cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.35078/ww3sre/83d5il
title: Bom Jardim II D.jpg

description: :unav
DOI: 10.35078/ivzaus/dbhjji
title: Bicas I. B.jpg

description: :unav
DOI: 10.35078/rptw1i/3tv8uj
title: Macaco A.jpg

description: :unav
DOI: 10.35078/rptw1i/dr8p9t
title: Cana Brava C.jpg

description: :unav
DOI: 10.35078/ww3sre/eiwvqd
title: José Balbino A.jpg

description: :unav
DOI: 10.35078/ivzaus/v8vw1l
title: Dourados B.jpg

description: :unav
DOI: 10.35078/ww3sre/tnm3bq
title: Coração A.jpg

description: :unav
DOI: 10.35078/rptw1i/sml7ua
title: Caiçarinha I B.jpg

description: :unav
DOI: 10.35078/ivzaus/3frpsy
title: Socó Velho E.jpg

description: :unav
DOI: 10.35078/ww3sre/3yi95c
title: Florêncio de Paula B.jpg

description: :unav
DOI: 10.35078/ivzaus/aveevn
title: Socó Verde D.jpg

description: :unav
DOI: 10.35078/rptw1i/aynuay
title: Campo do Meio C.jpg

description: :unav
DOI: 10.35078/ww3sre/ctczsq
title: Córrego Cascavel G.jpg

description: :unav
DOI: 10.35078/ivzaus/pdnb5k
title: Saputá C.jpg

description: :unav
DOI: 10.35078/rptw1i/ni7qyh
title: Açougue D.jpg

description: :unav
DOI: 10.35078/ww3sre/cqytza
title: Furna Grande I.jpg

description: :unav
DOI: 10.35078/ivzaus/luhert
title: Ribeirão das Piranhas B.jpg

description: :unav
DOI: 10.35078/rptw1i/iqnqel
title: Laranjão E.jpg

description: :unav
DOI: 10.35078/ivzaus/gvxryc
title: Furado das Pedras E.jpg

description: :unav
DOI: 10.35078/ww3sre/ctj2ff
title: Cabeceira da Vertente E.jpg

description: :unav
DOI: 10.35078/rptw1i/m1htck
title: Capoeirão C.jpg

description: :unav
DOI: 10.35078/ww3sre/o4lbcz
title: Coração C.jpg

description: :unav
DOI: 10.35078/ivzaus/jvruca
title: Paus Preto da Cruz E.jpg

description: :unav
DOI: 10.35078/rptw1i/u5yxlk
title: Cana Brava D.jpg

description: :unav
DOI: 10.35078/ww3sre/yw88uy
title: Gabriel F. da Silva C.jpg

description: :unav
DOI: 10.35078/ivzaus/i0w3rp
title: Largas C.jpg

description: :unav
DOI: 10.35078/rptw1i/81xl1s
title: Buriti Seco C.jpg

description: :unav
DOI: 10.35078/ww3sre/jvumzj
title: Córrego Lageadinho F.jpg

description: :unav
DOI: 10.35078/ivzaus/2cinpc
title: Gameleira Faz. B.jpg

description: :unav
DOI: 10.35078/rptw1i/qudatl
title: Jaci Mendes A.jpg

description: :unav
DOI: 10.35078/ww3sre/sqyo9s
title: Córrego do Cavalo C.jpg

description: :unav
DOI: 10.35078/ivzaus/0clwav
title: Passagem II. B.jpg

description: :unav
DOI: 10.35078/rptw1i/iueqel
title: Capim Pubo D.jpg

description: :unav
DOI: 10.35078/ivzaus/hormko
title: Dourados D.jpg

description: :unav
DOI: 10.35078/ww3sre/qkqgm2
title: Furna do Macaco N.jpg

description: :unav
DOI: 10.35078/ivzaus/n1frj0
title: Água Branca I.B.jpg

description: :unav
DOI: 10.35078/rptw1i/dmjyu5
title: Barreiro do Buqueirão F.jpg

description: :unav
DOI: 10.35078/ww3sre/rqjtex
title: Barra Lambari D.jpg

description: :unav
DOI: 10.35078/rptw1i/waghsz
title: Bonito A.jpg

description: :unav
DOI: 10.35078/ivzaus/dhjct9
title: Teotonio B.jpg

description: :unav
DOI: 10.35078/ww3sre/eugqqy
title: Urzedos J.jpg

description: :unav
DOI: 10.35078/rptw1i/otksne
title: Claraíbas B.jpg

description: :unav
DOI: 10.35078/ivzaus/m9jmx7
title: Vereda do Coqueiro F.jpg

description: :unav
DOI: 10.35078/ww3sre/jka3gd
title: Córrego Cachoeirão A.jpg

description: :unav
DOI: 10.35078/rptw1i/ad7yqb
title: Lagoinha I A.jpg

description: :unav
DOI: 10.35078/ivzaus/mqu0wa
title: Landinho II. D.jpg

description: :unav
DOI: 10.35078/rptw1i/6flu5e
title: Empoeira Preta - Espinho A.jpg

description: :unav
DOI: 10.35078/ww3sre/uzv1fx
title: Brejão B.jpg

description: :unav
DOI: 10.35078/ivzaus/vnoehg
title: Cabeceira do Landinho D.jpg

description: :unav
DOI: 10.35078/rptw1i/72tfuw
title: João de Barro C.jpg

description: :unav
DOI: 10.35078/ww3sre/6ppl27
title: Barra do Córrego da Serra H.jpg

description: :unav
DOI: 10.35078/rptw1i/gaepyj
title: Gameleira I F.jpg

description: :unav
DOI: 10.35078/ivzaus/bho4j0
title: Cabeceira do Landinho E.jpg

description: :unav
DOI: 10.35078/ww3sre/pa9h1x
title: Ribeirão dos Bois D.jpg

description: :unav
DOI: 10.35078/rptw1i/o8fiif
title: José Moreira B.jpg

description: :unav
DOI: 10.35078/ivzaus/ruepfs
title: Paus Preto da Cruz B.jpg

description: :unav
DOI: 10.35078/rptw1i/ni1nc9
title: Estiva F.jpg

description: :unav
DOI: 10.35078/ww3sre/dpanmk
title: Mamona J.jpg

description: :unav
DOI: 10.35078/ivzaus/4utury
title: Furado das Pedras C.jpg

description: :unav
DOI: 10.35078/rptw1i/tglq04
title: Barra A.jpg

description: :unav
DOI: 10.35078/ww3sre/kfqtr3
title: Barra Lambari G.jpg

description: :unav
DOI: 10.35078/ivzaus/36veai
title: Roçado Velho B.jpg

description: :unav
DOI: 10.35078/rptw1i/k5esm9
title: Empoeira I F.jpg

description: :unav
DOI: 10.35078/ww3sre/0oss2k
title: Córrego do Brejão A.jpg

description: :unav
DOI: 10.35078/ivzaus/zavj0y
title: Serra Ginete A.jpg

description: :unav
DOI: 10.35078/rptw1i/mhpbgt
title: Barra da Vereda A.jpg

description: :unav
DOI: 10.35078/ww3sre/rqvu92
title: José B. Carneiro A.jpg

description: :unav
DOI: 10.6084/m9.figshare.14208509
title: S2 Table. Statistica dataset for the manuscript "Inventory of water masses and carbonate system from Brazilian’s northeast coast: monitoring ocean acidification". ID Number = is the identification number of the sample, it is related to the sampling station. Group = is the number of samples (n) per water mass. psu = is the practical salinity unit; S% = is the absolute salinity; (A) = analyzed values and (C) = calculated values.

description: Raw data for the manuscript "Inventory of water masses and carbonate system from Brazilian’s northeast coast: monitoring ocean acidification ".
DOI: 10.6084/m9.figshare.14208509.v4
title: S2 Table. Statistica dataset for the manuscript "Inventory of water masses and carbonate system from Brazilian’s northeast coast: monitoring ocean acidification". ID Number = is the identification number of the sample, it is related to the sampling station. Group = is the number of samples (n) per water mass. psu = is the practical salinity unit; S% = is the absolute salinity; (A) = analyzed values and (C) = calculated values.

description: Raw data for the manuscript "Inventory of water masses and carbonate system from Brazilian’s northeast coast: monitoring ocean acidification ".
DOI: 10.6084/m9.figshare.14208509.v3
title: S2 Table. Raw data for the manuscript "Inventory of water masses and carbonate system from Brazilian’s northeast coast: monitoring ocean acidification ".

description: Raw date for the manuscript "Inventory of water masses and carbonate system from Brazilian’s northeast coast: monitoring ocean acidification ".
DOI: 10.35078/ivzaus/nj3b8t
title: Buqueirão do Coronel F.jpg

description: :unav
DOI: 10.35078/rptw1i/x2ss5v
title: Canoas C.jpg

description: :unav
DOI: 10.35078/ww3sre/nfaeoq
title: Bebedourinho H.jpg

description: :unav
DOI: 10.35078/ivzaus/uctgs6
title: Socó Verde F.jpg

description: :unav
DOI: 10.35078/rptw1i/xkp0s1
title: João Batista C.jpg

description: :unav
DOI: 10.15468/dl.5jsrc9
title: Occurrence Download

description: A dataset containing 1058 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lemur catta Linnaeus, 1758"
 ]
}

 The dataset includes 1058 records from 82 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0078408-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.z649dn
title: Occurrence Download

description: A dataset containing 1067 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "SpeciesKey is Octolasion cyaneum (Savigny, 1826)",
 "Year is greater than or equal to 2004",
 "Year is less than or equal to 2023"
 ]
}

 The dataset includes 1067 records from 60 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0078407-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13362798
title: Forest plots of pairwise comparisons from original studies for the primary outcomes limited to studies with low ROB only
title: Non-invasive respiratory support in preterm infants as primary mode: a network meta-analysis (CD014895)
DOI: 10.5281/zenodo.13362799
title: Forest plots of pairwise comparisons from original studies for the primary outcomes limited to studies with low ROB only
title: Non-invasive respiratory support in preterm infants as primary mode: a network meta-analysis (CD014895)
DOI: 10.15468/dl.wdy9ax
title: Occurrence Download

description: A dataset containing 4004 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "SpeciesKey is Theromyzon tessulatum (O.F.Müller, 1773)",
 "Year is greater than or equal to 2004",
 "Year is less than or equal to 2023"
 ]
}

 The dataset includes 4004 records from 86 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0078410-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8dhrt3
title: Occurrence Download

description: A dataset containing 32497620 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is South America",
 "Country is Colombia"
 ]
}

 The dataset includes 32497620 records from 3849 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0078360-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qrfbws
title: Occurrence Download

description: A dataset containing 1703 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cardamine bonariensis Pers."
 ]
}

 The dataset includes 1703 records from 195 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021236-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15208205
title: Micro-meso-macroporous channels finely tailored for highly efficient moisture energy harvesting
DOI: 10.5281/zenodo.15208206
title: Micro-meso-macroporous channels finely tailored for highly efficient moisture energy harvesting
DOI: 10.5281/zenodo.4561842
title: SautiDB: Nigerian Accent Dataset Collection

description: The SautiDB dataset collection project is an ongoing effort to collect datasets of various Nigerian accents. The dataset was collected in an uncontrolled manner, users who visit our webapp can record their voice and contribute to the dataset. The webapp uses the audio webapi to collect voice samples. We hope this dataset will be useful to people interested in developing voice technology in Nigeria. We will continuously collect more datasets and publish updated versions as we have them. This work grew out of our project Improving Online Experience using Accent Transfer.<br> The filename is of the form nativeLanguage_fluentLanguage_speakerID_gender_sentenceID.wav, where <strong>nativeLanguage:</strong> language spoken by the speaker's tribe. Native (mother) language of the speaker <strong>fluentLanguage:</strong> language that the speaker feels best describes their accents <strong>speakerID:</strong> ID, assigned to the speaker. It is possible for a speaker to have multiple IDs assigned since we are not authenticating users, we simply cached their browser sessions. <strong>gender:</strong> gender of the speaker. We did not explicitly collect this information from users, we hand-labeled it. <strong>sentenceID:</strong> the sentence ID for the sentences read. We used the CMU Arctic sentences. <br> ===========================<br> Before Postprocessing<br> ===========================<br> Number of Samples: 1615<br> Size Webm: 59MB<br> Size Wav: 847MB<br> Sampling Rate: 48000Hz<br> Total Time: 2hrs 30min 21sec <br> ============================<br> After Postprocessing<br> ============================<br> Number of Samples: 919<br> Size Wav: 336MB<br> Sampling Rate: 48000Hz<br> Total Time: 0hrs 59min 08sec<br> <br> The associated Github repository used for post-processing can also be found linked. We are grateful for funding from AI4D-IndabaX with IDRC Grant Number: 109187-002.<br> <br> This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
DOI: 10.5281/zenodo.6409447
title: SautiDB: Nigerian Accent Dataset Collection

description: The SautiDB dataset collection project is an ongoing effort to collect datasets of various Nigerian accents. The dataset was collected in an uncontrolled manner, users who visit our webapp can record their voice and contribute to the dataset. The webapp uses the audio webapi to collect voice samples. We hope this dataset will be useful to people interested in developing voice technology in Nigeria. We will continuously collect more datasets and publish updated versions as we have them. This work grew out of our project Improving Online Experience using Accent Transfer.<br> The filename is of the form nativeLanguage_fluentLanguage_speakerID_gender_sentenceID.wav, where <strong>nativeLanguage:</strong> language spoken by the speaker's tribe. Native (mother) language of the speaker <strong>fluentLanguage:</strong> language that the speaker feels best describes their accents <strong>speakerID:</strong> ID, assigned to the speaker. It is possible for a speaker to have multiple IDs assigned since we are not authenticating users, we simply cached their browser sessions. <strong>gender:</strong> gender of the speaker. We did not explicitly collect this information from users, we hand-labeled it. <strong>sentenceID:</strong> the sentence ID for the sentences read. We used the CMU Arctic sentences. <br> ===========================<br> Before Postprocessing<br> ===========================<br> Number of Samples: 1615<br> Size Webm: 59MB<br> Size Wav: 847MB<br> Sampling Rate: 48000Hz<br> Total Time: 2hrs 30min 21sec <br> ============================<br> After Postprocessing<br> ============================<br> Number of Samples: 919<br> Size Wav: 336MB<br> Sampling Rate: 48000Hz<br> Total Time: 0hrs 59min 08sec<br> ============================<br> Version 1.1<br> ============================<br> This version has two updates: 1. In version 1.0, the naming convention for each language was to space each language with an underscore and uppercased, e.g., "Efik Ibibio" -&gt; "EFIK_IBIBIO". We have changed "EFIK_IBIBIO" -&gt; "EFIKIBIBIO". i.e. the file name, which was previously 'EFIKIBIBIO_EFIKIBIBIO_0014_M_A0138.wav', has now been changed to 'EFIKIBIBIO_EFIKIBIBIO_0014_M_A0138.wav'. This change applies only to languages that contain spaces. The rest of the filenames, therefore, remain unchanged, i.e. 'EDO_YORUBA_0053_M_B0389.wav' is still 'EDO_YORUBA_0053_M_B0389.wav'. 2. We include an audio_metadata.csv file containing 'filename', 'nativeLanguage', 'fluentLanguage', 'speakerID', 'gender', 'sentenceID' and 'sentence', 'duration'. We hope this will make it easier for users to use our dataset for their work. The duration was calculated using the function 'librosa.get_duration()'. <br> <br> The associated Github repository used for post-processing can also be found linked. We are grateful for funding from AI4D-IndabaX with IDRC Grant Number: 109187-002.<br> <br> This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
DOI: 10.5281/zenodo.7565541
title: tuhh-softsec/A-Manually-Curated-Dataset-of-Vulnerability-Introducing-Commits-in-Java: v1.0.0

description: No description provided.
DOI: 10.5281/zenodo.7574340
title: tuhh-softsec/A-Manually-Curated-Dataset-of-Vulnerability-Introducing-Commits-in-Java: v1.0.0

description: No description provided.
DOI: 10.34740/kaggle/dsv/5009620
title: Nifty-50 & Nifty Future 50 Dataset
DOI: 10.35078/bjiapw
title: Replication Data for: Ficha epidemiológica de localidade: Distrito: Montes Claros | Município: Espinosa

description: Levantamento Triatomínico com operações de campo ocorridas em Minas Gerais pela Superintendência de Campanhas de Saúde Pública (SUCAM) e FUNASA (Fundação Nacional de Saúde), no período de 1979 a 1999, objetivando a busca da presença de vetores da doença de Chagas ou de vestígios dessa presença. A partir dela são orientadas as operações com inseticida (pt) Triatomine survey with field operations carried out in Minas Gerais by the Public Health Campaigns Superintendence (SUCAM) and FUNASA (National Health Foundation), from 1979 to 1999, aiming to search for the presence of Chagas disease vectors or traces of that presence. From it, operations with insecticide are guided (en) Encuesta de triatominos con operaciones de campo realizada en Minas Gerais por la Superintendencia de Campañas de Salud Pública (SUCAM) y FUNASA (Fundación Nacional de Salud), de 1979 a 1999, con el objetivo de buscar la presencia de vectores de la enfermedad de Chagas o rastros de esa presencia. Desde ella se orientan las operaciones con insecticida (es)
DOI: 10.34740/kaggle/dsv/5009661
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.35078/ukif7z
title: Replication Data for: Ficha epidemiológica de localidade: Distrito: Montes Claros | Município: Varzelândia

description: Levantamento Triatomínico com operações de campo ocorridas em Minas Gerais pela Superintendência de Campanhas de Saúde Pública (SUCAM) e FUNASA (Fundação Nacional de Saúde), no período de 1979 a 1999, objetivando a busca da presença de vetores da doença de Chagas ou de vestígios dessa presença. A partir dela são orientadas as operações com inseticida (pt) Triatomine survey with field operations carried out in Minas Gerais by the Public Health Campaigns Superintendence (SUCAM) and FUNASA (National Health Foundation), from 1979 to 1999, aiming to search for the presence of Chagas disease vectors or traces of that presence. From it, operations with insecticide are guided (en) Encuesta de triatominos con operaciones de campo realizada en Minas Gerais por la Superintendencia de Campañas de Salud Pública (SUCAM) y FUNASA (Fundación Nacional de Salud), de 1979 a 1999, con el objetivo de buscar la presencia de vectores de la enfermedad de Chagas o rastros de esa presencia. Desde ella se orientan las operaciones con insecticida (es)
DOI: 10.35078/wasuba
title: Replication Data for: Ficha epidemiológica de localidade: Distrito: Montes Claros | Município: Botumirim

description: Levantamento Triatomínico com operações de campo ocorridas em Minas Gerais pela Superintendência de Campanhas de Saúde Pública (SUCAM) e FUNASA (Fundação Nacional de Saúde), no período de 1979 a 1999, objetivando a busca da presença de vetores da doença de Chagas ou de vestígios dessa presença. A partir dela são orientadas as operações com inseticida (pt) Triatomine survey with field operations carried out in Minas Gerais by the Public Health Campaigns Superintendence (SUCAM) and FUNASA (National Health Foundation), from 1979 to 1999, aiming to search for the presence of Chagas disease vectors or traces of that presence. From it, operations with insecticide are guided (en) Encuesta de triatominos con operaciones de campo realizada en Minas Gerais por la Superintendencia de Campañas de Salud Pública (SUCAM) y FUNASA (Fundación Nacional de Salud), de 1979 a 1999, con el objetivo de buscar la presencia de vectores de la enfermedad de Chagas o rastros de esa presencia. Desde ella se orientan las operaciones con insecticida (es)
DOI: 10.5281/zenodo.7646428
title: Multi-model ensemble bias-corrected precipitation dataset for historical and future climate (1961–2099) in China

description: 本文基于耦合模式比较项目第六阶段(CMIP6)的27个全球气候模式(GCM),采用随机森林(RF)模型和EQM方法整合27个大气监测模型的降水模拟数据,进一步修正中国综合月降水数据。修正后的降水资料在月降水量和极端降水量方面均明显优于原GCM降水资料。数据以 GeoTIFF 格式,其中嵌入了具有 1° 空间分辨率的地理配准信息。LST在GeoTIFF中的单位是mm。压缩文件被命名为历史文件.zip、SSP126.zip、SSP245.zip 和 SSP585.zip。压缩文件中的每个文件都命名为“yyyymm.tif”,其中“yyyy”和“mm”分别表示年份和月份。例如,文件“196101.tif”存储了 1961 年 1 月中国每月降水量。
DOI: 10.5281/zenodo.7646427
title: Multi-model ensemble bias-corrected precipitation dataset for historical and future climate (1961–2099) in China

description: 本文基于耦合模式比较项目第六阶段(CMIP6)的27个全球气候模式(GCM),采用随机森林(RF)模型和EQM方法整合27个大气监测模型的降水模拟数据,进一步修正中国综合月降水数据。修正后的降水资料在月降水量和极端降水量方面均明显优于原GCM降水资料。数据以 GeoTIFF 格式,其中嵌入了具有 1° 空间分辨率的地理配准信息。LST在GeoTIFF中的单位是mm。压缩文件被命名为历史文件.zip、SSP126.zip、SSP245.zip 和 SSP585.zip。压缩文件中的每个文件都命名为“yyyymm.tif”,其中“yyyy”和“mm”分别表示年份和月份。例如,文件“196101.tif”存储了 1961 年 1 月中国每月降水量。
DOI: 10.5281/zenodo.7646440
title: trajectory for glycine

description: simulation of glycine using it is standard formula with opls-aa forcefield.
DOI: 10.5281/zenodo.7646439
title: trajectory for glycine

description: simulation of glycine using it is standard formula with opls-aa forcefield.
DOI: 10.4121/22096307
title: Dataset accompanying the publication: Introducing Power-to-H3: combining renewable electricity with heat, water and hydrogen production and storage in a neighbourhood

description: This dataset contains raw model results from 2 different scenario's as part of a publication on the the Power-to-H3 concept for system integration in a neigbhourhood energy- and water system. It is being made public to act as supplementary data for publication(s) and the PhD thesis of Els van der Roest. Also, it might be used by other researhers. <br> The dataset was created during model runs in the period between January 2019 - April 2019. <br> Abstract of the paper: In the transition from fossil to renewable energy, the energy system should become clean, while remaining reliable and affordable. Because of the intermittent nature of both renewable energy production and energy demand, an integrated system approach is required that includes energy conversion and storage. We propose a concept for a neighbourhood where locally produced renewable energy is partly converted and stored in the form of heat and hydrogen, accompanied by rainwater collection, storage, purification and use (Power-to-H3). A model is developed to create an energy balance and perform a techno-economic analysis, including an analysis of the avoided costs within the concept. The results show that a solar park of 8.7 MWp combined with rainwater collection and solar panels on roofs, can supply 900 houses over the year with heat (20 TJ) via an underground heat storage system as well as with almost half of their water demand (36,000 m3) and 540 hydrogen electric vehicles can be supplied with hydrogen (90 tonnes). The production costs for both hydrogen (8.7 €/kg) and heat (26 €/GJ) are below the current end user selling price in the Netherlands (10 €/kg and 34 €/GJ), making the system affordable. When taking avoided costs into account, the prices could decrease with 20–26%, while at the same time avoiding 3600 tonnes of CO2 a year. These results make clear that it is possible to provide a neighbourhood with all these different utilities, completely based on solar power and rainwater in a reliable, affordable and clean way.
DOI: 10.4121/21890640.v1
title: Data underlying the publication: “Spatial and seasonal variation in phytoplankton abundance and composition in Lake Victoria’s Mwanza Gulf, compared to northern parts of the lake”

description: The dataset contains the raw data of chlorophyll content, and of taxonomy, numbers, and sizes of phytoplankton samples collected in Mwanza Gulf of Lake Victoria (Africa) in 2011-2011. The R-script used for data analysis is also included.