From f91eb798eff9076be99f97151eb3e2d6615cad69 Mon Sep 17 00:00:00 2001
From: larnsce <18212549+larnsce@users.noreply.github.com>
Date: Mon, 2 Nov 2026 10:35:58 +0000
Subject: [PATCH] chore: weekly catalog harvest

---
 DESCRIPTION                    |   4 +-
 R/sysdata.rda                  | Bin 75260 -> 75512 bytes
 data-raw/harvest_report.md     |  24 +------
 inst/extdata/owd_datasets.csv  |   2 +-
 inst/extdata/owd_packages.csv  | 117 +++++++++++++++++----------------
 inst/extdata/owd_variables.csv |  42 ++++++------
 man/owdata-package.Rd          |   2 +
 7 files changed, 88 insertions(+), 103 deletions(-)

diff --git a/DESCRIPTION b/DESCRIPTION
index 5ca8dde..7c52861 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,6 +1,6 @@
 Package: owdata
 Title: Index of openwashdata R Data Packages
-Version: 0.1.0.9000
+Version: 0.1.0.9001
 Authors@R: c(
     person("Lars", "Schöbitz", , "lschoebitz@ethz.ch", role = c("aut", "cre"),
            comment = c(ORCID = "0000-0003-2196-5015")),
@@ -27,7 +27,7 @@ Imports:
 Language: en-GB
 LazyData: true
 Config/Needs/website: rmarkdown, brand.yml
-Date: 2026-10-26
+Date: 2026-11-02
 BugReports: https://github.com/openwashdata/owdata/issues
 Config/Needs/harvest: desc, cffr, gh, jsonlite
 Depends: 
diff --git a/R/sysdata.rda b/R/sysdata.rda
index ff4113e95e2db4d5b95266ca62f6f487223755d4..9e565e943ec1fc30fdf54c759d3f84d49e775a61 100644
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diff --git a/data-raw/harvest_report.md b/data-raw/harvest_report.md
index 149fc9b..5f0fecd 100644
--- a/data-raw/harvest_report.md
+++ b/data-raw/harvest_report.md
@@ -1,30 +1,12 @@
 # Harvest report
 
-Run: 2026-10-26T08:37:01Z (backend: github)
+Run: 2026-11-02T10:35:55Z (backend: github)
 
-Packages: 60 (50 published). Datasets: 78. Variables: 2716.
+Packages: 61 (50 published). Datasets: 78. Variables: 2716.
 
 ## Deltas since previous committed run
 
-- published change: basisghana FALSE -> TRUE
-- published change: boreholelabdata FALSE -> TRUE
-- published change: chckapmalawi FALSE -> TRUE
-- published change: cleanteamghana FALSE -> TRUE
-- published change: dowaodfsurvey FALSE -> TRUE
-- published change: drillingdata FALSE -> TRUE
-- published change: floodresponsemw FALSE -> TRUE
-- published change: grdwtrsmpkwale FALSE -> TRUE
-- published change: gwinfraassess FALSE -> TRUE
-- published change: handpumpstatusdata FALSE -> TRUE
-- published change: mwefloodresponse FALSE -> TRUE
-- published change: mwgroundwaterdata FALSE -> TRUE
-- published change: nchalohhwatersurvey FALSE -> TRUE
-- published change: portawaterperu FALSE -> TRUE
-- published change: rainwaterhsurvey FALSE -> TRUE
-- published change: thyolocbcc FALSE -> TRUE
-- published change: universityrankingafrica FALSE -> TRUE
-- published change: waterpointstatus FALSE -> TRUE
-- packages dropped from catalog: ploswater, washdataportalsl, wasteburningblantyre, wastecollectionblantyre, whatawaste, whdxdata
+- NA rate for doi rose from 17% to 18%
 
 ## Problems
 
diff --git a/inst/extdata/owd_datasets.csv b/inst/extdata/owd_datasets.csv
index dd06261..c22d2de 100644
--- a/inst/extdata/owd_datasets.csv
+++ b/inst/extdata/owd_datasets.csv
@@ -27,7 +27,7 @@
 "fecalcanuga","ghg","ghg: Greenhouse Gas Mass Flux Rates for each Non-Sewered Sanitation Containment","This data set contains the calculated mass flux rates from the measured point-source in situ GHG measurments and the observed person equivalents for each containment for the three key greenhouse gases (CH4, CO2 and N2O).",41,7,7,"https://raw.githubusercontent.com/openwashdata/fecalcanuga/main/inst/extdata/ghg.csv",
 "fecalcanuga","household_survey","household_survey: Demographic, Environmental and Technical Household / Institutional Data for each Non-Sewered Sanitation Containment","This data set contains the collected household / institutional survey data for each location where a non-sewered sanitation containment was sampled. This includes demographic information, operational and maintenance information and some technical and environmental parameters.",41,39,39,"https://raw.githubusercontent.com/openwashdata/fecalcanuga/main/inst/extdata/household_survey.csv",
 "fecalcanuga","phys_chem_parameter","phys_chem_parameter: Physio-Chemical Parameter Data for each Non-sewered Sanitation Containment","This data set contains the measured in situ and analyzed in laboratory physical, chemical and biological parameters pertaining to each containment sampled as well as at different vertical locations in each containment (i.e., Top of containment, middle and bottom).",119,29,29,"https://raw.githubusercontent.com/openwashdata/fecalcanuga/main/inst/extdata/phys_chem_parameter.csv",
-"floodchlorinationsurvey","floodchlorinationsurvey","USAID Flood Response Rehabilitation and Chlorination Survey","This dataset is from the USAID Flood Response Rehabilitation and Chlorination Survey, conducted between 2019 - 2020, to assess and rehabilitate flood-affected boreholes in Malawi. Using the mWater, data collectors captured detailed information on the condition of handpumps, their components, water safety risks, and the impact of chlorination and repairs. The survey was part of an emergency response initiative to restore access to safe drinking water following flood events.",328,118,118,"https://raw.githubusercontent.com/openwashdata/floodchlorinationsurvey/master/inst/extdata/floodchlorinationsurvey.csv","https://raw.githubusercontent.com/openwashdata/floodchlorinationsurvey/master/inst/extdata/floodchlorinationsurvey.xlsx"
+"floodchlorinationsurvey","floodchlorinationsurvey","USAID Flood Response Rehabilitation and Chlorination Survey","This dataset is from the USAID Flood Response Rehabilitation and Chlorination Survey, conducted between 2019 - 2020, to assess and rehabilitate flood-affected boreholes in Malawi. Using the mWater, data collectors captured detailed information on the condition of handpumps, their components, water safety risks, and the impact of chlorination and repairs. The survey was part of an emergency response initiative to restore access to safe drinking water following flood events.",328,118,118,"https://raw.githubusercontent.com/openwashdata/floodchlorinationsurvey/main/inst/extdata/floodchlorinationsurvey.csv","https://raw.githubusercontent.com/openwashdata/floodchlorinationsurvey/main/inst/extdata/floodchlorinationsurvey.xlsx"
 "floodresponsemw","floodresponsemw","Malawi USAID Flood Response – Water Point Assessment 2019 - 2020","This dataset contains detailed field-level information on the status and functionality of rural water points across Malawi, collected as part of the USAID Flood Response initiative between 2019 and 2020. The data was gathered using the mWater mobile data collection platform, enabling standardized, GPS-tagged assessments directly from field locations.",684,45,45,"https://raw.githubusercontent.com/openwashdata/floodresponsemw/main/inst/extdata/floodresponsemw.csv","https://raw.githubusercontent.com/openwashdata/floodresponsemw/main/inst/extdata/floodresponsemw.xlsx"
 "fslogisticskampala","trips","trips: Trips of faecal sludge trucks","This dataset contains the GPS locations of faecal sludge trucks collecting sludge from pit latrines and septic tanks in Kampala, Uganda. Each trip is recorded with a unique identifier, the numberplate of the truck, the date and time of the record. Data was collected from 30th March 2015 until 25th June 2015.",5653,7,7,"https://raw.githubusercontent.com/openwashdata/fslogisticskampala/main/inst/extdata/trips.csv","https://raw.githubusercontent.com/openwashdata/fslogisticskampala/main/inst/extdata/trips.xlsx"
 "fslogisticskampala","trucks","trucks: Faecal sludge emptying trucks","Additional information on the volume of each truck used in the dataset `trips`.",33,2,2,"https://raw.githubusercontent.com/openwashdata/fslogisticskampala/main/inst/extdata/trucks.csv","https://raw.githubusercontent.com/openwashdata/fslogisticskampala/main/inst/extdata/trucks.xlsx"
diff --git a/inst/extdata/owd_packages.csv b/inst/extdata/owd_packages.csv
index fd0209b..9954843 100644
--- a/inst/extdata/owd_packages.csv
+++ b/inst/extdata/owd_packages.csv
@@ -1,61 +1,62 @@
 "pkg_name","title","description","version","published","reviewed","maintainer","maintainer_orcid","authors","license","date","keywords","spatial_coverage","temporal_coverage","doi","cff_version","url_github","url_docs","n_datasets","latest_release","default_branch","created_at","last_commit","topics","has_dictionary","has_extdata","washr_version","brand_ref","pkgreview_standard","has_r_cmd_check","has_pkgdown_workflow","has_jsonld"
-"artesianwells","Artesian Well Site Assessment Data","A dataset capturing geospatial, structural, usage, and management characteristics of artesian well sites.","0.1.0",TRUE,,"Emmanuel Mhango","0000-0003-3197-6244","Emmanuel Mhango","CC BY 4.0",2025-06-02,,,,"10.5281/zenodo.15824828","0.1.0","https://github.com/openwashdata/artesianwells","https://openwashdata.github.io/artesianwells/",1,"v0.1.0","main",2025-06-02,2026-10-05,,TRUE,TRUE,,,,TRUE,FALSE,FALSE
-"basisghana","Basic Sanitation Information System - BaSIS","This package compiles sanitation data from established Open Defecation Free (ODF) communities across different regions in Ghana.","0.0.0.9000",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Lars Schöbitz; Sophia Skorik","CC BY 4.0",2026-09-18,"open data, washdata, sanitation, open defecation, Ghana",,,"10.5281/zenodo.10255444","0.0.0.9000","https://github.com/openwashdata/basisghana","https://openwashdata.github.io/basisghana/",2,"v0.0.1","main",2023-08-09,2026-09-23,"defecation, ghana, open-data, openwashdata, r, sanitation, wash",TRUE,TRUE,,,,TRUE,TRUE,TRUE
-"biogasoutcomesmalawi","Data for 61 semi-structured interviews with biogas owners in Malawi","This dataset consists of 61 semi-structured interviews with biogas owners in the Southern Region of Malawi. Interviews were conducted over multiple visits to sites over the course of a two-year period between June 2021 and October 2022.","0.0.1",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Lars Schöbitz; Sebastian Camilo Loos; Marc Kalina; Jonathan Olal Ogwang; Jonathan Kwangulero; Elizabeth Tilley","CC BY 4.0",2023-08-28,"biogas, interview-data, malawi, opendata, openwashdata, r",,,"10.5281/zenodo.8289620","0.0.1","https://github.com/openwashdata/biogasoutcomesmalawi","https://openwashdata.github.io/biogasoutcomesmalawi/",1,"v0.0.1","main",2023-07-26,2026-09-17,"biogas, interview-data, malawi, opendata, openwashdata, r",TRUE,TRUE,,,,TRUE,TRUE,FALSE
-"boreholeforensicspumpingtest","Borehole Forensics 4 - Pumping Test Data 2018-2024","This dataset contains borehole forensic pumping test data, capturing key parameters related to groundwater extraction, borehole performance, and water quality assessments. It includes information on the test conditions, water levels, pumping rates, flow measurement methods, and water quality indicators such as pH, turbidity, and electrical conductivity. The dataset also documents permissions granted for testing, equipment used, and observations on borehole performance.","0.1.0",TRUE,,"Emmanuel Mhango","0000-0003-3197-6244","Emmanuel Mhango; Finlay Paterson; Paul Kumpukwe","CC BY 4.0",2025-03-05,,,,"10.5281/zenodo.15800110","0.1.0","https://github.com/openwashdata/boreholeforensicspumpingtest","https://openwashdata.github.io/boreholeforensicspumpingtest/",1,"v0.1.0","main",2025-03-05,2025-07-03,,TRUE,TRUE,,,,FALSE,FALSE,FALSE
-"boreholefuncmwi","Analysis of boreholes' functionality in Northern Malawi","The data is obtained from a survey conducted in Wasambo in Karonga district (Northen Malawi). This data is about boreholes and handpumps that people mostly rely on for drinking water, secondary to wells and rivers. The data were collected in June 2023.","0.0.1",TRUE,,"Mabvuto Yesaya","0000-0003-3234-9699","Mabvuto Yesaya; Juliette Preisig; Hastings Kayira; Mian Zhong","CC BY 4.0",2024-06-27,"borehole, malawi, opendata, openwashdata, r, survey-data",,,"10.5281/zenodo.12635354","0.0.1","https://github.com/openwashdata/boreholefuncmwi","https://openwashdata.github.io/boreholefuncmwi/",1,"v0.0.1","main",2024-06-21,2024-07-03,"borehole, malawi, opendata, openwashdata, r, survey-data",TRUE,TRUE,,,,TRUE,FALSE,FALSE
-"boreholelabdata","Borehole Water Quality Laboratory Results, Malawi 2017 to 2019","This dataset contains comprehensive records of water quality test results collected from various water points across Malawi between 2017 and 2019.","1.0.1",TRUE,,"Emmanuel Mhango","0000-0003-3197-6244","Emmanuel Mhango; Finlay Paterson; Jamie Rattray","CC BY 4.0",2026-09-18,"open data, washdata, water quality, groundwater, boreholes, Malawi",,,"10.5281/zenodo.17433461","1.0.1","https://github.com/openwashdata/boreholelabdata","https://openwashdata.github.io/boreholelabdata/",1,"v1.0.1","main",2025-08-06,2026-09-23,"boreholes, wash, water-quality",TRUE,TRUE,,,,TRUE,TRUE,TRUE
-"breathablepitlat","Breathable Laminate-Lined Pit Latrines, Fatehpur, India 2021-2022","This dataset assists with a research study aims at capturing the pathogens and contaminants from pit latrines by lining them with a hydrophobic laminate. The data are collected to demonstrate the transport of contaminants from two pour flush, twin-pit latrines in which one pit is lined and one is unlined.","1.0.1",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Mian Zhong; Shray Saxena; Lars Schöbitz","CC BY 4.0",2024-06-21,"open data, washdata, sanitation, pit latrines, faecal contamination, soil quality, groundwater, India","Fatehpur District, Uttar Pradesh, India","2021-12-01/2022-12-31","10.5281/zenodo.13960698","1.0.1","https://github.com/openwashdata/breathablepitlat","https://openwashdata.github.io/breathablepitlat/",1,"v1.0","main",2024-06-21,2026-09-24,,TRUE,TRUE,,,,TRUE,TRUE,TRUE
-"cbssuitabilityhaiti","Sanitation Zoning and Water Points, Cap Haitien, Haiti 2015-2022","This package contains data for a sanitation zoning assessment of Cap Haitien, Haiti, used for an analysis of the suitability of container-based sanitation (CBS). It combines two datasets: neighbourhood level zoning data from a 2022 sanitation zoning assessment, covering Cap Haitien and five other communes in Haiti, and the locations of 1849 water points in the Cap Haitien area from the mWater platform, added between 2015 and 2022.","0.0.1",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Sebastian Camilo Loos; Sasha Kramer; Maya Lubeck-Schricker; Lars Schöbitz","CC BY 4.0",2023-09-19,"open data, washdata, sanitation, sanitation zoning, container-based sanitation, water points, urban planning, Cap Haitien, Haiti","Cap Haitien and five other communes (Canaan, Croix-des-Bouquets, Jeremie, Les Cayes, Mirebalais), Haiti","2015-07-24/2022-12-31","10.5281/zenodo.8361084","0.0.1","https://github.com/openwashdata/cbssuitabilityhaiti","https://openwashdata.github.io/cbssuitabilityhaiti/",2,"v0.0.1","main",2023-04-06,2026-09-24,"central-america, container-based-sanitation, haiti, open-data, open-datasets, r, sanitation, suitability-analysis, wash",TRUE,TRUE,,,,TRUE,TRUE,TRUE
-"chckapmalawi","KAP Survey on Community Health Centers in Malawi","This dataset captures insights from a Knowledge, Attitudes, and Practices (KAP) Survey conducted by BASEflow for Waste Advisers in Malawi, focusing on Community Health Centers (CHCs). It covers diverse aspects including household demographics, CHC membership, water sources, sanitation, nutrition knowledge, hygiene practices, and environmental conditions.","0.0.3",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Sophia Skorik; Lars Schöbitz; Rhodrick Sagawa; Paul Kumpukwe; Veronica Chinangwa; Baleke Banda; Rodney Kananji; Feston Bwanyula; Gloria Maliana; Given Ngwira","CC BY 4.0",2026-09-18,"open data, washdata, community health, KAP survey, WASH, Malawi",,,"10.5281/zenodo.10459432","0.0.3","https://github.com/openwashdata/chckapmalawi","https://openwashdata.github.io/chckapmalawi/",1,"v0.0.2","main",2023-10-25,2026-10-03,,TRUE,TRUE,,,,TRUE,TRUE,TRUE
-"choleramalawi","Tracks the progress of Cholera epidemic in Malawi (2022-23)","A dataset that tracks the progress of the cholera epidemic in each district of Malawi in 2022-23.","1.0.1",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Yash Dubey; Lars Schöbitz","CC BY 4.0",2024-10-11,"open data, washdata, cholera, epidemic, disease surveillance, public health, Malawi","Malawi","2022-02-28/2023-10-29","10.5281/zenodo.13920529","1.0.1","https://github.com/openwashdata/choleramalawi","https://openwashdata.github.io/choleramalawi/",1,"v1.0","main",2024-10-04,2026-09-24,,TRUE,TRUE,,,,TRUE,TRUE,TRUE
-"cleanteamghana","Clean Team Ghana","This package compiles user experience data for the Clean Team Ghana container-based sanitation service in Kumasi, Ghana.","0.0.2",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Sophia Skorik; James Benjamin Tidwell; Kwabena Biritwum Nyarko; Ian Ross; Bismark Dwumfour-Asare; Scott Pippa; Lars Schöbitz","CC BY 4.0",2026-09-18,"open data, washdata, container-based sanitation, Ghana",,,"10.5281/zenodo.10439886","0.0.2","https://github.com/openwashdata/cleanteamghana","https://openwashdata.github.io/cleanteamghana/",1,"v0.0.2","main",2023-10-25,2026-09-24,"container-based-sanitation, ghana, open-data, openwashdata, r, sanitation",TRUE,TRUE,,,,TRUE,TRUE,TRUE
-"climatevulnerabilitykhm","Climate Vulnerability Data in Rural Cambodia","Data on Effects of Climate Vulnerability on Sanitation Access, Sanitation Infrastructure Functionality and Households’ Fecal Sludge Management Practices in Rural Cambodia.","0.0.0.9000",FALSE,,"Mian Zhong","0009-0009-4546-7214","Mian Zhong; James Harper","CC BY 4.0",,"cambodia, climate-data, open-data, open-datasets, openwashdata, r, wash",,,,"0.0.0.9000","https://github.com/openwashdata/climatevulnerabilitykhm","https://openwashdata.github.io/climatevulnerabilitykhm/",1,,"main",2023-06-20,2023-07-05,"cambodia, climate-data, open-data, open-datasets, openwashdata, r, wash",TRUE,FALSE,,,,FALSE,FALSE,FALSE
-"dowalatrinesurvey","Household Latrine Survey Data from Dowa and Thyolo, Malawi","Contains survey data collected in October 2020 from households in Dowa and Thyolo Districts, Malawi. The dataset includes detailed information on household sanitation practices, latrine infrastructure, usage patterns, maintenance behaviors, and user preferences across rural and peri-urban communities. Data was collected using the mWater survey platform by BASEflow Malawi enumerators.","0.0.0.9000",FALSE,,"Emmanuel Mhango","0000-0003-3197-6244","Emmanuel Mhango","CC BY 4.0",2025-07-16,"hygiene, latrines, sanitation, wash",,,,"0.0.0.9000","https://github.com/openwashdata/dowalatrinesurvey","https://openwashdata.github.io/dowalatrinesurvey/",1,"v1.0.0","main",2025-06-25,2026-10-03,"hygiene, latrines, sanitation, wash",TRUE,TRUE,,,,FALSE,FALSE,FALSE
-"dowaodfsurvey","ODF Household Survey, Ntchisi and Dowa Districts, Malawi 2019","This dataset contains results from a household-level WASH (Water, Sanitation, and Hygiene) survey conducted on July 1st, 2019 in Mduku GVH, Dowa District, within the catchment area of Mbingwa Health Centre, Malawi. The purpose of the survey was to assess sanitation infrastructure, hygiene practices, and menstrual hygiene management (MHM) as part of an Open Defecation Free (ODF) verification exercise.","1.0.1",TRUE,,"Emmanuel Mhango","0000-0003-3197-6244","Emmanuel Mhango","CC BY 4.0",2026-09-18,"open data, washdata, sanitation, hygiene, open defecation free, household survey, Malawi",,,"10.5281/zenodo.17492107","1.0.1","https://github.com/openwashdata/dowaodfsurvey","https://openwashdata.github.io/dowaodfsurvey/",1,"v1.0.1","main",2025-08-07,2026-09-23,"open-defecation, sanitation, wash",TRUE,TRUE,,,,TRUE,TRUE,TRUE
-"drillingdata","Borehole Drilling and Construction Data – Malawi, 2018 - 2024","This dataset captures detailed information on borehole drilling and construction activities conducted across selected sites in Malawi in 2018. Data were collected using the mWater digital platform, documenting each stage of groundwater development, from site selection and hydrogeological studies to drilling operations, borehole design, and post-construction assessments.","1.0.1",TRUE,,"Emmanuel Mhango","0000-0003-3197-6244","Emmanuel Mhango; Jamie Rattray; Shaun MacLeod; Feston Bwanyula","CC BY 4.0",2026-09-18,"open data, washdata, boreholes, drilling, groundwater, water supply, Malawi",,,"10.5281/zenodo.17543305","1.0.1","https://github.com/openwashdata/drillingdata","https://openwashdata.github.io/drillingdata/",1,"v1.0.1","main",2025-04-08,2026-09-23,"borehole, sanitation, wash",TRUE,TRUE,,,,TRUE,TRUE,TRUE
-"dryingfaecal","What the Package Does (One Line, Title Case)","What the package does (one paragraph).","0.0.0.9000",FALSE,,"Lars Schöbitz","0000-0003-2196-5015","Mian Zhong; Lars Schöbitz","CC BY 4.0",,,,,,"0.0.0.9000","https://github.com/openwashdata/dryingfaecal","https://openwashdata.github.io/dryingfaecal/",2,,"main",2023-06-28,2026-09-23,,TRUE,FALSE,,,,FALSE,FALSE,FALSE
-"ds4owdanalytics","DS4OWD Analytics","Data collected from the Data Science for Open WASH Data (DS4OWD) course and the associated website and data publishing endeavour.","0.1.0",TRUE,,"Yash Dubey","0009-0001-2849-970X","Yash Dubey","CC BY 4.0",2025-01-31,,,,"10.5281/zenodo.14778963","0.1.0","https://github.com/openwashdata/ds4owdanalytics","https://openwashdata.github.io/ds4owdanalytics/",9,"v1.0.0","main",2025-01-31,2025-01-31,,TRUE,TRUE,,,,TRUE,FALSE,FALSE
+"artesianwells","Artesian Well Site Assessment Data","A dataset capturing geospatial, structural, usage, and management characteristics of artesian well sites.","0.1.0",TRUE,,"Emmanuel Mhango","0000-0003-3197-6244","Emmanuel Mhango","CC BY 4.0",2025-06-02,,,,"10.5281/zenodo.15824828","0.1.0","https://github.com/openwashdata/artesianwells","https://openwashdata.github.io/artesianwells/",1,"v0.1.0","main",2025-06-02,2026-11-01,,TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"basisghana","Basic Sanitation Information System - BaSIS","This package compiles sanitation data from established Open Defecation Free (ODF) communities across different regions in Ghana.","0.0.0.9000",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Lars Schöbitz; Sophia Skorik","CC BY 4.0",2026-09-18,"open data, washdata, sanitation, open defecation, Ghana",,,"10.5281/zenodo.10255444","0.0.0.9000","https://github.com/openwashdata/basisghana","https://openwashdata.github.io/basisghana/",2,"v0.0.1","main",2023-08-09,2026-11-01,"defecation, ghana, open-data, openwashdata, r, sanitation, wash",TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"biogasoutcomesmalawi","Data for 61 semi-structured interviews with biogas owners in Malawi","This dataset consists of 61 semi-structured interviews with biogas owners in the Southern Region of Malawi. Interviews were conducted over multiple visits to sites over the course of a two-year period between June 2021 and October 2022.","0.0.1",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Lars Schöbitz; Sebastian Camilo Loos; Marc Kalina; Jonathan Olal Ogwang; Jonathan Kwangulero; Elizabeth Tilley","CC BY 4.0",2023-08-28,"biogas, interview-data, malawi, opendata, openwashdata, r",,,"10.5281/zenodo.8289620","0.0.1","https://github.com/openwashdata/biogasoutcomesmalawi","https://openwashdata.github.io/biogasoutcomesmalawi/",1,"v0.0.1","main",2023-07-26,2026-11-01,"biogas, interview-data, malawi, opendata, openwashdata, r",TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"boreholeforensicspumpingtest","Borehole Forensics 4 - Pumping Test Data 2018-2024","This dataset contains borehole forensic pumping test data, capturing key parameters related to groundwater extraction, borehole performance, and water quality assessments. It includes information on the test conditions, water levels, pumping rates, flow measurement methods, and water quality indicators such as pH, turbidity, and electrical conductivity. The dataset also documents permissions granted for testing, equipment used, and observations on borehole performance.","0.1.0",TRUE,,"Emmanuel Mhango","0000-0003-3197-6244","Emmanuel Mhango; Finlay Paterson; Paul Kumpukwe","CC BY 4.0",2025-03-05,,,,"10.5281/zenodo.15800110","0.1.0","https://github.com/openwashdata/boreholeforensicspumpingtest","https://openwashdata.github.io/boreholeforensicspumpingtest/",1,"v0.1.0","main",2025-03-05,2026-11-01,,TRUE,TRUE,"1.2.2","v1.1.0",,FALSE,TRUE,TRUE
+"boreholefuncmwi","Analysis of boreholes' functionality in Northern Malawi","The data is obtained from a survey conducted in Wasambo in Karonga district (Northen Malawi). This data is about boreholes and handpumps that people mostly rely on for drinking water, secondary to wells and rivers. The data were collected in June 2023.","0.0.1",TRUE,,"Mabvuto Yesaya","0000-0003-3234-9699","Mabvuto Yesaya; Juliette Preisig; Hastings Kayira; Mian Zhong","CC BY 4.0",2024-06-27,"borehole, malawi, opendata, openwashdata, r, survey-data",,,"10.5281/zenodo.12635354","0.0.1","https://github.com/openwashdata/boreholefuncmwi","https://openwashdata.github.io/boreholefuncmwi/",1,"v0.0.1","main",2024-06-21,2026-11-01,"borehole, malawi, opendata, openwashdata, r, survey-data",TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"boreholelabdata","Borehole Water Quality Laboratory Results, Malawi 2017 to 2019","This dataset contains comprehensive records of water quality test results collected from various water points across Malawi between 2017 and 2019.","1.0.1",TRUE,,"Emmanuel Mhango","0000-0003-3197-6244","Emmanuel Mhango; Finlay Paterson; Jamie Rattray","CC BY 4.0",2026-09-18,"open data, washdata, water quality, groundwater, boreholes, Malawi",,,"10.5281/zenodo.17433461","1.0.1","https://github.com/openwashdata/boreholelabdata","https://openwashdata.github.io/boreholelabdata/",1,"v1.0.1","main",2025-08-06,2026-11-01,"boreholes, wash, water-quality",TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"breathablepitlat","Breathable Laminate-Lined Pit Latrines, Fatehpur, India 2021-2022","This dataset assists with a research study aims at capturing the pathogens and contaminants from pit latrines by lining them with a hydrophobic laminate. The data are collected to demonstrate the transport of contaminants from two pour flush, twin-pit latrines in which one pit is lined and one is unlined.","1.0.1",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Mian Zhong; Shray Saxena; Lars Schöbitz","CC BY 4.0",2024-06-21,"open data, washdata, sanitation, pit latrines, faecal contamination, soil quality, groundwater, India","Fatehpur District, Uttar Pradesh, India","2021-12-01/2022-12-31","10.5281/zenodo.13960698","1.0.1","https://github.com/openwashdata/breathablepitlat","https://openwashdata.github.io/breathablepitlat/",1,"v1.0","main",2024-06-21,2026-11-01,,TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"burigangaamr","Antibiotic Resistance of P. aeruginosa from the Buriganga River","Antibiotic susceptibility test results of 50 Pseudomonas aeruginosa isolates from surface water at seven sites along the Buriganga River, Bangladesh, tested against nine antibiotics by disc diffusion, with a summary per isolate and the zone diameter breakpoints used. The data are republished from the supplementary tables of Sharif, Amin, Mehbub and Ratul (2024) <doi:10.2166/wh.2024.270>, Journal of Water and Health, CC BY 4.0.","0.0.0.9000",FALSE,,"Lars Schöbitz","0000-0003-2196-5015","Lars Schöbitz","CC BY 4.0",2026-10-30,"open data, washdata, antimicrobial resistance, Pseudomonas aeruginosa, surface water, river water, Bangladesh","Buriganga River, Bangladesh","2023-03-01/2023-05-15",,"0.0.0.9000","https://github.com/openwashdata/burigangaamr","https://openwashdata.github.io/burigangaamr/",3,,"main",2026-10-30,2026-11-01,,TRUE,TRUE,"1.2.2","v1.1.0","1.7.0",TRUE,TRUE,TRUE
+"cbssuitabilityhaiti","Sanitation Zoning and Water Points, Cap Haitien, Haiti 2015-2022","This package contains data for a sanitation zoning assessment of Cap Haitien, Haiti, used for an analysis of the suitability of container-based sanitation (CBS). It combines two datasets: neighbourhood level zoning data from a 2022 sanitation zoning assessment, covering Cap Haitien and five other communes in Haiti, and the locations of 1849 water points in the Cap Haitien area from the mWater platform, added between 2015 and 2022.","0.0.1",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Sebastian Camilo Loos; Sasha Kramer; Maya Lubeck-Schricker; Lars Schöbitz","CC BY 4.0",2023-09-19,"open data, washdata, sanitation, sanitation zoning, container-based sanitation, water points, urban planning, Cap Haitien, Haiti","Cap Haitien and five other communes (Canaan, Croix-des-Bouquets, Jeremie, Les Cayes, Mirebalais), Haiti","2015-07-24/2022-12-31","10.5281/zenodo.8361084","0.0.1","https://github.com/openwashdata/cbssuitabilityhaiti","https://openwashdata.github.io/cbssuitabilityhaiti/",2,"v0.0.1","main",2023-04-06,2026-11-01,"central-america, container-based-sanitation, haiti, open-data, open-datasets, r, sanitation, suitability-analysis, wash",TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"chckapmalawi","KAP Survey on Community Health Centers in Malawi","This dataset captures insights from a Knowledge, Attitudes, and Practices (KAP) Survey conducted by BASEflow for Waste Advisers in Malawi, focusing on Community Health Centers (CHCs). It covers diverse aspects including household demographics, CHC membership, water sources, sanitation, nutrition knowledge, hygiene practices, and environmental conditions.","0.0.3",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Sophia Skorik; Lars Schöbitz; Rhodrick Sagawa; Paul Kumpukwe; Veronica Chinangwa; Baleke Banda; Rodney Kananji; Feston Bwanyula; Gloria Maliana; Given Ngwira","CC BY 4.0",2026-09-18,"open data, washdata, community health, KAP survey, WASH, Malawi",,,"10.5281/zenodo.10459432","0.0.3","https://github.com/openwashdata/chckapmalawi","https://openwashdata.github.io/chckapmalawi/",1,"v0.0.2","main",2023-10-25,2026-11-01,,TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"choleramalawi","Tracks the progress of Cholera epidemic in Malawi (2022-23)","A dataset that tracks the progress of the cholera epidemic in each district of Malawi in 2022-23.","1.0.1",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Yash Dubey; Lars Schöbitz","CC BY 4.0",2024-10-11,"open data, washdata, cholera, epidemic, disease surveillance, public health, Malawi","Malawi","2022-02-28/2023-10-29","10.5281/zenodo.13920529","1.0.1","https://github.com/openwashdata/choleramalawi","https://openwashdata.github.io/choleramalawi/",1,"v1.0","main",2024-10-04,2026-11-01,,TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"cleanteamghana","Clean Team Ghana","This package compiles user experience data for the Clean Team Ghana container-based sanitation service in Kumasi, Ghana.","0.0.2",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Sophia Skorik; James Benjamin Tidwell; Kwabena Biritwum Nyarko; Ian Ross; Bismark Dwumfour-Asare; Scott Pippa; Lars Schöbitz","CC BY 4.0",2026-09-18,"open data, washdata, container-based sanitation, Ghana",,,"10.5281/zenodo.10439886","0.0.2","https://github.com/openwashdata/cleanteamghana","https://openwashdata.github.io/cleanteamghana/",1,"v0.0.2","main",2023-10-25,2026-11-01,"container-based-sanitation, ghana, open-data, openwashdata, r, sanitation",TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"climatevulnerabilitykhm","Climate Vulnerability Data in Rural Cambodia","Data on Effects of Climate Vulnerability on Sanitation Access, Sanitation Infrastructure Functionality and Households’ Fecal Sludge Management Practices in Rural Cambodia.","0.0.0.9000",FALSE,,"Mian Zhong","0009-0009-4546-7214","Mian Zhong; James Harper","CC BY 4.0",2026-10-31,"cambodia, climate-data, open-data, open-datasets, openwashdata, r, wash",,,,"0.0.0.9000","https://github.com/openwashdata/climatevulnerabilitykhm","https://openwashdata.github.io/climatevulnerabilitykhm/",1,,"main",2023-06-20,2026-11-01,"cambodia, climate-data, open-data, open-datasets, openwashdata, r, wash",TRUE,FALSE,"1.2.2","v1.1.0",,FALSE,TRUE,TRUE
+"dowalatrinesurvey","Household Latrine Survey Data from Dowa and Thyolo, Malawi","Contains survey data collected in October 2020 from households in Dowa and Thyolo Districts, Malawi. The dataset includes detailed information on household sanitation practices, latrine infrastructure, usage patterns, maintenance behaviors, and user preferences across rural and peri-urban communities. Data was collected using the mWater survey platform by BASEflow Malawi enumerators.","0.0.0.9000",FALSE,,"Emmanuel Mhango","0000-0003-3197-6244","Emmanuel Mhango","CC BY 4.0",2025-07-16,"hygiene, latrines, sanitation, wash",,,,"0.0.0.9000","https://github.com/openwashdata/dowalatrinesurvey","https://openwashdata.github.io/dowalatrinesurvey/",1,"v1.0.0","main",2025-06-25,2026-11-01,"hygiene, latrines, sanitation, wash",TRUE,TRUE,"1.2.2","v1.1.0",,FALSE,TRUE,TRUE
+"dowaodfsurvey","ODF Household Survey, Ntchisi and Dowa Districts, Malawi 2019","This dataset contains results from a household-level WASH (Water, Sanitation, and Hygiene) survey conducted on July 1st, 2019 in Mduku GVH, Dowa District, within the catchment area of Mbingwa Health Centre, Malawi. The purpose of the survey was to assess sanitation infrastructure, hygiene practices, and menstrual hygiene management (MHM) as part of an Open Defecation Free (ODF) verification exercise.","1.0.1",TRUE,,"Emmanuel Mhango","0000-0003-3197-6244","Emmanuel Mhango","CC BY 4.0",2026-09-18,"open data, washdata, sanitation, hygiene, open defecation free, household survey, Malawi",,,"10.5281/zenodo.17492107","1.0.1","https://github.com/openwashdata/dowaodfsurvey","https://openwashdata.github.io/dowaodfsurvey/",1,"v1.0.1","main",2025-08-07,2026-11-01,"open-defecation, sanitation, wash",TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"drillingdata","Borehole Drilling and Construction Data – Malawi, 2018 - 2024","This dataset captures detailed information on borehole drilling and construction activities conducted across selected sites in Malawi in 2018. Data were collected using the mWater digital platform, documenting each stage of groundwater development, from site selection and hydrogeological studies to drilling operations, borehole design, and post-construction assessments.","1.0.1",TRUE,,"Emmanuel Mhango","0000-0003-3197-6244","Emmanuel Mhango; Jamie Rattray; Shaun MacLeod; Feston Bwanyula","CC BY 4.0",2026-09-18,"open data, washdata, boreholes, drilling, groundwater, water supply, Malawi",,,"10.5281/zenodo.17543305","1.0.1","https://github.com/openwashdata/drillingdata","https://openwashdata.github.io/drillingdata/",1,"v1.0.1","main",2025-04-08,2026-11-01,"borehole, sanitation, wash",TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"dryingfaecal","What the Package Does (One Line, Title Case)","What the package does (one paragraph).","0.0.0.9000",FALSE,,"Lars Schöbitz","0000-0003-2196-5015","Mian Zhong; Lars Schöbitz","CC BY 4.0",2026-10-31,,,,,"0.0.0.9000","https://github.com/openwashdata/dryingfaecal","https://openwashdata.github.io/dryingfaecal/",2,,"main",2023-06-28,2026-11-01,,TRUE,FALSE,"1.2.2","v1.1.0",,FALSE,TRUE,TRUE
+"ds4owdanalytics","DS4OWD Analytics","Data collected from the Data Science for Open WASH Data (DS4OWD) course and the associated website and data publishing endeavour.","0.1.0",TRUE,,"Yash Dubey","0009-0001-2849-970X","Yash Dubey","CC BY 4.0",2025-01-31,,,,"10.5281/zenodo.14778963","0.1.0","https://github.com/openwashdata/ds4owdanalytics","https://openwashdata.github.io/ds4owdanalytics/",9,"v1.0.0","main",2025-01-31,2026-11-01,,TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
 "faecalsludgekampala","What the Package Does (One Line, Title Case)","What the package does (one paragraph).","0.0.0.9000",FALSE,,"Lars Schöbitz",,"Lars Schöbitz; Matt Bannert","`use_mit_license()`, `use_gpl3_license()` or friends to pick a license",,,,,,"0.0.0.9000","https://github.com/openwashdata/faecalsludgekampala","https://openwashdata.github.io/faecalsludgekampala/",1,,"main",2023-11-30,2023-11-30,,FALSE,FALSE,,,,FALSE,FALSE,FALSE
-"fecalcanuga","Non-Sewered Sanitation Containments, Canada and Uganda 2023-2024","This data package contains data representing 5 months of field work from April - June 2023 (Canada) and January - February 2024 (Uganda) collecting household and commercial wastewater containment data and characterizing physical, chemical and greenhouse gas data for 22 non-sewered sanitation sites on southern Vancouver island and the southern gulf islands in British Columbia, Canada and 19 sites in Kampala, Uganda.","0.1.0",TRUE,,"Kelsey Shaw","0000-0001-7417-110X","Kelsey Shaw; Caetano Dorea; Linda Strande; Charles Niwagaba; Mian Zhong","CC BY 4.0",2026-06-22,"open data, washdata, non-sewered sanitation, fecal sludge, septic tanks, greenhouse gas emissions, Canada, Uganda","Southern Vancouver Island and the Southern Gulf Islands, British Columbia, Canada; Kampala, Uganda","2023-04-06/2024-02-13","10.5281/zenodo.20795916","0.1.0","https://github.com/openwashdata/fecalcanuga","https://openwashdata.github.io/fecalcanuga/",4,"v0.1.0","main",2026-06-18,2026-09-24,,TRUE,TRUE,,,,TRUE,TRUE,TRUE
-"floodchlorinationsurvey","USAID Flood Response Rehabilitation and Chlorination Survey","This R package provides tools for analyzing and visualizing data from the USAID Flood Response Rehabilitation and Chlorination Survey conducted in Mulanje, Malawi (2019–2020). It includes functions to assess handpump component replacements, evaluate changes in functionality before and after rehabilitation, and identify common repair trends using mWater-collected data.","0.1.0",TRUE,,"Emmanuel Mhango","0000-0003-3197-6244","Emmanuel Mhango","CC BY 4.0",2025-07-01,,,,"10.5281/zenodo.15846578","0.1.0","https://github.com/openwashdata/floodchlorinationsurvey","https://openwashdata.github.io/floodchlorinationsurvey/",1,"v0.1.0","master",2025-06-30,2026-10-05,,TRUE,TRUE,,,,TRUE,FALSE,FALSE
-"floodresponsemw","Water Point Assessments - USAID Flood Response Malawi 2019-2020","Field-level data on rural water point status and functionality across Malawi, collected during the USAID Flood Response initiative (2019-2020). Includes GPS locations, flood impact indicators, pump functionality, water quality measurements, and microbial contamination data from mWater mobile assessments.","0.0.2",TRUE,,"Emmanuel Mhango","0000-0003-3197-6244","Emmanuel Mhango","CC BY 4.0",2026-09-23,"open data, washdata, water points, flood response, handpumps, water quality, Malawi","Malawi","2019-05-27/2020-02-26","10.5281/zenodo.17432023","0.0.2","https://github.com/openwashdata/floodresponsemw","https://openwashdata.github.io/floodresponsemw/",1,"v0.0.1","main",2025-06-27,2026-10-03,"flood, floodresponse, waterpoints",TRUE,TRUE,,,,TRUE,TRUE,TRUE
-"fslogisticskampala","Data on Faecal Sludge Transporting Logistics in Kampala, Uganda","Contains two data resources. `trips` contains the GPS locations of faecal sludge emptying trucks collecting sludge from pit latrines and septic tanks in Kampala, Uganda. Each trip is recorded with a unique identifier, the numberplate of the truck, the date and time of the record. Data was collected from 30th March 2015 until 25th June 2015. `trucks` has additional information on the volume of each truck.","1.0.0",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Lars Schöbitz","CC BY 4.0",2026-07-08,,,,"10.5281/zenodo.21260446","1.0.0","https://github.com/openwashdata/fslogisticskampala","https://openwashdata.github.io/fslogisticskampala/",2,"v1.0.0","main",2024-07-18,2026-10-03,,TRUE,TRUE,,"main","1.0.0-dev",TRUE,FALSE,FALSE
-"fsmglobal","Global Faecal Sludge Emptying Services Demand","Global faecal sludge emptying demand data for 175 countries and territories, based on 2017 population figures. Demand is quantified by the population served by one of four emptying methods (mechanized, non-mechanized, unemptiable, no facility). The demand is disaggregated into urban and rural proportions.","0.0.1",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Nicola Greene; Sarah Hennessy; Tate W. Rogers; Jocelyn Tsai; Francis L. de los Reyes III; Lars Schöbitz","CC BY 4.0",2023-04-26,"open data, washdata, faecal sludge management, emptying services, sanitation, demand, low- and middle-income countries, global","Global, 175 countries and territories in Africa, Asia, Latin America and the Caribbean, and Oceania","2017-01-01/2017-12-31","10.5281/zenodo.8208292","0.0.1","https://github.com/openwashdata/fsmglobal","https://openwashdata.github.io/fsmglobal/",1,"v0.0.1","main",2022-12-13,2026-09-24,"faecal, faecal-sludge-emptying, open-data, open-datasets, open-research-data, population-data, r",TRUE,TRUE,,,,TRUE,TRUE,TRUE
-"gdho","Global Database of Humanitarian Organizations","A dataset of global humanitarian organizations collected by Humanitarian Outcomes.","0.0.2",TRUE,,"Mian Zhong","0009-0009-4546-7214","Mian Zhong; Abby Stoddard; Tichakunda Mangono","CC BY 4.0",2024-02-29,"humanitarian, humanitarian-aid, open-data, openwashdata, r",,,"10.5281/zenodo.10727977","0.0.2","https://github.com/openwashdata/gdho","https://openwashdata.github.io/gdho/",2,"v0.0.1","main",2023-09-21,2026-10-05,"humanitarian, humanitarian-aid, open-data, openwashdata, r",TRUE,TRUE,,,,TRUE,FALSE,FALSE
-"glaas","Complete Data from the Global Analysis and Assessment of Sanitation and Drinking-Water (GLAAS)","An R data package providing comprehensive access to the UN-Water Global Analysis and Assessment of Sanitation and Drinking-water (GLAAS) dataset. The WHO GLAAS survey collects data on water, sanitation, and hygiene (WASH) systems, policies, and financing from countries worldwide.","0.2.0",FALSE,,"Adriana Clavijo Daza","0009-0002-0589-2274","Nicolò Massari; Colin Walder; Adriana Clavijo Daza","CC BY 4.0",2026-02-05,"glaas, r, rpackage, wash",,,,"0.2.0","https://github.com/openwashdata/glaas","https://openwashdata.github.io/glaas/",1,"v0.2.0","main",2025-04-28,2026-03-27,"glaas, r, rpackage, wash",FALSE,FALSE,,,,FALSE,FALSE,FALSE
-"glossarywho","WHO Glossary","This package provides access to a tidy version of the WHO Glossary (https://www.who.int/publications/i/item/9789240105485) and thematic areas for each term.","1.0.2",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Yash Dubey; Lars Schöbitz","CC BY 4.0",2025-01-28,"open data, washdata, glossary, health data, health statistics, public health indicators, data governance, WHO","Global","2025-01-01/2025-12-31","10.5281/zenodo.14754016","1.0.2","https://github.com/openwashdata/glossarywho","https://openwashdata.github.io/glossarywho/",2,"v1.0.1","main",2025-01-28,2026-09-24,,TRUE,TRUE,,,,TRUE,TRUE,TRUE
-"grdwtrsmpkwale","Groundwater analysis from 2016 in Kwale, Kenya","The goal of grdwtrsmpkwale is to provide datasets for research and planning of water and solid waste management in Kwale, Kenya. This package includes water analysis data collected in 2016 combined with the geospatial data from the collection points.","0.0.1",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Sebastian Camilo Loos; Mian Zhong; Rob Hope; Lars Schöbitz","CC BY 4.0",2023-10-16,"open data, washdata, groundwater, water quality, Kwale, Kenya","Kwale, Kenya","2016-03-01/2016-06-25","10.5281/zenodo.10016874","0.0.1","https://github.com/openwashdata/grdwtrsmpkwale","https://openwashdata.github.io/grdwtrsmpkwale/",2,"v0.0.1","main",2023-08-17,2026-09-24,"groundwater, groundwater-data, kenya, opendata, openwashdata, r",TRUE,TRUE,,,,TRUE,TRUE,TRUE
-"gwinfraassess","Groundwater Monitoring Wells, Nkhotakota, Malawi 2022-2023","The Groundwater Monitoring Infrastructure Assessment Dataset (2022 to 2023) is an open dataset published by BASEflow Malawi. The dataset contains field observations collected during an assessment of groundwater monitoring infrastructure in Nkhotakota District, Malawi. It includes information on monitoring well characteristics, groundwater level measurements, monitoring equipment, site accessibility, infrastructure condition, community awareness, and recommended maintenance and rehabilitation actions.","1.0.1",TRUE,,"Emmanuel Mhango","0000-0003-3197-6244","Emmanuel Mhango","CC BY 4.0",2026-08-07,"open data, washdata, groundwater, groundwater monitoring, monitoring wells, water levels, Malawi","Nkhotakota, Malawi","2022-02-08/2023-10-04","10.5281/zenodo.21839342","1.0.1","https://github.com/openwashdata/gwinfraassess","https://openwashdata.github.io/gwinfraassess/",1,"v1.0.0","main",2026-08-07,2026-09-23,,TRUE,TRUE,,,,TRUE,TRUE,TRUE
-"handpumpstatusdata","Chiradzulu Handpump Functionality Verification Survey","This dataset contains detailed field survey records of borehole and handpump functionality verification exercises conducted in Chiradzulu District, Malawi in February 2020.","1.0.1",TRUE,,"Emmanuel Mhango","0000-0003-3197-6244","Emmanuel Mhango","CC BY 4.0",2026-09-23,"open data, washdata, handpumps, boreholes, water point functionality, water supply, Malawi","Chiradzulu, Malawi","2020-02-06/2020-11-06","10.5281/zenodo.17474593","1.0.1","https://github.com/openwashdata/handpumpstatusdata","https://openwashdata.github.io/handpumpstatusdata/",1,"v1.0.0","main",2025-08-12,2026-09-23,"handpump, wash, waterpoints",TRUE,TRUE,,,,TRUE,TRUE,TRUE
-"hydrogeologicalghana","Hydrogeological Dynamics Data in Ghana","This package contains data on boreholes collected to study the hydrogeological dynamics in the greater Accra and Ashanti regions of Ghana.","0.0.1",TRUE,,"Adriana Clavijo Daza","0009-0002-0589-2274","Benedict Addae-Mensah; Elizabeth Tilley; Adriana Clavijo Daza","CC BY 4.0",2025-08-05,"open data, washdata, boreholes, groundwater, hydrogeology, pumping tests, aquifers, Ghana","Greater Accra and Ashanti regions, Ghana","2001-01-01/2001-01-03","10.5281/zenodo.16743741","0.0.1","https://github.com/openwashdata/hydrogeologicalghana","https://openwashdata.github.io/hydrogeologicalghana/",1,"v0.0.1","main",2025-07-24,2026-09-24,,TRUE,TRUE,,,,TRUE,TRUE,TRUE
+"fecalcanuga","Non-Sewered Sanitation Containments, Canada and Uganda 2023-2024","This data package contains data representing 5 months of field work from April - June 2023 (Canada) and January - February 2024 (Uganda) collecting household and commercial wastewater containment data and characterizing physical, chemical and greenhouse gas data for 22 non-sewered sanitation sites on southern Vancouver island and the southern gulf islands in British Columbia, Canada and 19 sites in Kampala, Uganda.","0.1.0",TRUE,,"Kelsey Shaw","0000-0001-7417-110X","Kelsey Shaw; Caetano Dorea; Linda Strande; Charles Niwagaba; Mian Zhong","CC BY 4.0",2026-06-22,"open data, washdata, non-sewered sanitation, fecal sludge, septic tanks, greenhouse gas emissions, Canada, Uganda","Southern Vancouver Island and the Southern Gulf Islands, British Columbia, Canada; Kampala, Uganda","2023-04-06/2024-02-13","10.5281/zenodo.20795916","0.1.0","https://github.com/openwashdata/fecalcanuga","https://openwashdata.github.io/fecalcanuga/",4,"v0.1.0","main",2026-06-18,2026-11-01,,TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"floodchlorinationsurvey","USAID Flood Response Rehabilitation and Chlorination Survey","This R package provides tools for analyzing and visualizing data from the USAID Flood Response Rehabilitation and Chlorination Survey conducted in Mulanje, Malawi (2019–2020). It includes functions to assess handpump component replacements, evaluate changes in functionality before and after rehabilitation, and identify common repair trends using mWater-collected data.","0.1.0",TRUE,,"Emmanuel Mhango","0000-0003-3197-6244","Emmanuel Mhango","CC BY 4.0",2025-07-01,,,,"10.5281/zenodo.15846578","0.1.0","https://github.com/openwashdata/floodchlorinationsurvey","https://openwashdata.github.io/floodchlorinationsurvey/",1,"v0.1.0","main",2025-06-30,2026-11-01,,TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"floodresponsemw","Water Point Assessments - USAID Flood Response Malawi 2019-2020","Field-level data on rural water point status and functionality across Malawi, collected during the USAID Flood Response initiative (2019-2020). Includes GPS locations, flood impact indicators, pump functionality, water quality measurements, and microbial contamination data from mWater mobile assessments.","0.0.2",TRUE,,"Emmanuel Mhango","0000-0003-3197-6244","Emmanuel Mhango","CC BY 4.0",2026-09-23,"open data, washdata, water points, flood response, handpumps, water quality, Malawi","Malawi","2019-05-27/2020-02-26","10.5281/zenodo.17432023","0.0.2","https://github.com/openwashdata/floodresponsemw","https://openwashdata.github.io/floodresponsemw/",1,"v0.0.1","main",2025-06-27,2026-11-01,"flood, floodresponse, waterpoints",TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"fslogisticskampala","Data on Faecal Sludge Transporting Logistics in Kampala, Uganda","Contains two data resources. `trips` contains the GPS locations of faecal sludge emptying trucks collecting sludge from pit latrines and septic tanks in Kampala, Uganda. Each trip is recorded with a unique identifier, the numberplate of the truck, the date and time of the record. Data was collected from 30th March 2015 until 25th June 2015. `trucks` has additional information on the volume of each truck.","1.0.0",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Lars Schöbitz","CC BY 4.0",2026-07-08,,,,"10.5281/zenodo.21260446","1.0.0","https://github.com/openwashdata/fslogisticskampala","https://openwashdata.github.io/fslogisticskampala/",2,"v1.0.0","main",2024-07-18,2026-11-01,,TRUE,TRUE,"1.2.2","v1.1.0","1.0.0-dev",TRUE,TRUE,TRUE
+"fsmglobal","Global Faecal Sludge Emptying Services Demand","Global faecal sludge emptying demand data for 175 countries and territories, based on 2017 population figures. Demand is quantified by the population served by one of four emptying methods (mechanized, non-mechanized, unemptiable, no facility). The demand is disaggregated into urban and rural proportions.","0.0.1",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Nicola Greene; Sarah Hennessy; Tate W. Rogers; Jocelyn Tsai; Francis L. de los Reyes III; Lars Schöbitz","CC BY 4.0",2023-04-26,"open data, washdata, faecal sludge management, emptying services, sanitation, demand, low- and middle-income countries, global","Global, 175 countries and territories in Africa, Asia, Latin America and the Caribbean, and Oceania","2017-01-01/2017-12-31","10.5281/zenodo.8208292","0.0.1","https://github.com/openwashdata/fsmglobal","https://openwashdata.github.io/fsmglobal/",1,"v0.0.1","main",2022-12-13,2026-11-01,"faecal, faecal-sludge-emptying, open-data, open-datasets, open-research-data, population-data, r",TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"gdho","Global Database of Humanitarian Organizations","A dataset of global humanitarian organizations collected by Humanitarian Outcomes.","0.0.2",TRUE,,"Mian Zhong","0009-0009-4546-7214","Mian Zhong; Abby Stoddard; Tichakunda Mangono","CC BY 4.0",2024-02-29,"humanitarian, humanitarian-aid, open-data, openwashdata, r",,,"10.5281/zenodo.10727977","0.0.2","https://github.com/openwashdata/gdho","https://openwashdata.github.io/gdho/",2,"v0.0.1","main",2023-09-21,2026-11-01,"humanitarian, humanitarian-aid, open-data, openwashdata, r",TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"glaas","Complete Data from the Global Analysis and Assessment of Sanitation and Drinking-Water (GLAAS)","An R data package providing comprehensive access to the UN-Water Global Analysis and Assessment of Sanitation and Drinking-water (GLAAS) dataset. The WHO GLAAS survey collects data on water, sanitation, and hygiene (WASH) systems, policies, and financing from countries worldwide.","0.2.0",FALSE,,"Adriana Clavijo Daza","0009-0002-0589-2274","Nicolò Massari; Colin Walder; Adriana Clavijo Daza","CC BY 4.0",2026-02-05,"glaas, r, rpackage, wash",,,,"0.2.0","https://github.com/openwashdata/glaas","https://openwashdata.github.io/glaas/",1,"v0.2.0","main",2025-04-28,2026-11-01,"glaas, r, rpackage, wash",FALSE,FALSE,"1.2.2","v1.1.0",,FALSE,TRUE,FALSE
+"glossarywho","WHO Glossary","This package provides access to a tidy version of the WHO Glossary (https://www.who.int/publications/i/item/9789240105485) and thematic areas for each term.","1.0.2",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Yash Dubey; Lars Schöbitz","CC BY 4.0",2025-01-28,"open data, washdata, glossary, health data, health statistics, public health indicators, data governance, WHO","Global","2025-01-01/2025-12-31","10.5281/zenodo.14754016","1.0.2","https://github.com/openwashdata/glossarywho","https://openwashdata.github.io/glossarywho/",2,"v1.0.1","main",2025-01-28,2026-11-01,,TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"grdwtrsmpkwale","Groundwater analysis from 2016 in Kwale, Kenya","The goal of grdwtrsmpkwale is to provide datasets for research and planning of water and solid waste management in Kwale, Kenya. This package includes water analysis data collected in 2016 combined with the geospatial data from the collection points.","0.0.1",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Sebastian Camilo Loos; Mian Zhong; Rob Hope; Lars Schöbitz","CC BY 4.0",2023-10-16,"open data, washdata, groundwater, water quality, Kwale, Kenya","Kwale, Kenya","2016-03-01/2016-06-25","10.5281/zenodo.10016874","0.0.1","https://github.com/openwashdata/grdwtrsmpkwale","https://openwashdata.github.io/grdwtrsmpkwale/",2,"v0.0.1","main",2023-08-17,2026-11-01,"groundwater, groundwater-data, kenya, opendata, openwashdata, r",TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"gwinfraassess","Groundwater Monitoring Wells, Nkhotakota, Malawi 2022-2023","The Groundwater Monitoring Infrastructure Assessment Dataset (2022 to 2023) is an open dataset published by BASEflow Malawi. The dataset contains field observations collected during an assessment of groundwater monitoring infrastructure in Nkhotakota District, Malawi. It includes information on monitoring well characteristics, groundwater level measurements, monitoring equipment, site accessibility, infrastructure condition, community awareness, and recommended maintenance and rehabilitation actions.","1.0.1",TRUE,,"Emmanuel Mhango","0000-0003-3197-6244","Emmanuel Mhango","CC BY 4.0",2026-08-07,"open data, washdata, groundwater, groundwater monitoring, monitoring wells, water levels, Malawi","Nkhotakota, Malawi","2022-02-08/2023-10-04","10.5281/zenodo.21839342","1.0.1","https://github.com/openwashdata/gwinfraassess","https://openwashdata.github.io/gwinfraassess/",1,"v1.0.0","main",2026-08-07,2026-11-01,,TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"handpumpstatusdata","Chiradzulu Handpump Functionality Verification Survey","This dataset contains detailed field survey records of borehole and handpump functionality verification exercises conducted in Chiradzulu District, Malawi in February 2020.","1.0.1",TRUE,,"Emmanuel Mhango","0000-0003-3197-6244","Emmanuel Mhango","CC BY 4.0",2026-09-23,"open data, washdata, handpumps, boreholes, water point functionality, water supply, Malawi","Chiradzulu, Malawi","2020-02-06/2020-11-06","10.5281/zenodo.17474593","1.0.1","https://github.com/openwashdata/handpumpstatusdata","https://openwashdata.github.io/handpumpstatusdata/",1,"v1.0.0","main",2025-08-12,2026-11-01,"handpump, wash, waterpoints",TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"hydrogeologicalghana","Hydrogeological Dynamics Data in Ghana","This package contains data on boreholes collected to study the hydrogeological dynamics in the greater Accra and Ashanti regions of Ghana.","0.0.1",TRUE,,"Adriana Clavijo Daza","0009-0002-0589-2274","Benedict Addae-Mensah; Elizabeth Tilley; Adriana Clavijo Daza","CC BY 4.0",2025-08-05,"open data, washdata, boreholes, groundwater, hydrogeology, pumping tests, aquifers, Ghana","Greater Accra and Ashanti regions, Ghana","2001-01-01/2001-01-03","10.5281/zenodo.16743741","0.0.1","https://github.com/openwashdata/hydrogeologicalghana","https://openwashdata.github.io/hydrogeologicalghana/",1,"v0.0.1","main",2025-07-24,2026-11-01,,TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
 "jmpdata","Input Data and Indicator Estimates from the WHO/UNICEF Joint Monitoring Programme","Contains two data resources from the WHO/UNICEF Joint Monitoring Programme (JMP) for Water Supply, Sanitation and Hygiene. `jmpraw` holds the survey-level input data on sanitation that underlies the JMP estimates, collected from the country files published on <https://washdata.org>. `jmpindicators` holds the modelled JMP indicator estimates for water, sanitation and hygiene from the JMP world file. Both datasets are packaged from the JMP 2025 release.","0.2.0",FALSE,,"Lars Schöbitz","0000-0003-2196-5015","Lars Schöbitz","CC BY 4.0",2026-08-20,,,,,"0.2.0","https://github.com/openwashdata/jmpdata","https://openwashdata.github.io/jmpdata/",2,"v0.1.0","main",2022-04-26,2026-10-03,,TRUE,TRUE,,,,FALSE,FALSE,FALSE
-"kalaiwash","Household Water Insecurity and Drinking Water Service Levels from the KALAI Project in Nampula, Mozambique","Baseline (November 2024) and endline (June 2025) household survey data from the KALAI water, sanitation and hygiene project of HELVETAS in Larde, Memba, Moma and Mecuburi districts, Nampula Province, Mozambique. The data cover 275 household interviews and include the primary drinking water source classified with the WHO/UNICEF Joint Monitoring Programme (JMP) service ladder, water collection times and volumes, sanitation and handwashing practices, and the 12-item Household Water Insecurity Experiences (HWISE) Scale with its summary score and insecurity level.","0.1.0",TRUE,,"Adriana Clavijo Daza","0009-0002-0589-2274","John Brogan; Adriana Clavijo Daza; Dercio Obra","CC BY 4.0",2026-10-05,,,,"10.5281/zenodo.23164217","0.1.0","https://github.com/openwashdata/kalaiwash","https://openwashdata.github.io/kalaiwash/",1,"v0.1.0","main",2026-08-24,2026-10-08,,TRUE,TRUE,,,,TRUE,FALSE,FALSE
-"mwefloodresponse","Malawi Emergency Flood Response Water Point Survey (2019–2020)","This dataset contains water point assessment data collected during an emergency flood response in Malawi between 2019 and 2020. The survey was conducted under the BASEflow program to evaluate the status, functionality, and safety of water points affected by flooding events.","0.0.2",TRUE,,"Emmanuel Mhango","0000-0003-3197-6244","Emmanuel Mhango","CC BY 4.0",2026-09-23,"open data, washdata, floods, emergency response, water points, water quality, Malawi","Southern Region, Malawi","2019-04-03/2020-02-12","10.5281/zenodo.18755616","0.0.2","https://github.com/openwashdata/mwefloodresponse","https://openwashdata.github.io/mwefloodresponse/",1,"v.0.0.1","main",2026-02-20,2026-09-23,"sanitation, wash, water",TRUE,TRUE,,,,TRUE,TRUE,TRUE
-"mwgroundwaterdata","Malawi Groundwater Monitoring Time-Series Dataset (2024–2025)","This dataset contains groundwater monitoring data collected from monitoring wells across 9 districts in Malawi between 2024 and 2025. The data were captured using automated data loggers installed in monitoring wells and were collected and managed by BASEflow. The dataset provides time-series measurements of key groundwater parameters, enabling detailed analysis of aquifer behavior across multiple geographic locations.","0.0.2",TRUE,,"Emmanuel Mhango","0000-0003-3197-6244","Emmanuel Mhango","CC BY 4.0",2026-09-23,"open data, washdata, groundwater, groundwater monitoring, water level, water quality, Malawi","Southern Region, Malawi","2024-12-31/2025-02-07","10.5281/zenodo.18798409","0.0.2","https://github.com/openwashdata/mwgroundwaterdata","https://openwashdata.github.io/mwgroundwaterdata/",1,"v.0.0.1","main",2026-02-26,2026-09-23,"groundwater, sanitation, wash, water, watermonitoring",TRUE,TRUE,,,,TRUE,TRUE,TRUE
-"nchalohhwatersurvey","Nchalo Water Project Household Survey 2021","Household and community survey data from rural communities around Nchalo, Malawi. Includes water access, livelihoods, governance, and infrastructure information collected via mWater platform to support water supply planning and rural development.","1.0.1",TRUE,,"Emmanuel Mhango","0000-0003-3197-6244","Emmanuel Mhango","CC BY 4.0",2026-09-23,"open data, washdata, household survey, water supply, boreholes, livelihoods, Nchalo, Malawi","Nchalo, Malawi","2021-04-07/2021-04-08","10.5281/zenodo.17522182","1.0.1","https://github.com/openwashdata/nchalohhwatersurvey","https://openwashdata.github.io/nchalohhwatersurvey/",1,"v1.0.0","main",2025-06-27,2026-10-05,"hygiene, sanitation, wash",TRUE,TRUE,,,,TRUE,TRUE,TRUE
-"planetaryhdi","Planetary Pressures Adjusted Human Development Index Data","Provides data on Planetary Pressures Adjusted Human Development, adjusted by carbon emissions per capita (production related) and materials footprint per capita.","0.1.1",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Yash Dubey; Lars Schöbitz","CC BY 4.0",2024-12-10,"open data, washdata, human development index, planetary pressures, carbon dioxide emissions, material footprint, sdgs","Worldwide","2021-01-01/2022-12-31","10.5281/zenodo.14355747","0.1.1","https://github.com/openwashdata/planetaryhdi","https://openwashdata.github.io/planetaryhdi/",1,"0.0.2","main",2024-12-10,2026-09-24,"emissions-per-capita, hdi, planetary-pressures, sdgs",TRUE,TRUE,,,,TRUE,TRUE,TRUE
-"portawaterperu","A Preliminary Review of Peruvian Potable Water System Data","Data to gain preliminary understanding of community potable water systems in Peru.","0.0.1",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Lauren Judah; Sebastian Camilo Loos; Mian Zhong; Lars Schöbitz","CC BY 4.0",2024-07-24,"open data, washdata, water supply, community water systems, drinking water, SIASAR, Peru","Peru","2015-06-02/2015-12-19","10.5281/zenodo.13134309","0.0.1","https://github.com/openwashdata/portawaterperu","https://openwashdata.github.io/portawaterperu/",1,"v0.0.1","main",2024-06-18,2026-09-24,,TRUE,TRUE,,,,TRUE,TRUE,TRUE
-"postfloodintervention","USAID Flood Response Post Intervention Survey Data","Post-intervention monitoring data for rural water points in the Mulanje district of Malawi, collected as part of the USAID Flood Response program during 2019-2020. The dataset includes comprehensive water point assessments covering physical condition, operational performance, hydraulic measurements, water quality parameters, and microbiological quality assessments.","0.1.2",TRUE,,"Emmanuel Mhango","0000-0003-3197-6244","Emmanuel Mhango","CC BY 4.0",2026-09-30,"open data, washdata, water points, water quality, boreholes, rehabilitation, flood response, E. coli, Malawi","Mulanje, Malawi","2019-06-13/2020-03-09","10.5281/zenodo.15837460","0.1.2","https://github.com/openwashdata/postfloodintervention","https://openwashdata.github.io/postfloodintervention/",1,"v0.1.1","main",2025-07-01,2026-10-05,"flood-intervation, malawi, sanitation, wash, waterpoints",TRUE,TRUE,,,,TRUE,TRUE,TRUE
-"rainwaterhsurvey","Rainwater Harvesting and Groundwater Recharge Survey, Malawi 2025","This dataset contains household-level survey data collected in 2025 under the BASEflow monitoring and data systems using the mWater digital data collection platform. The survey was conducted across selected communities to assess household water access conditions, perceptions of groundwater systems, and adoption of rainwater harvesting (RWH) practices.","1.0.1",TRUE,,"Emmanuel Mhango","0000-0003-3197-6244","Emmanuel Mhango","CC BY 4.0",2026-09-23,"open data, washdata, rainwater harvesting, groundwater recharge, household survey, water scarcity, Malawi","Balaka, Chikwawa and Machinga, Malawi","2025-01-01/2025-12-31","10.5281/zenodo.19610496","1.0.1","https://github.com/openwashdata/rainwaterhsurvey","https://openwashdata.github.io/rainwaterhsurvey/",1,"v1.0.0","main",2026-04-16,2026-09-23,"baseflow, groundwater, opendatawash, rainwater-harvesting",TRUE,TRUE,,,,TRUE,TRUE,TRUE
-"rwpfunctionality","Water point functionality in sub-Saharan Africa and South Asia","Water point monitoring data associated with the paper ""[Rural water point functionality estimates and associations: evidence from nine countries in sub-Saharan Africa and South Asia](https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023WR034679)"" (Murray, Anna L et al., 2024).","0.0.1",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Margaux Götschmann; Anna L. Murray; Gabriela Stone; Audrey R. Yang; Nicholas F. Lawrence; Hannah Matthews; Georgia L. Kayser; Lars Schöbitz","CC BY 4.0",2024-03-11,"open data, washdata, water points, functionality, rural water supply, water committees, Ethiopia, India, Malawi, Mali, Mozambique, Nepal, Niger, Rwanda, Uganda","Ethiopia, India, Malawi, Mali, Mozambique, Nepal, Niger, Rwanda, Uganda","2017-05-22/2020-12-19","10.5281/zenodo.10878634","0.0.1","https://github.com/openwashdata/rwpfunctionality","https://openwashdata.github.io/rwpfunctionality/",1,"v0.0.1","main",2024-03-11,2026-09-24,"management, open-data, r, wash, water, waterpoint",TRUE,TRUE,,,,TRUE,TRUE,TRUE
-"saniabidjan","Sanitation Facility Management in Abidjan, Cote d'Ivoire, 2018","This data package contains household survey data collected from two low-income areas of Abidjan, Cote d'Ivoire. The survey was focusing on practices related to the management of sanitation facilities, specifically, latrines and tanks.","0.0.1",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Phaniwa Zié Zoumana Coulibaly; Kouassi Dongo; Mian Zhong; Lars Schöbitz","CC BY 4.0",2024-07-30,"open data, washdata, sanitation, latrines, septic tanks, faecal sludge emptying, household survey, Abidjan, Cote d'Ivoire","Abobo and Yopougon, Abidjan, Cote d'Ivoire","2018-04-17/2018-04-21","10.5281/zenodo.13134219","0.0.1","https://github.com/openwashdata/saniabidjan","https://openwashdata.github.io/saniabidjan/",1,"v0.0.1","main",2024-07-03,2026-09-24,"abidjan, cote-d-ivoire, household-surveys, open-data, openwashdata, r, sanitation, wash, water-management",TRUE,TRUE,,,,TRUE,TRUE,TRUE
-"solidwastekampala","Quantity and Composition of Domestic Solid Waste in Kampala City","Domestic solid waste generation and composition data for 103 households in Kampala City, Uganda, collected over a seven-day measurement campaign in three parishes representing different income levels (Bwaise I, low income; Bukoto I, middle income; Ggaba, high income). Includes ten measured waste-category masses, derived per-household metrics, and household socio-economic characteristics. The data accompany the paper ""Quantity and composition of domestic solid waste in Kampala City as influenced by socioeconomic factors"" (Katukiza et al. 2026, Frontiers in Environmental Science, <doi:10.3389/fenvs.2026.1889921>).","1.0.2",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Alex Y. Katukiza; Charles B. Niwagaba; Ivan Feni; Shaluwa Namagembe; Swaib Semiyaga; Abubakar Batte; Lars Schöbitz; Musa Manga","CC BY 4.0",2026-09-23,"open data, washdata, solid waste, household waste, waste generation, waste composition, Kampala, Uganda","Kampala, Uganda","2025-01-14/2025-03-13","10.5281/zenodo.21519796","1.0.2","https://github.com/openwashdata/solidwastekampala","https://openwashdata.github.io/solidwastekampala/",1,"v1.0.1","main",2026-07-22,2026-10-03,,TRUE,TRUE,,,"1.0.0",TRUE,TRUE,TRUE
-"thyolocbcc","WASH in Childcare Centres in Thyolo and Chikwawa, Malawi (2021)","This dataset provides detailed information on Water, Sanitation, and Hygiene (WASH) conditions and related management practices in Community-Based Childcare Centres (CBCCs) across Thyolo and Chikwawa Districts in Malawi, collected in 2021. Data were gathered by BASEflow using the mWater digital data collection platform.","1.0.1",TRUE,,"Emmanuel Mhango","0000-0003-3197-6244","Emmanuel Mhango","CC BY 4.0",2026-09-23,"open data, washdata, childcare centres, early childhood development, sanitation, hygiene, water supply, Malawi","Thyolo and Chikwawa, Malawi","2021-08-23/2021-10-25","10.5281/zenodo.17540498","1.0.1","https://github.com/openwashdata/thyolocbcc","https://openwashdata.github.io/thyolocbcc/",1,"v1.0.0","main",2025-06-24,2026-09-23,"baseflow, cbcc, hygiene, openwashdata, sanitation, wash",TRUE,TRUE,,,,TRUE,TRUE,TRUE
-"ugabore","Borehole repair data from central Uganda","Data set about borehole repair records from the borehole operation and maintenance company operating in central Uganda. Population data is picked as an interview from a representative of the Local Water User Committees (LWUCs). The data on the technical specifications about the borehole is picked from the borehole records file from the company.","0.0.1",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Margaux Götschmann; Joseph Lwere; Lars Schöbitz","CC BY 4.0",2024-06-20,"open data, washdata, boreholes, borehole repair, operation and maintenance, groundwater, water supply, Uganda","Luwero, Wakiso and Nakaseke districts, Central Region, Uganda","2021-10-28/2023-11-25","10.5281/zenodo.12188178","0.0.1","https://github.com/openwashdata/ugabore","https://openwashdata.github.io/ugabore/",1,"v.0.0.1","main",2024-04-30,2026-09-24,"analysis, borehole, data, open-data, r, uganda, wash, water",TRUE,TRUE,,,,TRUE,TRUE,TRUE
-"undpcomposite","UNDP Composite Indicators Timeseries","Provides tidy data on the composite indices of the UNDP Human Development Report 2023/2024 (HDI, GDI, IHDI, GII and PHDI) and their components as a time series from 1990 to 2022 for 195 countries and territories and 11 UNDP aggregates.","1.0.2",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Yash Dubey; Lars Schöbitz","CC BY 4.0",2025-02-10,"open data, washdata, human development index, gender development index, gender inequality index, inequality, planetary pressures, time series, sdgs","Worldwide","1990-01-01/2022-12-31","10.5281/zenodo.14845847","1.0.2","https://github.com/openwashdata/undpcomposite","https://openwashdata.github.io/undpcomposite/",1,"v1.0.0","main",2025-02-10,2026-10-03,,TRUE,TRUE,,,,TRUE,TRUE,TRUE
-"unhcrwash","WASH Data From Refugee Camps and Settlements (UNHCR)","This is a dataset on WASH indicators in refugee camps and settlements. The data was collected from the UNHCR Information Management System (IRIS) and was available on the UNHCR WASH dashboard. This dataset includes data from 226 sites and 35 countries. The source dashboard has since been retired and the data now sits behind the login-gated iRHIS portal, so this dataset is a fixed historical snapshot (2013 to 2024) that can no longer be regenerated.","1.1.1",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Lars Schöbitz; Yash Dubey","CC BY 4.0",2026-06-22,"open data, washdata, refugee camps, refugee settlements, humanitarian WASH, water supply, sanitation, hygiene, UNHCR","Refugee camps and settlements in 35 countries in Africa, the Middle East, Asia and Latin America","2013-09-30/2024-12-31","10.5281/zenodo.14185116","1.1.1","https://github.com/openwashdata/unhcrwash","https://openwashdata.github.io/unhcrwash/",1,"v1.1.0","main",2024-11-13,2026-10-03,,TRUE,TRUE,,,,TRUE,TRUE,TRUE
-"universityrankingafrica","University Ranking Africa","Data from institutional and national levels was combined into a dataset to provide a comprehensive characterization of the top ranked Universities of every African country. This was done to demonstrate the correlation of certain attributes with the academic ranking performance. The dataset also highlights the difficulties of accessing data from many African Universities online.","0.0.2",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Samuel Sigrist; Sophia Skorik; Lars Schöbitz","CC BY 4.0",2026-09-23,"open data, washdata, universities, higher education, university rankings, Africa","Africa","2023-04-24/2023-06-23","10.5281/zenodo.10284864","0.0.2","https://github.com/openwashdata/universityrankingafrica","https://openwashdata.github.io/universityrankingafrica/",2,"v0.0.1","main",2023-12-04,2026-09-24,"africa, openwashdata, r, university-ranking",TRUE,TRUE,,,,TRUE,TRUE,TRUE
-"waschoolpiracema","WASH in Schools in Piracema, Brazil","The main goal of this study was to describe the profile of schools from the basic education system in the municipality of Piracema (Minas Gerais, Brazil). Moreover, we also aimed to compare the characteristics of schools, with a special concern to WASH, pre- (2020), peri- (2021) and post-COVID-19 pandemic (2022) to evaluate to what extend schools in Piracema made progress in providing WASH since the beginning of the COVID-19 pandemic. This study is a sub-project of a PhD project and an initial study comparing the BNSC from 2020 and 2021 has already been conducted and published by the author of this project (for more details see references). Findings will be essential for the next phase of the research, which will be the collection of primary data in schools in the municipality of Piracema through qualitative methods (interviews, on-spot observations and art-based research).","0.0.1",TRUE,,"Alexis Tabin","0009-0004-4908-9250","Alexis Tabin; Kasandra Poague; Mian Zhong","CC BY 4.0",2024-07-09,"open data, washdata, WASH in schools, water supply, sanitation, solid waste, school census, Piracema, Minas Gerais, Brazil","Piracema, Minas Gerais, Brazil","2020-01-01/2022-12-31","10.5281/zenodo.12701106","0.0.1","https://github.com/openwashdata/waschoolpiracema","https://openwashdata.github.io/waschoolpiracema/",1,"v0.0.1","main",2024-06-18,2026-09-24,"brazil, opendata, openwashdata, piracema, r, sanitation, wash",TRUE,TRUE,,,,TRUE,TRUE,TRUE
-"washinvestments","Multilateral Development Bank Investment in Water and Sanitation","Dataset on multilateral development bank (MDB) investment in water supply and sanitation: 1,872 project records of the World Bank, the African Development Bank and the Asian Development Bank, approved between 1963 and 2020, compiled to assess territorial trends, technology choices, distribution of financial burdens, and reforms to institutional arrangements. Most records are for projects in Africa and Asia.","0.0.2",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Margaux Götschmann; Andri Heidler; Muhil Nesi; Josiane Nikiema; Christoph Lüthi; Lars Schöbitz","CC BY 4.0",2024-05-16,"open data, washdata, multilateral development banks, investment, water supply, sanitation, Africa, Asia","Global, 149 countries in Africa, Asia, Latin America and the Caribbean, Europe and Oceania","1963-01-01/2020-12-31","10.5281/zenodo.11203433","0.0.2","https://github.com/openwashdata/washinvestments","https://openwashdata.github.io/washinvestments/",1,"v0.0.1","main",2024-03-11,2026-10-03,"africa, asia, investment, mdb, open-data, r, sanitation, wash, water",TRUE,TRUE,,,"1.0.0",TRUE,TRUE,TRUE
-"washmalawi","WASH Household Level Survey Data 2018 - 2023","This package provides access to Water, Sanitation, and Hygiene (WASH) household-level survey data collected in Malawi between 2018 and 2023. The dataset includes comprehensive indicators for monitoring WASH-related Sustainable Development Goals at the household level.","1.0.1",TRUE,,"Emmanuel Mhango","0000-0003-3197-6244","Emmanuel Mhango; Donald Robertson; Chifundo Mandala; M Nzengo; Muthi Nhlema; M. Banda; Khumbo Zinyongo; Christian Nedi; Leman Ngwena; M Kazembe; Yankho Mthindi; E. Mofolo; Jeffrey Bauleni; Khallen Malliot; Thandi Mtemangombe; Tamandani Tembo; Samuel Mlenga; Dufter Joshua; Andrew Mthunzi; Martha Kafuwa; Takondwa Tembo; Peter Singogo; Goodwin Mkandawire; Monica Msiska; Lemekezani Chilora; Tendai Jambo; William Kanyinji; Chikondi Kanyinji; Madalitso Kamamkhudza; Sylvia Siliya; Edward K Gadi; Buli Echika; Sunganani Monjeza; Derick Macheke; Fatsani Chinawa; Jonathan Sunthika; Precious Phiri; Bright Mphero; Rodney Kananji","CC BY 4.0",2025-04-30,,,,"10.5281/zenodo.15799918","1.0.1","https://github.com/openwashdata/washmalawi","https://openwashdata.github.io/washmalawi/",1,"v1.0.1","main",2025-04-29,2026-10-05,,TRUE,TRUE,,,,TRUE,FALSE,FALSE
-"washopenresearch","Dataset about open research data information in Water, Sanitation, and Hygiene","The goal of washopenresearch is to provide an overview of open research data related to Water Sanitation and Hygiene (WASH). The package provides access to seven datasets: `washdev`, `ws`, `jwh`, `aqua`, `uncnewsletter`, `ploswater`, and `datapapers`. Each dataset collects information on scientific articles about (1) article metadata (e.g. title, first author, correspondence author), (2) supplementary material information, (3) data availability statement, and (4) semantic information (e.g. keywords).","0.5.0",TRUE,,"Mian Zhong","0009-0009-4546-7214","Mian Zhong; Ludwig Luz; Lars Schöbitz; Yash Dubey","CC BY 4.0",2026-10-02,"open-data, open-research-data, open-science, openwashdata, sanitation, wash",,,"10.5281/zenodo.11185699","0.5.0","https://github.com/openwashdata/washopenresearch","https://openwashdata.github.io/washopenresearch/",7,"v0.5.0","main",2023-12-21,2026-10-08,"open-data, open-research-data, open-science, openwashdata, sanitation, wash",TRUE,TRUE,,,,TRUE,FALSE,FALSE
-"wastedata","Waste Site Survey Data (2017 - 2018)","This dataset contains survey records on cemeteries, burial grounds, and waste disposal sites in Malawi. The information was gathered through field enumerators using the mWater platform as part of a mapping initiative. Each record captures details such as the location of the site, its operational status, management arrangements, and opening or closing history. The dataset also includes data on the type and state of waste present, evidence of pollution, the sources of waste, and the population served by municipal facilities. In addition, it documents the types of operations at municipal, commercial, industrial, and sludge waste sites, as well as practices related to drinking water and waste water treatment.","0.0.0.9000",FALSE,,"Emmanuel Mhango","0000-0003-3197-6244","Emmanuel Mhango","CC BY 4.0",2025-09-01,"waste-data, waste-management",,,,,"https://github.com/openwashdata/wastedata","https://openwashdata.github.io/wastedata/",1,"v1.0.0","master",2025-09-01,2025-10-28,"waste-data, waste-management",TRUE,TRUE,,,,FALSE,FALSE,FALSE
-"wasteskipsblantyre","Locations of Public Waste Skips in Blantyre, Malawi","An R data package containing the locations of public waste skips in Blantyre, Malawi, updated in 2023, with the number of skips, vehicle access and the fill-up times reported at each location, and the points of interest for their collection (depot, dump site, compost site and gas stations).","0.1.0",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Mabvuto Yesaya; Limbani Msuku; Lars Schöbitz; Elizabeth Tilley; Sebastian Camilo Loos; Nicolas Seemann-Ricard","CC BY 4.0",,"open data, washdata, solid waste, waste skips, waste collection, Blantyre, Malawi","Blantyre, Malawi","2023-01-01/2023-12-31","10.5281/zenodo.6470364","0.1.0","https://github.com/openwashdata/wasteskipsblantyre","https://openwashdata.github.io/wasteskipsblantyre/",2,,"main",2023-07-05,2026-09-24,"data-visualization, geolocation, malawi, open-data, open-datasets, r, solid-waste, waste-management",TRUE,TRUE,,,,TRUE,TRUE,TRUE
-"waterconsumersurvey","Household Water Point Satisfaction Survey Data from Malawi","Provides household-level survey data on water access, reliability, and user satisfaction from Zomba and Mangochi Districts in Malawi. Collected in September 2021 using GPS-enabled devices, the dataset includes 423 households with information on water sources, infrastructure conditions, seasonal availability, and demographic indicators relevant to water access and decision-making.","0.0.0.9000",FALSE,,"Emmanuel Mhango","0000-0003-3197-6244","Emmanuel Mhango","CC BY 4.0",2025-07-16,,,,,"0.0.0.9000","https://github.com/openwashdata/waterconsumersurvey","https://openwashdata.github.io/waterconsumersurvey/",1,"v1.0.0","master",2025-06-26,2026-10-05,,TRUE,TRUE,,,,FALSE,FALSE,FALSE
-"watercostaccra","Household Water Costs and Coping Strategies, Accra 2023","A household survey on water costs and coping strategies (116 households) and a water point survey (49 water points, with E. coli and total coliform test results) were conducted in October and November 2023 in two low-income communities in metropolitan Accra, Ghana. These are Korle Gonno, a larger, well-planned coastal area with over 35 household water vendors, and Abuja, a small, densely packed, extralegal settlement with 15 water vendor and bathhouse businesses.","0.0.0.9000",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Elizabeth Vicario; Margaux Götschmann; Betty Avanu Davidson; Ebenezer F. Amankwaa; Mian Zhong; Lars Schöbitz","CC BY 4.0",2024-06-21,"open data, washdata, water costs, coping strategies, household survey, water points, water vendors, water quality, Accra, Ghana","Korle Gonno and Abuja, Accra, Ghana","2023-10-05/2023-11-23","10.5281/zenodo.13981224","0.0.0.9000","https://github.com/openwashdata/watercostaccra","https://openwashdata.github.io/watercostaccra/",2,"v0.0.0.9000","main",2024-06-18,2026-09-24,"accra, ghana, household-surveys, open-data, openwashdata, r, water-cost",TRUE,TRUE,,,,TRUE,TRUE,TRUE
-"waterpointstatus","Water Point Functionality and Service Monitoring, Malawi 2023","This dataset contains structured field survey responses collected from water point inspections and interviews with community members or water point committee representatives. Each record represents a single survey event linked to a specific water point, including GPS coordinates and detailed observations on infrastructure condition, functionality, water availability, maintenance practices, and governance arrangements.","1.0.0",TRUE,,"Emmanuel Mhango","0000-0003-3197-6244","Emmanuel Mhango","CC BY 4.0",2026-04-10,"open data, washdata, water points, functionality, water supply, service delivery, Malawi","Southern Region, Malawi","2023-01-01/2023-12-31","10.5281/zenodo.19498016","1.0.0","https://github.com/openwashdata/waterpointstatus","https://openwashdata.github.io/waterpointstatus/",1,"v1.0.0","main",2026-04-10,2026-10-01,"baseflow, boreholes, groundwater, wash, waterpoints",TRUE,TRUE,,,,TRUE,TRUE,TRUE
-"waterpumpkwale","Weekly Handpump Water Volumes, Kwale County, Kenya 2014-2015","This dataset contains a summary of the weekly volumetric output of handpumps monitored using Smart Handpump sensors in 2014 and 2015 in Kwale County, Kenya, together with the locations of the monitored pumps.","0.0.1",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Patrick Thomson; Rob Hope; Tim Foster; Mian Zhong; Lars Schöbitz","CC BY 4.0",2023-10-02,"open data, washdata, handpumps, water supply, groundwater, smart handpump, kwale, kenya","Kwale County, Kenya","2014-01-01/2015-12-31","10.5281/zenodo.8399886","0.0.1","https://github.com/openwashdata/waterpumpkwale","https://openwashdata.github.io/waterpumpkwale/",3,"v0.0.1","main",2023-08-16,2026-09-24,"africa, kenya, kwale, open-data, open-datasets, r, underground-water, upgro, water-pump",TRUE,TRUE,,,,TRUE,TRUE,TRUE
-"waterqualityuganda","Drinking Water Quality from Boreholes to Household Storage in Uganda","Monthly E. coli monitoring of drinking water along the chain from borehole sources to household storage in four Ugandan districts (Nakaseke, Kaabong, Kumi and Luuka) between November 2024 and September 2025. For each borehole, water was sampled at the source and, in three households using it, from the container used to carry water home and from the drinking water storage container. Samples were analysed by membrane filtration and classified into five contamination levels. The package provides four tidy datasets: field visits to boreholes, field visits to households, water samples with their laboratory results, and laboratory blanks.","0.0.0.9000",FALSE,,"Adriana Clavijo Daza","0009-0002-0589-2274","Cecilia Nansiimbi; Adriana Clavijo Daza","CC BY 4.0",2026-10-16,"water quality, E. coli, boreholes, household water storage, water transport, WASH, Uganda","Nakaseke, Kaabong, Kumi and Luuka districts, Uganda","2024-11-01/2025-09-16",,"0.0.0.9000","https://github.com/openwashdata/waterqualityuganda","https://openwashdata.github.io/waterqualityuganda/",4,,"main",2026-08-24,2026-10-23,,TRUE,TRUE,,"main",,TRUE,FALSE,TRUE
-"worldhdi","Human Development Index Worldwide 1990-2022 (2024)","Provides Human Development Index (HDI) trends from 1990 to 2022 for 195 countries and territories (193 of them ranked) and 15 UNDP aggregates (development groups, regions and the world), from the UNDP Human Development Report 2023/2024 Statistical Annex. It includes HDI ranks, changes in rank and average annual HDI growth.","1.0.2",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Yash Dubey; Lars Schöbitz","CC BY 4.0",2024-10-29,"open data, washdata, human development index, hdi, undp, development indicators, sdgs","Worldwide","1990-01-01/2022-12-31","10.5281/zenodo.14006109","1.0.2","https://github.com/openwashdata/worldhdi","https://openwashdata.github.io/worldhdi/",1,"V1.0.1","main",2024-10-28,2026-09-24,,TRUE,TRUE,,,,TRUE,TRUE,TRUE
-"wsabrazil","Wastewater management and household infrastructure in Brazil","This dataset about wastewater management and household infrastructure from various Brazilian regions provides insights into wastewater disposal habits, water sources, bathroom facilities, and sanitation infrastructure.","0.1.0",FALSE,,"Lars Schöbitz","0000-0003-2196-5015","Margaux Götschmann; Lais Santos; Lars Schöbitz","CC BY 4.0",2026-09-23,"open data, washdata, wastewater, sanitation, water supply, census, Brazil","Brazil","2010-08-01/2010-10-30",,"0.1.0","https://github.com/openwashdata/wsabrazil","https://openwashdata.github.io/wsabrazil/",1,,"main",2024-03-26,2026-10-03,"2010, brazil, infrastructure, open-data, r, sanitation, wash, wastewater, water",TRUE,TRUE,,,,TRUE,TRUE,TRUE
+"kalaiwash","Household Water Insecurity and Drinking Water Service Levels from the KALAI Project in Nampula, Mozambique","Baseline (November 2024) and endline (June 2025) household survey data from the KALAI water, sanitation and hygiene project of HELVETAS in Larde, Memba, Moma and Mecuburi districts, Nampula Province, Mozambique. The data cover 275 household interviews and include the primary drinking water source classified with the WHO/UNICEF Joint Monitoring Programme (JMP) service ladder, water collection times and volumes, sanitation and handwashing practices, and the 12-item Household Water Insecurity Experiences (HWISE) Scale with its summary score and insecurity level.","0.1.0",TRUE,,"Adriana Clavijo Daza","0009-0002-0589-2274","John Brogan; Adriana Clavijo Daza; Dercio Obra","CC BY 4.0",2026-10-05,,,,"10.5281/zenodo.23164217","0.1.0","https://github.com/openwashdata/kalaiwash","https://openwashdata.github.io/kalaiwash/",1,"v0.1.0","main",2026-08-24,2026-11-01,,TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"mwefloodresponse","Malawi Emergency Flood Response Water Point Survey (2019–2020)","This dataset contains water point assessment data collected during an emergency flood response in Malawi between 2019 and 2020. The survey was conducted under the BASEflow program to evaluate the status, functionality, and safety of water points affected by flooding events.","0.0.2",TRUE,,"Emmanuel Mhango","0000-0003-3197-6244","Emmanuel Mhango","CC BY 4.0",2026-09-23,"open data, washdata, floods, emergency response, water points, water quality, Malawi","Southern Region, Malawi","2019-04-03/2020-02-12","10.5281/zenodo.18755616","0.0.2","https://github.com/openwashdata/mwefloodresponse","https://openwashdata.github.io/mwefloodresponse/",1,"v.0.0.1","main",2026-02-20,2026-11-01,"sanitation, wash, water",TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"mwgroundwaterdata","Malawi Groundwater Monitoring Time-Series Dataset (2024–2025)","This dataset contains groundwater monitoring data collected from monitoring wells across 9 districts in Malawi between 2024 and 2025. The data were captured using automated data loggers installed in monitoring wells and were collected and managed by BASEflow. The dataset provides time-series measurements of key groundwater parameters, enabling detailed analysis of aquifer behavior across multiple geographic locations.","0.0.2",TRUE,,"Emmanuel Mhango","0000-0003-3197-6244","Emmanuel Mhango","CC BY 4.0",2026-09-23,"open data, washdata, groundwater, groundwater monitoring, water level, water quality, Malawi","Southern Region, Malawi","2024-12-31/2025-02-07","10.5281/zenodo.18798409","0.0.2","https://github.com/openwashdata/mwgroundwaterdata","https://openwashdata.github.io/mwgroundwaterdata/",1,"v.0.0.1","main",2026-02-26,2026-11-01,"groundwater, sanitation, wash, water, watermonitoring",TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"nchalohhwatersurvey","Nchalo Water Project Household Survey 2021","Household and community survey data from rural communities around Nchalo, Malawi. Includes water access, livelihoods, governance, and infrastructure information collected via mWater platform to support water supply planning and rural development.","1.0.1",TRUE,,"Emmanuel Mhango","0000-0003-3197-6244","Emmanuel Mhango","CC BY 4.0",2026-09-23,"open data, washdata, household survey, water supply, boreholes, livelihoods, Nchalo, Malawi","Nchalo, Malawi","2021-04-07/2021-04-08","10.5281/zenodo.17522182","1.0.1","https://github.com/openwashdata/nchalohhwatersurvey","https://openwashdata.github.io/nchalohhwatersurvey/",1,"v1.0.0","main",2025-06-27,2026-11-01,"hygiene, sanitation, wash",TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"planetaryhdi","Planetary Pressures Adjusted Human Development Index Data","Provides data on Planetary Pressures Adjusted Human Development, adjusted by carbon emissions per capita (production related) and materials footprint per capita.","0.1.1",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Yash Dubey; Lars Schöbitz","CC BY 4.0",2024-12-10,"open data, washdata, human development index, planetary pressures, carbon dioxide emissions, material footprint, sdgs","Worldwide","2021-01-01/2022-12-31","10.5281/zenodo.14355747","0.1.1","https://github.com/openwashdata/planetaryhdi","https://openwashdata.github.io/planetaryhdi/",1,"0.0.2","main",2024-12-10,2026-11-01,"emissions-per-capita, hdi, planetary-pressures, sdgs",TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"portawaterperu","A Preliminary Review of Peruvian Potable Water System Data","Data to gain preliminary understanding of community potable water systems in Peru.","0.0.1",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Lauren Judah; Sebastian Camilo Loos; Mian Zhong; Lars Schöbitz","CC BY 4.0",2024-07-24,"open data, washdata, water supply, community water systems, drinking water, SIASAR, Peru","Peru","2015-06-02/2015-12-19","10.5281/zenodo.13134309","0.0.1","https://github.com/openwashdata/portawaterperu","https://openwashdata.github.io/portawaterperu/",1,"v0.0.1","main",2024-06-18,2026-11-01,,TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"postfloodintervention","USAID Flood Response Post Intervention Survey Data","Post-intervention monitoring data for rural water points in the Mulanje district of Malawi, collected as part of the USAID Flood Response program during 2019-2020. The dataset includes comprehensive water point assessments covering physical condition, operational performance, hydraulic measurements, water quality parameters, and microbiological quality assessments.","0.1.2",TRUE,,"Emmanuel Mhango","0000-0003-3197-6244","Emmanuel Mhango","CC BY 4.0",2026-09-30,"open data, washdata, water points, water quality, boreholes, rehabilitation, flood response, E. coli, Malawi","Mulanje, Malawi","2019-06-13/2020-03-09","10.5281/zenodo.15837460","0.1.2","https://github.com/openwashdata/postfloodintervention","https://openwashdata.github.io/postfloodintervention/",1,"v0.1.1","main",2025-07-01,2026-11-01,"flood-intervation, malawi, sanitation, wash, waterpoints",TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"rainwaterhsurvey","Rainwater Harvesting and Groundwater Recharge Survey, Malawi 2025","This dataset contains household-level survey data collected in 2025 under the BASEflow monitoring and data systems using the mWater digital data collection platform. The survey was conducted across selected communities to assess household water access conditions, perceptions of groundwater systems, and adoption of rainwater harvesting (RWH) practices.","1.0.1",TRUE,,"Emmanuel Mhango","0000-0003-3197-6244","Emmanuel Mhango","CC BY 4.0",2026-09-23,"open data, washdata, rainwater harvesting, groundwater recharge, household survey, water scarcity, Malawi","Balaka, Chikwawa and Machinga, Malawi","2025-01-01/2025-12-31","10.5281/zenodo.19610496","1.0.1","https://github.com/openwashdata/rainwaterhsurvey","https://openwashdata.github.io/rainwaterhsurvey/",1,"v1.0.0","main",2026-04-16,2026-11-01,"baseflow, groundwater, opendatawash, rainwater-harvesting",TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"rwpfunctionality","Water point functionality in sub-Saharan Africa and South Asia","Water point monitoring data associated with the paper ""[Rural water point functionality estimates and associations: evidence from nine countries in sub-Saharan Africa and South Asia](https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023WR034679)"" (Murray, Anna L et al., 2024).","0.0.1",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Margaux Götschmann; Anna L. Murray; Gabriela Stone; Audrey R. Yang; Nicholas F. Lawrence; Hannah Matthews; Georgia L. Kayser; Lars Schöbitz","CC BY 4.0",2024-03-11,"open data, washdata, water points, functionality, rural water supply, water committees, Ethiopia, India, Malawi, Mali, Mozambique, Nepal, Niger, Rwanda, Uganda","Ethiopia, India, Malawi, Mali, Mozambique, Nepal, Niger, Rwanda, Uganda","2017-05-22/2020-12-19","10.5281/zenodo.10878634","0.0.1","https://github.com/openwashdata/rwpfunctionality","https://openwashdata.github.io/rwpfunctionality/",1,"v0.0.1","main",2024-03-11,2026-11-01,"management, open-data, r, wash, water, waterpoint",TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"saniabidjan","Sanitation Facility Management in Abidjan, Cote d'Ivoire, 2018","This data package contains household survey data collected from two low-income areas of Abidjan, Cote d'Ivoire. The survey was focusing on practices related to the management of sanitation facilities, specifically, latrines and tanks.","0.0.1",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Phaniwa Zié Zoumana Coulibaly; Kouassi Dongo; Mian Zhong; Lars Schöbitz","CC BY 4.0",2024-07-30,"open data, washdata, sanitation, latrines, septic tanks, faecal sludge emptying, household survey, Abidjan, Cote d'Ivoire","Abobo and Yopougon, Abidjan, Cote d'Ivoire","2018-04-17/2018-04-21","10.5281/zenodo.13134219","0.0.1","https://github.com/openwashdata/saniabidjan","https://openwashdata.github.io/saniabidjan/",1,"v0.0.1","main",2024-07-03,2026-11-01,"abidjan, cote-d-ivoire, household-surveys, open-data, openwashdata, r, sanitation, wash, water-management",TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"solidwastekampala","Quantity and Composition of Domestic Solid Waste in Kampala City","Domestic solid waste generation and composition data for 103 households in Kampala City, Uganda, collected over a seven-day measurement campaign in three parishes representing different income levels (Bwaise I, low income; Bukoto I, middle income; Ggaba, high income). Includes ten measured waste-category masses, derived per-household metrics, and household socio-economic characteristics. The data accompany the paper ""Quantity and composition of domestic solid waste in Kampala City as influenced by socioeconomic factors"" (Katukiza et al. 2026, Frontiers in Environmental Science, <doi:10.3389/fenvs.2026.1889921>).","1.0.2",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Alex Y. Katukiza; Charles B. Niwagaba; Ivan Feni; Shaluwa Namagembe; Swaib Semiyaga; Abubakar Batte; Lars Schöbitz; Musa Manga","CC BY 4.0",2026-09-23,"open data, washdata, solid waste, household waste, waste generation, waste composition, Kampala, Uganda","Kampala, Uganda","2025-01-14/2025-03-13","10.5281/zenodo.21519796","1.0.2","https://github.com/openwashdata/solidwastekampala","https://openwashdata.github.io/solidwastekampala/",1,"v1.0.1","main",2026-07-22,2026-11-01,,TRUE,TRUE,"1.2.2","v1.1.0","1.0.0",TRUE,TRUE,TRUE
+"thyolocbcc","WASH in Childcare Centres in Thyolo and Chikwawa, Malawi (2021)","This dataset provides detailed information on Water, Sanitation, and Hygiene (WASH) conditions and related management practices in Community-Based Childcare Centres (CBCCs) across Thyolo and Chikwawa Districts in Malawi, collected in 2021. Data were gathered by BASEflow using the mWater digital data collection platform.","1.0.1",TRUE,,"Emmanuel Mhango","0000-0003-3197-6244","Emmanuel Mhango","CC BY 4.0",2026-09-23,"open data, washdata, childcare centres, early childhood development, sanitation, hygiene, water supply, Malawi","Thyolo and Chikwawa, Malawi","2021-08-23/2021-10-25","10.5281/zenodo.17540498","1.0.1","https://github.com/openwashdata/thyolocbcc","https://openwashdata.github.io/thyolocbcc/",1,"v1.0.0","main",2025-06-24,2026-11-01,"baseflow, cbcc, hygiene, openwashdata, sanitation, wash",TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"ugabore","Borehole repair data from central Uganda","Data set about borehole repair records from the borehole operation and maintenance company operating in central Uganda. Population data is picked as an interview from a representative of the Local Water User Committees (LWUCs). The data on the technical specifications about the borehole is picked from the borehole records file from the company.","0.0.1",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Margaux Götschmann; Joseph Lwere; Lars Schöbitz","CC BY 4.0",2024-06-20,"open data, washdata, boreholes, borehole repair, operation and maintenance, groundwater, water supply, Uganda","Luwero, Wakiso and Nakaseke districts, Central Region, Uganda","2021-10-28/2023-11-25","10.5281/zenodo.12188178","0.0.1","https://github.com/openwashdata/ugabore","https://openwashdata.github.io/ugabore/",1,"v.0.0.1","main",2024-04-30,2026-11-01,"analysis, borehole, data, open-data, r, uganda, wash, water",TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"undpcomposite","UNDP Composite Indicators Timeseries","Provides tidy data on the composite indices of the UNDP Human Development Report 2023/2024 (HDI, GDI, IHDI, GII and PHDI) and their components as a time series from 1990 to 2022 for 195 countries and territories and 11 UNDP aggregates.","1.0.2",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Yash Dubey; Lars Schöbitz","CC BY 4.0",2025-02-10,"open data, washdata, human development index, gender development index, gender inequality index, inequality, planetary pressures, time series, sdgs","Worldwide","1990-01-01/2022-12-31","10.5281/zenodo.14845847","1.0.2","https://github.com/openwashdata/undpcomposite","https://openwashdata.github.io/undpcomposite/",1,"v1.0.0","main",2025-02-10,2026-11-01,,TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"unhcrwash","WASH Data From Refugee Camps and Settlements (UNHCR)","This is a dataset on WASH indicators in refugee camps and settlements. The data was collected from the UNHCR Information Management System (IRIS) and was available on the UNHCR WASH dashboard. This dataset includes data from 226 sites and 35 countries. The source dashboard has since been retired and the data now sits behind the login-gated iRHIS portal, so this dataset is a fixed historical snapshot (2013 to 2024) that can no longer be regenerated.","1.1.1",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Lars Schöbitz; Yash Dubey","CC BY 4.0",2026-06-22,"open data, washdata, refugee camps, refugee settlements, humanitarian WASH, water supply, sanitation, hygiene, UNHCR","Refugee camps and settlements in 35 countries in Africa, the Middle East, Asia and Latin America","2013-09-30/2024-12-31","10.5281/zenodo.14185116","1.1.1","https://github.com/openwashdata/unhcrwash","https://openwashdata.github.io/unhcrwash/",1,"v1.1.0","main",2024-11-13,2026-11-01,,TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"universityrankingafrica","University Ranking Africa","Data from institutional and national levels was combined into a dataset to provide a comprehensive characterization of the top ranked Universities of every African country. This was done to demonstrate the correlation of certain attributes with the academic ranking performance. The dataset also highlights the difficulties of accessing data from many African Universities online.","0.0.2",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Samuel Sigrist; Sophia Skorik; Lars Schöbitz","CC BY 4.0",2026-09-23,"open data, washdata, universities, higher education, university rankings, Africa","Africa","2023-04-24/2023-06-23","10.5281/zenodo.10284864","0.0.2","https://github.com/openwashdata/universityrankingafrica","https://openwashdata.github.io/universityrankingafrica/",2,"v0.0.1","main",2023-12-04,2026-11-01,"africa, openwashdata, r, university-ranking",TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"waschoolpiracema","WASH in Schools in Piracema, Brazil","The main goal of this study was to describe the profile of schools from the basic education system in the municipality of Piracema (Minas Gerais, Brazil). Moreover, we also aimed to compare the characteristics of schools, with a special concern to WASH, pre- (2020), peri- (2021) and post-COVID-19 pandemic (2022) to evaluate to what extend schools in Piracema made progress in providing WASH since the beginning of the COVID-19 pandemic. This study is a sub-project of a PhD project and an initial study comparing the BNSC from 2020 and 2021 has already been conducted and published by the author of this project (for more details see references). Findings will be essential for the next phase of the research, which will be the collection of primary data in schools in the municipality of Piracema through qualitative methods (interviews, on-spot observations and art-based research).","0.0.1",TRUE,,"Alexis Tabin","0009-0004-4908-9250","Alexis Tabin; Kasandra Poague; Mian Zhong","CC BY 4.0",2024-07-09,"open data, washdata, WASH in schools, water supply, sanitation, solid waste, school census, Piracema, Minas Gerais, Brazil","Piracema, Minas Gerais, Brazil","2020-01-01/2022-12-31","10.5281/zenodo.12701106","0.0.1","https://github.com/openwashdata/waschoolpiracema","https://openwashdata.github.io/waschoolpiracema/",1,"v0.0.1","main",2024-06-18,2026-11-01,"brazil, opendata, openwashdata, piracema, r, sanitation, wash",TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"washinvestments","Multilateral Development Bank Investment in Water and Sanitation","Dataset on multilateral development bank (MDB) investment in water supply and sanitation: 1,872 project records of the World Bank, the African Development Bank and the Asian Development Bank, approved between 1963 and 2020, compiled to assess territorial trends, technology choices, distribution of financial burdens, and reforms to institutional arrangements. Most records are for projects in Africa and Asia.","0.0.2",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Margaux Götschmann; Andri Heidler; Muhil Nesi; Josiane Nikiema; Christoph Lüthi; Lars Schöbitz","CC BY 4.0",2024-05-16,"open data, washdata, multilateral development banks, investment, water supply, sanitation, Africa, Asia","Global, 149 countries in Africa, Asia, Latin America and the Caribbean, Europe and Oceania","1963-01-01/2020-12-31","10.5281/zenodo.11203433","0.0.2","https://github.com/openwashdata/washinvestments","https://openwashdata.github.io/washinvestments/",1,"v0.0.1","main",2024-03-11,2026-11-01,"africa, asia, investment, mdb, open-data, r, sanitation, wash, water",TRUE,TRUE,"1.2.2","v1.1.0","1.0.0",TRUE,TRUE,TRUE
+"washmalawi","WASH Household Level Survey Data 2018 - 2023","This package provides access to Water, Sanitation, and Hygiene (WASH) household-level survey data collected in Malawi between 2018 and 2023. The dataset includes comprehensive indicators for monitoring WASH-related Sustainable Development Goals at the household level.","1.0.1",TRUE,,"Emmanuel Mhango","0000-0003-3197-6244","Emmanuel Mhango; Donald Robertson; Chifundo Mandala; M Nzengo; Muthi Nhlema; M. Banda; Khumbo Zinyongo; Christian Nedi; Leman Ngwena; M Kazembe; Yankho Mthindi; E. Mofolo; Jeffrey Bauleni; Khallen Malliot; Thandi Mtemangombe; Tamandani Tembo; Samuel Mlenga; Dufter Joshua; Andrew Mthunzi; Martha Kafuwa; Takondwa Tembo; Peter Singogo; Goodwin Mkandawire; Monica Msiska; Lemekezani Chilora; Tendai Jambo; William Kanyinji; Chikondi Kanyinji; Madalitso Kamamkhudza; Sylvia Siliya; Edward K Gadi; Buli Echika; Sunganani Monjeza; Derick Macheke; Fatsani Chinawa; Jonathan Sunthika; Precious Phiri; Bright Mphero; Rodney Kananji","CC BY 4.0",2025-04-30,,,,"10.5281/zenodo.15799918","1.0.1","https://github.com/openwashdata/washmalawi","https://openwashdata.github.io/washmalawi/",1,"v1.0.1","main",2025-04-29,2026-11-01,,TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"washopenresearch","Dataset about open research data information in Water, Sanitation, and Hygiene","The goal of washopenresearch is to provide an overview of open research data related to Water Sanitation and Hygiene (WASH). The package provides access to seven datasets: `washdev`, `ws`, `jwh`, `aqua`, `uncnewsletter`, `ploswater`, and `datapapers`. Each dataset collects information on scientific articles about (1) article metadata (e.g. title, first author, correspondence author), (2) supplementary material information, (3) data availability statement, and (4) semantic information (e.g. keywords).","0.5.0",TRUE,,"Mian Zhong","0009-0009-4546-7214","Mian Zhong; Ludwig Luz; Lars Schöbitz; Yash Dubey","CC BY 4.0",2026-10-02,"open-data, open-research-data, open-science, openwashdata, sanitation, wash",,,"10.5281/zenodo.11185699","0.5.0","https://github.com/openwashdata/washopenresearch","https://openwashdata.github.io/washopenresearch/",7,"v0.5.0","main",2023-12-21,2026-11-01,"open-data, open-research-data, open-science, openwashdata, sanitation, wash",TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"wastedata","Waste Site Survey Data (2017 - 2018)","This dataset contains survey records on cemeteries, burial grounds, and waste disposal sites in Malawi. The information was gathered through field enumerators using the mWater platform as part of a mapping initiative. Each record captures details such as the location of the site, its operational status, management arrangements, and opening or closing history. The dataset also includes data on the type and state of waste present, evidence of pollution, the sources of waste, and the population served by municipal facilities. In addition, it documents the types of operations at municipal, commercial, industrial, and sludge waste sites, as well as practices related to drinking water and waste water treatment.","0.0.0.9000",FALSE,,"Emmanuel Mhango","0000-0003-3197-6244","Emmanuel Mhango","CC BY 4.0",2025-09-01,"waste-data, waste-management",,,,,"https://github.com/openwashdata/wastedata","https://openwashdata.github.io/wastedata/",1,"v1.0.0","main",2025-09-01,2026-11-01,"waste-data, waste-management",TRUE,TRUE,"1.2.2","v1.1.0",,FALSE,TRUE,TRUE
+"wasteskipsblantyre","Locations of Public Waste Skips in Blantyre, Malawi","An R data package containing the locations of public waste skips in Blantyre, Malawi, updated in 2023, with the number of skips, vehicle access and the fill-up times reported at each location, and the points of interest for their collection (depot, dump site, compost site and gas stations).","0.1.0",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Mabvuto Yesaya; Limbani Msuku; Lars Schöbitz; Elizabeth Tilley; Sebastian Camilo Loos; Nicolas Seemann-Ricard","CC BY 4.0",2026-10-31,"open data, washdata, solid waste, waste skips, waste collection, Blantyre, Malawi","Blantyre, Malawi","2023-01-01/2023-12-31","10.5281/zenodo.6470364","0.1.0","https://github.com/openwashdata/wasteskipsblantyre","https://openwashdata.github.io/wasteskipsblantyre/",2,,"main",2023-07-05,2026-11-01,"data-visualization, geolocation, malawi, open-data, open-datasets, r, solid-waste, waste-management",TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"waterconsumersurvey","Household Water Point Satisfaction Survey Data from Malawi","Provides household-level survey data on water access, reliability, and user satisfaction from Zomba and Mangochi Districts in Malawi. Collected in September 2021 using GPS-enabled devices, the dataset includes 423 households with information on water sources, infrastructure conditions, seasonal availability, and demographic indicators relevant to water access and decision-making.","0.0.0.9000",FALSE,,"Emmanuel Mhango","0000-0003-3197-6244","Emmanuel Mhango","CC BY 4.0",2025-07-16,,,,,"0.0.0.9000","https://github.com/openwashdata/waterconsumersurvey","https://openwashdata.github.io/waterconsumersurvey/",1,"v1.0.0","main",2025-06-26,2026-11-01,,TRUE,TRUE,"1.2.2","v1.1.0",,FALSE,TRUE,TRUE
+"watercostaccra","Household Water Costs and Coping Strategies, Accra 2023","A household survey on water costs and coping strategies (116 households) and a water point survey (49 water points, with E. coli and total coliform test results) were conducted in October and November 2023 in two low-income communities in metropolitan Accra, Ghana. These are Korle Gonno, a larger, well-planned coastal area with over 35 household water vendors, and Abuja, a small, densely packed, extralegal settlement with 15 water vendor and bathhouse businesses.","0.0.0.9000",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Elizabeth Vicario; Margaux Götschmann; Betty Avanu Davidson; Ebenezer F. Amankwaa; Mian Zhong; Lars Schöbitz","CC BY 4.0",2024-06-21,"open data, washdata, water costs, coping strategies, household survey, water points, water vendors, water quality, Accra, Ghana","Korle Gonno and Abuja, Accra, Ghana","2023-10-05/2023-11-23","10.5281/zenodo.13981224","0.0.0.9000","https://github.com/openwashdata/watercostaccra","https://openwashdata.github.io/watercostaccra/",2,"v0.0.0.9000","main",2024-06-18,2026-11-01,"accra, ghana, household-surveys, open-data, openwashdata, r, water-cost",TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"waterpointstatus","Water Point Functionality and Service Monitoring, Malawi 2023","This dataset contains structured field survey responses collected from water point inspections and interviews with community members or water point committee representatives. Each record represents a single survey event linked to a specific water point, including GPS coordinates and detailed observations on infrastructure condition, functionality, water availability, maintenance practices, and governance arrangements.","1.0.0",TRUE,,"Emmanuel Mhango","0000-0003-3197-6244","Emmanuel Mhango","CC BY 4.0",2026-04-10,"open data, washdata, water points, functionality, water supply, service delivery, Malawi","Southern Region, Malawi","2023-01-01/2023-12-31","10.5281/zenodo.19498016","1.0.0","https://github.com/openwashdata/waterpointstatus","https://openwashdata.github.io/waterpointstatus/",1,"v1.0.0","main",2026-04-10,2026-11-01,"baseflow, boreholes, groundwater, wash, waterpoints",TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"waterpumpkwale","Weekly Handpump Water Volumes, Kwale County, Kenya 2014-2015","This dataset contains a summary of the weekly volumetric output of handpumps monitored using Smart Handpump sensors in 2014 and 2015 in Kwale County, Kenya, together with the locations of the monitored pumps.","0.0.1",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Patrick Thomson; Rob Hope; Tim Foster; Mian Zhong; Lars Schöbitz","CC BY 4.0",2023-10-02,"open data, washdata, handpumps, water supply, groundwater, smart handpump, kwale, kenya","Kwale County, Kenya","2014-01-01/2015-12-31","10.5281/zenodo.8399886","0.0.1","https://github.com/openwashdata/waterpumpkwale","https://openwashdata.github.io/waterpumpkwale/",3,"v0.0.1","main",2023-08-16,2026-11-01,"africa, kenya, kwale, open-data, open-datasets, r, underground-water, upgro, water-pump",TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"waterqualityuganda","Drinking Water Quality from Boreholes to Household Storage in Uganda","Monthly E. coli monitoring of drinking water along the chain from borehole sources to household storage in four Ugandan districts (Nakaseke, Kaabong, Kumi and Luuka) between November 2024 and September 2025. For each borehole, water was sampled at the source and, in three households using it, from the container used to carry water home and from the drinking water storage container. Samples were analysed by membrane filtration and classified into five contamination levels. The package provides four tidy datasets: field visits to boreholes, field visits to households, water samples with their laboratory results, and laboratory blanks.","0.0.0.9000",FALSE,,"Adriana Clavijo Daza","0009-0002-0589-2274","Cecilia Nansiimbi; Adriana Clavijo Daza","CC BY 4.0",2026-10-16,"water quality, E. coli, boreholes, household water storage, water transport, WASH, Uganda","Nakaseke, Kaabong, Kumi and Luuka districts, Uganda","2024-11-01/2025-09-16",,"0.0.0.9000","https://github.com/openwashdata/waterqualityuganda","https://openwashdata.github.io/waterqualityuganda/",4,,"main",2026-08-24,2026-11-01,,TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"worldhdi","Human Development Index Worldwide 1990-2022 (2024)","Provides Human Development Index (HDI) trends from 1990 to 2022 for 195 countries and territories (193 of them ranked) and 15 UNDP aggregates (development groups, regions and the world), from the UNDP Human Development Report 2023/2024 Statistical Annex. It includes HDI ranks, changes in rank and average annual HDI growth.","1.0.2",TRUE,,"Lars Schöbitz","0000-0003-2196-5015","Yash Dubey; Lars Schöbitz","CC BY 4.0",2024-10-29,"open data, washdata, human development index, hdi, undp, development indicators, sdgs","Worldwide","1990-01-01/2022-12-31","10.5281/zenodo.14006109","1.0.2","https://github.com/openwashdata/worldhdi","https://openwashdata.github.io/worldhdi/",1,"V1.0.1","main",2024-10-28,2026-11-01,,TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
+"wsabrazil","Wastewater management and household infrastructure in Brazil","This dataset about wastewater management and household infrastructure from various Brazilian regions provides insights into wastewater disposal habits, water sources, bathroom facilities, and sanitation infrastructure.","0.1.0",FALSE,,"Lars Schöbitz","0000-0003-2196-5015","Margaux Götschmann; Lais Santos; Lars Schöbitz","CC BY 4.0",2026-09-23,"open data, washdata, wastewater, sanitation, water supply, census, Brazil","Brazil","2010-08-01/2010-10-30",,"0.1.0","https://github.com/openwashdata/wsabrazil","https://openwashdata.github.io/wsabrazil/",1,,"main",2024-03-26,2026-11-01,"2010, brazil, infrastructure, open-data, r, sanitation, wash, wastewater, water",TRUE,TRUE,"1.2.2","v1.1.0",,TRUE,TRUE,TRUE
diff --git a/inst/extdata/owd_variables.csv b/inst/extdata/owd_variables.csv
index d22898b..af0f09a 100644
--- a/inst/extdata/owd_variables.csv
+++ b/inst/extdata/owd_variables.csv
@@ -726,8 +726,8 @@
 "ds4owdanalytics","publishing_metadata","doi","character","Zenodo DOI of package"
 "ds4owdanalytics","publishing_metadata","temporal_coverage","logical","Temporal coverage of data"
 "ds4owdanalytics","publishing_metadata","keywords","character","Keywords to identify data"
-"fecalcanuga","containment","sample_id","factor","unique identifier for each sampling location in the format ##-Location-ddmmyyyy"
-"fecalcanuga","containment","location_id","factor","unique location identifier for each sampling day in the format of (#)-day of sampling (a) - location in that day"
+"fecalcanuga","containment","sample_id","character","unique identifier for each sampling location in the format ##-Location-ddmmyyyy"
+"fecalcanuga","containment","location_id","character","unique location identifier for each sampling day in the format of (#)-day of sampling (a) - location in that day"
 "fecalcanuga","containment","date","POSIXct","date of sampling"
 "fecalcanuga","containment","area","numeric","surface area of liquid surface in containment m^2"
 "fecalcanuga","containment","sludge_depth","numeric","depth in meters, of where from the top of the sludge the sample was taken"
@@ -736,51 +736,51 @@
 "fecalcanuga","containment","fs_volume","numeric","total volume of the sludge in containment in m^3"
 "fecalcanuga","containment","accumulation_rate","numeric","the accumulation rate in litres/capita -year (based on total volume and number of users)"
 "fecalcanuga","containment","scum_depth","numeric","the depth of the top scum layer in centimeters"
-"fecalcanuga","ghg","sample_id","factor","unique identifier for each sampling location in the format ##-Location-ddmmyyyy"
-"fecalcanuga","ghg","location_id","factor","unique location identifier for each sampling day in the format of (#)-day of sampling (a) - location in that day"
+"fecalcanuga","ghg","sample_id","character","unique identifier for each sampling location in the format ##-Location-ddmmyyyy"
+"fecalcanuga","ghg","location_id","character","unique location identifier for each sampling day in the format of (#)-day of sampling (a) - location in that day"
 "fecalcanuga","ghg","date","POSIXct","date of sampling"
 "fecalcanuga","ghg","users","numeric","average number of users for the sanitation system that was sampled"
 "fecalcanuga","ghg","flux_ch4","numeric","methane flux in grams/capita-day - based on number of users"
 "fecalcanuga","ghg","flux_co2","numeric","carbon dioxide flux in grams/capita-day - based on number of users"
 "fecalcanuga","ghg","flux_n2o","numeric","nitrous oxide flux in grams/capita-day - based on number of users"
-"fecalcanuga","household_survey","sample_id","factor","unique identifier for each sampling location in the format ##-Location-ddmmyyyy"
-"fecalcanuga","household_survey","location_id","factor","unique location identifier for each sampling day in the format of (#)-day of sampling (a) - location in that day"
+"fecalcanuga","household_survey","sample_id","character","unique identifier for each sampling location in the format ##-Location-ddmmyyyy"
+"fecalcanuga","household_survey","location_id","character","unique location identifier for each sampling day in the format of (#)-day of sampling (a) - location in that day"
 "fecalcanuga","household_survey","date","POSIXct","date of sampling"
 "fecalcanuga","household_survey","local_area_name","factor","community / area name that locals commonly use where samples were taken"
 "fecalcanuga","household_survey","establishment_type","factor","type of establishment where sampling occurred (household, commercial, school, office building, other)"
 "fecalcanuga","household_survey","users","numeric","average number of users for the sanitation system that was sampled"
 "fecalcanuga","household_survey","last_emptied","numeric","in years how long ago from sampling date the containment was last emptied"
-"fecalcanuga","household_survey","shared_toilet","factor","Is the toilet(s) connected to the sanitation containment shared or not (Yes/No)"
+"fecalcanuga","household_survey","shared_toilet","logical","Is the toilet(s) connected to the sanitation containment shared or not (Yes/No)"
 "fecalcanuga","household_survey","rent_or_own","factor","Is the establishment where the containment is rented or owned by the head of household?"
 "fecalcanuga","household_survey","containment","factor","The type of containment (septic tank, pit latrine, treatment plant unit, etc.)"
 "fecalcanuga","household_survey","lining","factor","The type of containment lining (fully lined, unlined, don't know)"
 "fecalcanuga","household_survey","lining_material","factor","The material the lining is made of if it is lined (fiberglass, concrete, PVC, unlined, etc.)"
-"fecalcanuga","household_survey","change_in_liquid_level","factor","Is there a change in liquid level due to seasonal variation (Y/N)"
-"fecalcanuga","household_survey","baffles","factor","Are there baffles in the containment (Y/N/I don't know)"
-"fecalcanuga","household_survey","outflow","factor","Is there an outflow for the containment (Y/N/I don't know)"
+"fecalcanuga","household_survey","change_in_liquid_level","logical","Is there a change in liquid level due to seasonal variation (Y/N)"
+"fecalcanuga","household_survey","baffles","logical","Are there baffles in the containment (Y/N/I don't know)"
+"fecalcanuga","household_survey","outflow","logical","Is there an outflow for the containment (Y/N/I don't know)"
 "fecalcanuga","household_survey","outflow_location","factor","If there is an outflow, where is it located (i.e., leech field)"
 "fecalcanuga","household_survey","toilet_type","factor","What is the type of toilet connected to the sanitation system (cistern flush, pour-flush, etc.)"
 "fecalcanuga","household_survey","anal_cleansing_material","factor","What type of material is used for anal cleansing (water, paper, both)"
-"fecalcanuga","household_survey","paper","numeric","Is paper used for anal cleansing (Yes = 1 | No = 0)"
-"fecalcanuga","household_survey","water","numeric","Is water used for anal cleansing (Yes = 1 | No = 0)"
-"fecalcanuga","household_survey","additives","factor","Are there additives added to the containment (Y/N/I don't know)"
+"fecalcanuga","household_survey","paper","logical","Is paper used for anal cleansing (Yes = 1 | No = 0)"
+"fecalcanuga","household_survey","water","logical","Is water used for anal cleansing (Yes = 1 | No = 0)"
+"fecalcanuga","household_survey","additives","logical","Are there additives added to the containment (Y/N/I don't know)"
 "fecalcanuga","household_survey","frequency","factor","If additives are added, in what frequency?"
 "fecalcanuga","household_survey","chemicals","factor","What chemicals are added to the sanitation system?"
 "fecalcanuga","household_survey","wastewater_type","factor","What are the types of wastewater that the containment collects (toilet, kitchen, laundry, bathing)"
-"fecalcanuga","household_survey","toilet","numeric","Does the containment collect this type of wastewater (Yes = 1 | No = 0)"
-"fecalcanuga","household_survey","bathing","numeric","Does the containment collect this type of wastewater (Yes = 1 | No = 0)"
-"fecalcanuga","household_survey","laundry","numeric","Does the containment collect this type of wastewater (Yes = 1 | No = 0)"
-"fecalcanuga","household_survey","kitchen","numeric","Does the containment collect this type of wastewater (Yes = 1 | No = 0)"
-"fecalcanuga","household_survey","water_connection","factor","What type of water connection does the establishment where sampling is occurring have (tap inside building, standpipe, other)?"
+"fecalcanuga","household_survey","toilet","logical","Does the containment collect this type of wastewater (Yes = 1 | No = 0)"
+"fecalcanuga","household_survey","bathing","logical","Does the containment collect this type of wastewater (Yes = 1 | No = 0)"
+"fecalcanuga","household_survey","laundry","logical","Does the containment collect this type of wastewater (Yes = 1 | No = 0)"
+"fecalcanuga","household_survey","kitchen","logical","Does the containment collect this type of wastewater (Yes = 1 | No = 0)"
+"fecalcanuga","household_survey","water_connection","logical","What type of water connection does the establishment where sampling is occurring have (tap inside building, standpipe, other)?"
 "fecalcanuga","household_survey","tap_inside_building","numeric","Does the establishment have this type of water connection (Yes = 1 | No = 0)"
 "fecalcanuga","household_survey","standpipe","numeric","Does the establishment have this type of water connection (Yes = 1 | No = 0)"
 "fecalcanuga","household_survey","containment_age","factor","What is the age (in years) of the containment system?"
 "fecalcanuga","household_survey","containment_constructed","factor","Who constructed the containment system (Technician, professional engineering, myself, don't know)?"
 "fecalcanuga","household_survey","containment_volume","numeric","What (in m^3) is the total volume of the containment?"
-"fecalcanuga","household_survey","fully_emptied","factor","When the system was last emptied was it emptied fully? (Y/N/I don't know)"
+"fecalcanuga","household_survey","fully_emptied","logical","When the system was last emptied was it emptied fully? (Y/N/I don't know)"
 "fecalcanuga","household_survey","emptying_interval","numeric","What is the average / typical emptying interval (in years) of the containment?"
-"fecalcanuga","household_survey","rainy_season","factor","Is it currently the rainy season? (Y/N)"
-"fecalcanuga","household_survey","solid_waste","factor","Does the containment contain solid waste (i.e., garbage) (Y/N)"
+"fecalcanuga","household_survey","rainy_season","logical","Is it currently the rainy season? (Y/N)"
+"fecalcanuga","household_survey","solid_waste","logical","Does the containment contain solid waste (i.e., garbage) (Y/N)"
 "fecalcanuga","household_survey","type","factor","If there is solid waste, what type is it?"
 "fecalcanuga","phys_chem_parameter","sample_id","factor","unique identifier for each sampling location in the format ##-Location-ddmmyyyy"
 "fecalcanuga","phys_chem_parameter","location_id","factor","unique location identifier for each sampling day in the format of (#)-day of sampling (a) - location in that day"
diff --git a/man/owdata-package.Rd b/man/owdata-package.Rd
index d4f8a1c..dfdf955 100644
--- a/man/owdata-package.Rd
+++ b/man/owdata-package.Rd
@@ -6,6 +6,8 @@
 \alias{owdata-package}
 \title{owdata: Index of openwashdata R Data Packages}
 \description{
+\if{html}{\figure{logo.png}{options: style='float: right' alt='logo' width='120'}}
+
 Index metapackage for the openwashdata R data packages. Ships a harvested catalog of every package in the openwashdata GitHub organisation, with its datasets and variables, as internal data behind accessor and search functions, and installs any listed package from the openwashdata R-universe. The catalog is refreshed by a weekly harvest.
 }
 \seealso{