local community members surveyed could correctly identify the giant honey bee. Inferential statistics showed that a lower level of education and higher household vegetation contribute to correct identification of the giant honey bee. Spatial analysis revealed that mean NDVI of sampled nesting tree areas has dropped from 0.61 in the year 1988 to 0.41 in 2015. This reduction on vegetation cover may contribute to reduced bee-human interactions and may also be an indication that commercialising non-timber forest products is not fulfiling its objective of development alongside conservation. Indigenous wild honey hunting and gathering as an ICDP shows the complexity of the social-ecological system of forest communities. It also shows the difficulty of getting a win-win situation out of simultaneous pursuit of forest conservation and rural development. Knowledge shifts can, indeed, occur from the interaction of ecological and social factors and we see that if resource management interventions do not employ a systems approach, it can overlook important feedback. NGO interventions should not only facilitate the learning of visible resource managers like wild honey hunters but of the community as a whole.

Further location tags:
Aborlan
Sagpangan

Quality/Lineage: NATRIPAL has given access to profit data of wild honey enterprise and, together with survey data, gross margin analysis have been applied.
Purpose: This poster has been presented at Tropentag 2017 session 3.4 Knowledge systems.
description: This dataset was first published on the institutional Repository "Zentrum für Entwicklungsforschung: ZEF Data Portal" with ID={266a43a8-4ac3-47d5-b8db-8896413b022c}.
DOI: 10.60507/fk2/q5flr3
title: Changes in Soil Properties Across a Chronosequence of Reclamation of Alluvial Gold-mine Waste in Colombia

description: This dataset presents the result of soil physicochemical characterization and results of field measurements performed in the alluvial gold-mine spoils under reclamation with agroforestry systems in the municipality of El Bagre, Antioquia. The area is under the influence of the company Mineros S.A. who supported the collection and analysis of soil properties.

Purpose: The objective of this research is to assess the changes in soil physicochemical and hydraulic properties across a chronosequence of restoration of sand and gravel deposits created by suction and bucket dredges after alluvial gold exploitation. The authors aim to provide a broader understanding of processes that take place in the reclaimed deposits, to provide insights on management for transition of nutrient poor and acidic deposition sites towards productive agroforestry-based systems.
description: This dataset was first published on the institutional Repository "Zentrum für Entwicklungsforschung: ZEF Data Portal" with ID={90ac4b13-c04e-49fa-8955-2560de7f996f}.
DOI: 10.60507/fk2/on7j92
title: Government effectiveness, Worldwide Governance Indicator, 2016

description: Government effectiveness captures perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government's commitment to such policies. This table lists the individual variables from each data source used to construct this measure in the Worldwide Governance Indicators

Quality/Lineage: The data is downloaded from the above link http://info.worldbank.org/governance/wgi/#home and manipulated only table format keeping the value same for all the countries as the requirement of the Strive database. The map is created based on the values of the country using rworldmap package in R.
description: This dataset was first published on the institutional Repository "Zentrum für Entwicklungsforschung: ZEF Data Portal" with ID={7f6ce3bc-68f9-46e3-ad07-cdb9e39586d5}.
DOI: 10.60507/fk2/qm2qkr
title: Productivity Change and Number of Land Cover Changes in Kenya between 2001 and 2011

description: The Map shows the overlay of the number of land cover changes with NDVI decrease and increase between 2001 and 2011 referring to NDVI trends. Three classes among the trends are built. Besides a “tolerance class” meaning NDVI trends between -0.005 and +0.005 the dataset was classified into “decreasing” (NDVI Trend &lt;-0.005) and “increasing” (NDVI trend &gt;0.005) vegetation trends. The overlay highlights the southern part of Kenya, especially the counties Narok and Kajiado where a stable land cover and decreasing trends overlap. Within this overlap are also Kitui and Isiolo – both counties that were also highlighted in the OLS-regression output as underpredicting –, parts of Marsabit and some small areas along the coastline. Also again the northwestern area, mainly Turkana Region but also West Pokot and Baringo are expressing increasing trends and seem to be linked to a more stable land cover.

Quality/Lineage: Overlay of Number of Land Cover Changes with Productivity trends. It is indicated where positive and where negative productivity trends occurred. Raster data was reclassified and overlayed in ArcGIS.
Purpose: Productivity Change and Number of Land Cover Changes in Kenya between 2001 and 2011
description: This dataset was first published on the institutional Repository "Zentrum für Entwicklungsforschung: ZEF Data Portal" with ID={110f3192-ba06-4fa5-9b50-81fd8716aac0}.
DOI: 10.60507/fk2/gdqj3q
title: Number of Land Cover Changes in Kenya between 2001 and 2011

description: MODIS provides the Land Cover Type Product MCD12Q1 (Friedl et al., 2002) with 500m grid resolution which represents the same pixel size also used for the MODIS NDVI time-series analysis. Annually data provision and a matching pixel size with the MODIS NDVI data used earlier in this study were key elements for choosing this dataset. The Map shows the number of LULC changes as calculated based on the methods described in chapter II.3.3. Stable areas – where land cover changes are zero – can be identified in southern Kenya, Kajiado County in particular, but also in western Kenya north of Lake Victoria, around Lake Turkana, and in the northeastern part of Kenya bordering Ethiopia. Around 33.16% of the total land area experience zero changes from 2001-2011 while 16.11% changed once and 22.92% show two changes. Three (13.98%), four (9.53%) and five (3.42%) changes can still be observed in Map III.11 while areas experiencing more than five changes are occurring in less than 1% of the total land area.
The different classes show the number of land cover changes within the observation period.

Quality/Lineage: Data was reclassified and analysed in R. Extraction of each land cover change per year and analysis of how many changes occurred in the observation period. Visualization was done in ArcGIS.
Purpose: Number of Land Cover Changes in Kenya between 2001 and 2011
description: This dataset was first published on the institutional Repository "Zentrum für Entwicklungsforschung: ZEF Data Portal" with ID={5ea78367-968c-499c-9cf0-658529272bf9}.<br>
The number defines the number of land cover changes that occurred between 2001 and 2011.
DOI: 10.60507/fk2/txxns9
title: Soil data Ethiopia

description: The table includes soil properties in Ethiopia (Jimma, Bako, Yayu).
Temporal coverage approximate 1950-2005.
Spatial resolution 1km.

Quality/Lineage: Source: http://www.isric.org/data/soil-property-maps-africa-1-km
ISRIC – World Soil Information, 2013. Soil property maps of Africa at 1 km.
description: This dataset was first published on the institutional Repository "Zentrum für Entwicklungsforschung: ZEF Data Portal" with ID={686c4780-fe42-41cb-b8f2-2c4b09701f53}.<br>
Spatial resolution 1km.