cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.30152916.v1
title: Web-based predictive tool for vaginal and vulvar melanomas: a machine learning study

description: One in every 41 women develops malignant melanoma in their lifetime, with noncutaneous melanomas arising in areas such as the genitourinary (GU) system being particularly rare and aggressive. We used machine learning (ML) to build prognostic models for vaginal (VaM) and vulvar (VuM) melanomas and developed the first predictive web-based tool for survival in these cancers. We leveraged the SEER database (2000–2020) to assemble our cohort and extract relevant clinical and demographic variables. Prognostic factors were screened using univariate and multivariate Cox proportional hazards regression analyses. Subsequently, we developed five machine-learning classifiers to predict 5-year survival. The discrimination of each model was assessed using the area under the receiver operating characteristic curve (AUC-ROC), and calibration was examined to ensure reliability. Kaplan–Meier analyses were performed to visualize survival distributions across key subgroups. This study included 1575 patients, of whom 372 and 1203 had VaM and VuM, respectively. The median patient age was 67 years, and the median tumor size was 2.4 cm. The 5-year survival rate of patients with VuM (45.4%) was significantly higher than that of patients with VaM (15.2%) (P &lt; 0.001). This study highlights the aggressive nature of rare GU melanomas and the importance of surgical intervention and caution in the use of chemotherapy and radiotherapy. This study focused on rare and aggressive cancers known as VaM and VuM melanomas, which arise in the GU system. Using machine learning techniques, we analyzed patient data to identify factors affecting survival and created the first web-based tool to predict survival outcomes in these cancers. This study found that surgical treatment significantly improved survival rates, whereas chemotherapy and radiotherapy had mixed effects. Tumor size and marital status were identified as important predictors of survival. The developed web tool allows clinicians to input patient information and receive personalized survival predictions, helping guide treatment decisions. This study highlights the need for cautious use of therapies and offers innovative ways to personalize care for patients with these rare cancers of therapies and offers innovative ways to personalize care for patients with these rare cancers.
DOI: 10.57715/unr/1fa2mb/d9ium2
title: 2008_Cualidades Docentes Memorables.ods

description: Datos de 2008 sobre docentes memorables.
DOI: 10.15468/dl.yv2r63
title: Occurrence Download

description: A dataset containing 45 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Myrceugenia brevipedicellata"
 ]
}

 The dataset includes 45 records from 27 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0047087-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57715/unr/1fa2mb/6hzf4k
title: 2015_Cualidades Docentes Memorables.ods

description: Recolección anual de 2015; mantiene estructura.
DOI: 10.57715/unr/1fa2mb/qbmst2
title: 2024_Cualidades Docentes Memorables.ods

description: Archivo de 2024.
DOI: 10.57715/unr/1fa2mb/eewqsf
title: 2018_Cualidades Docentes Memorables.ods

description: Registro de 2018 sobre docentes memorables.
DOI: 10.57715/unr/1fa2mb/xrzf0u
title: 2017_Cualidades Docentes Memorables.ods

description: Datos recolectados en 2017.
DOI: 10.57715/unr/1fa2mb/xljuvs
title: 2012_Cualidades Docentes Memorables.ods

description: Compilación de respuestas de 2012; mismas variables que los años anteriores.
DOI: 10.15468/dl.ym92sh
title: Occurrence Download

description: A dataset containing 168411 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tracheophyta",
 "DecimalLatitude is greater than or equal to -20.914722",
 "DecimalLatitude is less than or equal to -15.914722",
 "DecimalLongitude is greater than or equal to 140.0",
 "DecimalLongitude is less than or equal to 145.0",
 "HasCoordinate is TRUE",
 "HasGeospatialIssue is FALSE"
 ]
}

 The dataset includes 168411 records from 94 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0047051-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57715/unr/1fa2mb/pphzdj
title: 2020_Cualidades Docentes Memorables.ods

description: Datos de 2020.
DOI: 10.57715/unr/1fa2mb/lynmrm
title: 2005_Cualidades Docentes Memorables.ods

description: Recolección de datos de 2005 sobre cualidades docentes.
DOI: 10.57715/unr/1fa2mb/g5d3y2
title: 2009_Cualidades Docentes Memorables.ods

description: Archivo de 2009 sobre docentes memorables.
DOI: 10.57715/unr/1fa2mb/nckqxk
title: 2004_Cualidades Docentes Memorables.ods

description: Archivo con respuestas de 2004 sobre docentes memorables.
DOI: 10.57715/unr/1fa2mb/mpmtqg
title: 2022_Cualidades Docentes Memorables.ods

description: Compilación de 2022; misma estructura que años anteriores.
DOI: 10.57715/unr/1fa2mb/czsz4g
title: 2021_Cualidades Docentes Memorables.ods

description: Relevamiento de 2021.
DOI: 10.57715/unr/1fa2mb/yeiuef
title: 2002_Cualidades Docentes Memorables.ods

description: Relevamiento inicial de cualidades de docentes memorables; contiene columnas: Año, Docente, Sexo, Curso, Asignatura, Cualidades.
DOI: 10.57715/unr/1fa2mb/hb1kav
title: 2007_Cualidades Docentes Memorables.ods

description: Registro anual de 2007 sobre docentes memorables.
DOI: 10.57715/unr/1fa2mb/xlv18c
title: 2011_Cualidades Docentes Memorables.ods

description: Registro de 2011 sobre docentes memorables.
DOI: 10.57715/unr/1fa2mb/u1c5qi
title: 2025_Cualidades Docentes Memorables.ods

description: Último relevamiento disponible (2025); se mantuvo la estructura de variables Año, Docente, Sexo, Curso, Asignatura, Cualidades.
DOI: 10.57715/unr/1fa2mb/0kqqgb
title: 2023_Cualidades Docentes Memorables.ods

description: Datos de 2023.
DOI: 10.21335/nmdc-297831853
title: Mesozooplankton, North Sea and Skagerrak 2006–2024

description: This dataset provides data on mesozooplankton from the northern North Sea and Skagerrak 2005-2024, collected and analyzed by the Plankton Research Group at the Institute of Marine Research (IMR), Norway.
The dataset includes information on taxa (species or higher taxonomic levels), life stages, and abundances of mesozooplankton 2005-2024. Three main transects (“Utsira–W”, “Hanstholm–Aberdeen”, and “Torungen–Hirtshals”) have been sampled approximately four times per year, in addition to larger-scale ecosystem surveys mainly conducted in spring (April to early May). Zooplankton data are also provided from three monitoring stations located along the Norwegian Skagerrak coast, sampled 1–2 times per month.
 Sampling has been conducted at predefined stations using a standard WP2 net (0.56 m opening diameter, 180 μm mesh size), towed vertically from near-bottom to the surface. Samples were preserved in formaldehyde and analyzed using a stereomicroscope for enumeration and species identification. Abundances are expressed as individuals per cubic meter (N/m³).
The IMR North Sea monitoring activity is part of the IMR project “Climate and Plankton in the North Sea and Skagerrak,” funded by the Ministry of Trade, Industry and Fisheries. The IMR coastal monitoring has been funded by the IMR Coastal Research Programme and the Norwegian Environment Agency.
This dataset was submitted to OSPAR via ICES DOME for inclusion in the OSPAR Intermediate Assessment 2029 (IA 2029) in OSPAR Region II (Greater North Sea).
A detailed description of methods, column names, and codes is provided in Appendix 1.
DOI: 10.57715/unr/1fa2mb/yhbkqj
title: Informe_datos_10.57715.UNR.1FA2MB.txt

description: Este archivo README de documentación proporciona una visión general del dataset relevante para entender y utilizar el dataset de manera efectiva.
DOI: 10.57715/unr/1fa2mb
title: Cualidades de docentes memorables reconocidos por ingresantes al Profesorado en Matemática de la Universidad Nacional de Rosario (2002-2025)

description: Este conjunto de datos reúne, de manera anual y continua (2002–2025), las cualidades de docentes memorables que identifican los ingresantes al Profesorado en Matemática (UNR) el primer día de clase de Práctica Profesional Docente I, denominada Práctica de la Enseñanza I hasta 2017. Cada persona participante menciona dos docentes recordados de su trayectoria educativa y consigna tres cualidades destacadas de cada uno, junto con asignatura, año escolar y género. El objetivo es posibilitar análisis longitudinales sobre atributos valorados en la docencia en general y en Matemática en particular. Tabla de contenidos 2002 Cualidades Docentes Memorables.ods 2003 Cualidades Docentes Memorables.ods 2004 Cualidades Docentes Memorables.ods 2005 Cualidades Docentes Memorables.ods 2006 Cualidades Docentes Memorables.ods 2007 Cualidades Docentes Memorables.ods 2008 Cualidades Docentes Memorables.ods 2009 Cualidades Docentes Memorables.ods 2010 Cualidades Docentes Memorables.ods 2011 Cualidades Docentes Memorables.ods 2012 Cualidades Docentes Memorables.ods 2013 Cualidades Docentes Memorables.ods 2014 Cualidades Docentes Memorables.ods 2015 Cualidades Docentes Memorables.ods 2016 Cualidades Docentes Memorables.ods 2017 Cualidades Docentes Memorables.ods 2018 Cualidades Docentes Memorables.ods 2019 Cualidades Docentes Memorables.ods 2020 Cualidades Docentes Memorables.ods 2021 Cualidades Docentes Memorables.ods 2022 Cualidades Docentes Memorables.ods 2023 Cualidades Docentes Memorables.ods 2024 Cualidades Docentes Memorables.ods 2025 Cualidades Docentes Memorables.ods Informe_datos_10.57715.UNR.1FA2MB (información técnica y metodológica) Tipos de datos Datos tabulares en hojas de cálculo en formato abierto OpenDocument Spreadsheet, que contienen la complilación de cualidades declaradas por los estudiantes, y variables categóricas ( año escolar, docente, género, curso y asignatura). Metodología Relevantamiento anual el primer día de clase de la asignatura, mediante consignas estandarizadas. Las respuestas se registran y sistematizan en planillas ODS por cohorte/año. Las categorías de análisis (p. ej., claridad, empatía, compromiso, motivación, innovación didáctica) se consolidan longitudinalmente y se emplean para recuentos y comparativas. Organización de los datos Un archivo por año (2002–2025) con estructura homogénea de columnas. Las variables mínimas incluyen: docente memorable (1 y 2), asignatura, año escolar en que fue estudiante, género, y tres cualidades por docente. Valor de los datos La serie continua de más de dos décadas permite estudiar tendencias y permanencias en las cualidades docentes valoradas por ingresantes. El diseño repetido, la estandarización de consignas y la homogeneidad de estructura entre archivos favorecen la comparabilidad y la reproducibilidad de análisis descriptivos e inferenciales.
DOI: 10.7910/dvn/nddwhj
title: Replication Data for: What do cross-country surveys tell us about social capital?

description: Code and data to reproduce all results and graphs reported in Tannenbaum et al. (2022). This folder contains data files (.dta files) and a Stata do-file (code.do) that stitches together the different data files and executes all analyses and produces all figures reported in the paper.&lt;br&gt;&lt;br&gt;

The do-file uses a number of user-written packages, which are listed below. Most of these can be installed using the ssc install command in Stata. Also, users will need to change the current directory path (at the start of the do-file) before executing the code.&lt;br&gt;&lt;br&gt;

List of user written packages (descriptions): &lt;br&gt;&lt;br&gt;

revrs (reverse-codes variable)&lt;br&gt;
ereplace (extends the egen command to permit replacing)&lt;br&gt;
grstyle (changes the settings for the overall look of graphs)&lt;br&gt;
spmap (used for graphing spatial data)&lt;br&gt;
qqvalue (used for obtaining Benjamini-Hochberg corrected p-values)&lt;br&gt;
parmby (creates a dataset by calling an estimation command for each by-group)&lt;br&gt;
domin (used to perform dominance analyses)&lt;br&gt;
coefplot (used for creating coefficient plots)&lt;br&gt;
grc1leg (combine graphs with a single common legend)&lt;br&gt;
xframeappend (append data frames to the end of the current data frame)
DOI: 10.15468/dl.5c8g7t
title: Occurrence Download

description: A dataset containing 46 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "Country is Indonesia",
 "Geometry POLYGON((94.58492 6.32041,94.5329 4.61154,94.84503 1.96301,98.95479 -3.80827,104.20904 -7.07047,107.33038 -5.00123,107.12229 -2.40577,105.9778 -0.58569,102.18017 2.015,98.53861 5.49248,94.58492 6.32041))",
 "HasGeospatialIssue is false",
 "TaxonKey is Amorphophallus titanum"
 ]
}

 The dataset includes 46 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0047089-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.v48k6x
title: Occurrence Download

description: A dataset containing 17035 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((0.83577 44.09908,0.8317 44.11587,0.82516 44.12105,0.81788 44.12216,0.80788 44.12191,0.79764 44.11426,0.81245 44.08403,0.82318 44.06737,0.82607 44.04693,0.84826 44.03372,0.87342 44.02072,0.91382 44.00508,0.96126 43.97723,1.00676 43.9431,1.05442 43.91619,1.15056 43.87053,1.20226 43.83917,1.28394 43.79858,1.32329 43.78582,1.34605 43.7627,1.35376 43.75096,1.38731 43.75167,1.4583 43.74036,1.4952 43.72642,1.52656 43.70262,1.56494 43.6806,1.59534 43.66931,1.6193 43.65738,1.64512 43.63909,1.6641 43.63143,1.65806 43.62278,1.66562 43.61338,1.68974 43.61084,1.70002 43.6234,1.69154 43.63809,1.65995 43.65548,1.63822 43.67186,1.60846 43.68624,1.58707 43.69944,1.56784 43.70345,1.54108 43.71929,1.50304 43.7412,1.47694 43.7527,1.41944 43.76775,1.38539 43.77424,1.37111 43.7756,1.35591 43.77657,1.34614 43.79334,1.32071 43.80397,1.30376 43.81214,1.29261 43.81375,1.27678 43.82909,1.21686 43.85421,1.13625 43.89862,1.09594 43.92593,1.05259 43.94714,0.97832 43.99082,0.92377 44.02116,0.88964 44.03854,0.86008 44.05554,0.84698 44.05861,0.84267 44.08857,0.83577 44.09908))",
 "PublishingOrg is 1928bdf0-f5d2-11dc-8c12-b8a03c50a862",
 "Year 2015-2025"
 ]
}

 The dataset includes 17035 records from 97 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0047088-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fmnduz
title: Occurrence Download

description: A dataset containing 45 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Myrceugenia brevipedicellata"
 ]
}

 The dataset includes 45 records from 27 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0047091-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.28233854
title: 指南针力场

description: COMPASS 力场文件
DOI: 10.6084/m9.figshare.28233854.v5
title: 指南针力场

description: COMPASS 力场文件
DOI: 10.6084/m9.figshare.28233854.v4
title: COMPASS Force field

description: COMPASS Force field file
DOI: 10.7910/dvn/o1i2xh
title: Replication data for: Deleting a Signal: Evidence from Pre-Employment Credit Checks

description: Bartik, Alexander W., and Nelson, Scott T., (2025) “Deleting a Signal: Evidence from Pre-employment Credit Checks.” Review of Economics and Statistics 107:1, 152–171.
description: Volume XX, Issue X
DOI: 10.15468/dl.9yk825
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((105.476 -1.448819, 105.405714 -1.454385, 105.337159 -1.470945, 105.272019 -1.498093, 105.211899 -1.535159, 105.158279 -1.581232, 105.112478 -1.635178, 105.075624 -1.695669, 105.048626 -1.761217, 105.032147 -1.830207, 105.026597 -1.900941, 105.032111 -1.971678, 105.048557 -2.040677, 105.07553 -2.106237, 105.112367 -2.166744, 105.158162 -2.220708, 105.211788 -2.266799, 105.271925 -2.303881, 105.33709 -2.331041, 105.405678 -2.34761, 105.476 -2.353178, 105.546322 -2.34761, 105.61491 -2.331041, 105.680075 -2.303881, 105.740212 -2.266799, 105.793838 -2.220708, 105.839633 -2.166744, 105.87647 -2.106237, 105.903443 -2.040677, 105.919889 -1.971678, 105.925403 -1.900941, 105.919853 -1.830207, 105.903374 -1.761217, 105.876376 -1.695669, 105.839522 -1.635178, 105.793721 -1.581232, 105.740101 -1.535159, 105.679981 -1.498093, 105.614841 -1.470945, 105.546286 -1.454385, 105.476 -1.448819))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0047090-251120083545085/datasets/export for details.
DOI: 10.15468/dl.cs82ev
title: Occurrence Download

description: A dataset containing 14741 species occurrences available in GBIF matching the query:
{
 "and" : [
 "CoordinateUncertaintyInMeters 0.0-1000.0",
 "Geometry POLYGON((-6.25617 41.0851,27.48128 41.0851,27.48128 72.26782,-6.25617 72.26782,-6.25617 41.0851))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Arabis alpina"
 ]
}

 The dataset includes 14741 records from 147 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0047092-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zgsnvx
title: Occurrence Download

description: A dataset containing 752417 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Betula pendula)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Geometry POLYGON ((-20 20, 45 20, 45 75, -20 75, -20 20))"
 ]
}

 The dataset includes 752417 records from 2592 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0047063-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bdw5gk
title: Occurrence Download

description: A dataset containing 15832 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "GadmGid is CHN.31_1",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Aves",
 "Year is 2020"
 ]
}

 The dataset includes 15832 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008423-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ppqyy9
title: Occurrence Download

description: A dataset containing 64 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-69.983 6.92785,-72.0324 7.07878,-72.4534 5.87137,-72.40625 5.51374,-72.82495 5.31653,-73.04916 4.98171,-73.1842 4.35418,-74.50281 3.82197,-75.13034 2.694,-74.9953 2.41598,-74.68224 2.41285,-74.52542 1.81696,-74.03879 1.5815,-73.67775 1.64429,-73.59141 2.36638,-73.17543 2.32713,-72.82223 2.58614,-72.46119 2.64108,-72.12369 2.86085,-71.10335 2.91579,-70.81294 2.77451,-70.52254 3.22189,-69.89464 3.50445,-69.26673 3.70067,-68.74308 3.61224,-68.44261 3.8498,-67.71267 4.03817,-67.75393 5.03691,-67.18554 6.33609,-69.45911 6.24012,-69.983 6.92785))",
 "OccurrenceStatus is Present",
 "TaxonKey is Gouania Jacq."
 ]
}

 The dataset includes 64 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008425-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13921232
title: Separating the relative roles of climate and forest disturbance in high and low flows in snow-dominated watersheds of Southern British Columbia

description: 1. Historical hydrological data in watershed 241, Camp, Greata, and Trepanier watersheds, including daily hydrometeorological records and aggregated hydrometeorological metrics. 

2. Relative contributions of climate metrics and forest disturbance to multiple hydrological signatures (i.e., high and low flows) in watershed 241, Camp, Greata, and Trepanier watersheds.
DOI: 10.5281/zenodo.13921233
title: Separating the relative roles of climate and forest disturbance in high and low flows in snow-dominated watersheds of Southern British Columbia

description: 1. Historical hydrological data in watershed 241, Camp, Greata, and Trepanier watersheds, including daily hydrometeorological records and aggregated hydrometeorological metrics. 

2. Relative contributions of climate metrics and forest disturbance to multiple hydrological signatures (i.e., high and low flows) in watershed 241, Camp, Greata, and Trepanier watersheds.
DOI: 10.15468/dl.8qxyju
title: Occurrence Download

description: A dataset listing the 2 species recorded in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Entyloma microsporum (Unger) J.Schröt."
 ]
}

 The dataset's 2 records were derived from 55 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008420-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xfq2xj
title: Occurrence Download

description: A dataset containing 28126 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Hemerocallis fulva (L.) L."
 ]
}

 The dataset includes 28126 records from 591 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008427-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13921244
title: Assessment of Middle Ear Effusion in Children Under 5 Years in Timergara

description: Otitis media with effusion is a chronic inflammatory disease that usually affects children aged 3 to 7 years. Otitis media with effusion is characterized by fluid deposition in the middle ear behind an intact tympanic membrane without the symptoms or signs acute infection. The aim of this study was to assess Otitis media with effusion in children less than 5 years of age. Cross sectional study was carried out in DHQ Timergara, Lower Dir, KPK Pakistan. This duration of study takes a time period of 4 months after topic approval. This study was done on 130 children less than 5 years of age with otitis media with effusion selected through convenient sampling techniques from DHQ hospital Timergara. Data was collected through self-design questionnaire consists of 31 questions to assess otitis media with effusion under 5 year of age. There were  a total of 130  participants that participated in this study and of age 1-3 was  53.08%, and 46.92%  from 3-5 years, 54.62% male, 45.38% female 53.08% participants were middle level of education, 40.00%, participant were level of metric, 6.92% participant were level of FA and F.Sc and this study finds out that the prevalence of otitis media with effusion is 13.63% in under five year of age.