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26 results for “social housing”

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zenodo48/100

Share and spatial concentration of social housing in Dutch urban areas

<p>This dataset contains the amount of social housing units of the Netherlands per urban area, as well as the intensity of their spatial autocorrelation and its proportion compared to the total housing stock, for the year 2023.&nbsp;<a href="https://www.cbs.nl/nl-nl/dossier/nederland-regionaal/geografische-data/kaart-van-100-meter-bij-100-meter-met-statistieken">Original data</a> comes from Statistics Netherlands (<em>Centraal Bureau voor de Statistiek</em>) released for 100 m x 100 m grid cells covering a large share of the Dutch territory. Grid cells with missing values were excluded from the analysis. The spatial autocorrelation of social housing was calculated with urban area-level and U-style computations of Global Moran's I based on the share of social housing units compared to the total housing stock of every grid cell.&nbsp;Limits and definition of urban areas are extracted from&nbsp;<a href="https://www.oecd.org/en/data/datasets/oecd-definition-of-cities-and-functional-urban-areas.html">the OECD</a>. Data show considerable variation in the levels of social housing and its spatial concentration among Dutch urban areas.</p>

opencc-by-4.0Oct 2024View details →
zenodo44/100

Social housing is good for everyone

<p><strong>Coordinador del Seminario:</strong> Carlos A. Navarrete Ulloa.<br> <strong>Expositor</strong>: Ramona Esmeralda Vel&aacute;zquez Garc&iacute;a<br> <strong>Comit&eacute; Ejecutivo PRONACE-Vivien</strong>da</p> <ul> <li>Fernando C&oacute;rdova Canela, Centro Universitario de Arte, Arquitectura y Dise&ntilde;o, Universidad de Guadalajara (UdeG).</li> <li>Francisco Javier Porras S&aacute;nchez, Instituto de Investigaciones Dr. Jos&eacute; Mar&iacute;a Luis Mora.</li> <li>Gabriel Casta&ntilde;eda Nolasco, Universidad Aut&oacute;noma de Chiapas (UNACH).</li> <li>Carlos A. Navarrete Ulloa, Centro Universitario de Tonal&aacute;, (UdeG).</li> </ul> <p>Exposici&oacute;n realizada en el marco del PRONACE Vivienda en el cual se comenta la lectura:</p> <p>Khalid, M. (2015). Social housing is good por everyone. A benefits-Cost analysis. In J. Silver &amp; J. Brandon (Eds.), Poor Housing: A Silent Crisis. Fernwood Publishing&nbsp;</p>

opencc-by-4.0Feb 2021View details →
zenodo44/100

ES12 - Social Housing - Candeleda (Spain)

<p>Data files for building: ES12 - Social Housing - Candeleda (Spain)</p><p>Languages: Spanish, English</p><p>These files are part of the public benchmark repository created as a part of the crossCert EU project.&nbsp;</p><p>This repository contains curated building data, certificate results and, where available, measured performance results. The repository is publicly available so that it can be used as a testbench for new Energy Performance Certificate (EPC) procedures.</p><p>The files are organised in the following folders&nbsp; (note that not all files are always provided):</p><ol><li>Main data&nbsp; and Results, with:<ol><li>Neutral data inventory.</li><li>Neutral results report.</li><li>Original EPC certificate.</li></ol></li><li>Energy Consumption Data, with:<ol><li>Files, where available, with energy consumption data for the building, which can be used for validation of models and EPC results.</li></ol></li><li>Drawings<ol><li>Building drawings which can be used as an aid for generating the EPC, or for creating dynamic energy consumption&nbsp; models.</li></ol></li><li>Other Data<ol><li>Any other data that can be useful for the purposes of creating or validating an EPC or an energy consumption dynamic model for the building.</li></ol></li><li>Dynamic Model<ol><li>Data to run a dynamic model of the building, if available.</li></ol></li></ol><p>The files have been redacted to exclude confidential information.&nbsp;</p>

opencc-by-4.0Oct 2023View details →
zenodo44/100

ES11 - Social housing - Simancas (Spain)

<p>Data files for building: ES11 - Social housing - Simancas (Spain)</p><p>Languages: Spanish, English</p><p>These files are part of the public benchmark repository created as a part of the crossCert EU project.&nbsp;</p><p>This repository contains curated building data, certificate results and, where available, measured performance results. The repository is publicly available so that it can be used as a testbench for new Energy Performance Certificate (EPC) procedures.</p><p>The files are organised in the following folders&nbsp; (note that not all files are always provided):</p><ol><li>Main data&nbsp; and Results, with:<ol><li>Neutral data inventory.</li><li>Neutral results report.</li><li>Original EPC certificate.</li></ol></li><li>Energy Consumption Data, with:<ol><li>Files, where available, with energy consumption data for the building, which can be used for validation of models and EPC results.</li></ol></li><li>Drawings<ol><li>Building drawings which can be used as an aid for generating the EPC, or for creating dynamic energy consumption&nbsp; models.</li></ol></li><li>Other Data<ol><li>Any other data that can be useful for the purposes of creating or validating an EPC or an energy consumption dynamic model for the building.</li></ol></li><li>Dynamic Model<ol><li>Data to run a dynamic model of the building, if available.</li></ol></li></ol><p>The files have been redacted to exclude confidential information.&nbsp;</p>

opencc-by-4.0Oct 2023View details →
zenodo40/100

Supplementary material for "Playback experiments highlight the importance of nearest-neighbor distance and social information for nest site selection in the House Martin (Delichon urbicum)"

<p><strong>Abstract</strong></p> <p>Understanding nest site selection is crucial for species conservation. Bird conservation often involves installing nesting aids to increase nest site availability and induce colonization of unoccupied sites. However, prospecting individuals must find nesting aids, which may be facilitated by social information. Here, we investigated the effectiveness of artificial nests and playback in the declining, migratory House Martin <em>Delichon urbicum</em>. We selected unoccupied sites with artificial nests along a distance gradient to occupied sites and broadcasted conspecific vocalizations during prospection times of House Martins in both the post- and the following pre-breeding periods. Visitation and colonization rates increased considerably in proximity to occupied sites. Playback during the post-breeding and pre-breeding periods enhanced visitation rates, while pre-breeding-only and post-breeding-only playback had smaller positive effects. Colonization rate increased exclusively with pre-breeding-only playback. Colonized playback and non-playback sites had similar breeding success, indicating that playback did not create ecological traps by attracting House Martins to suboptimal sites. Hence, broadcasting conspecific vocalizations informs prospecting birds of nest site availability, thereby increasing visitation, and to some degree, colonization of unoccupied House Martin sites. To boost colonization, we recommend installing artificial House Martin nests within approximately 500 meters of occupied sites and using playback of conspecific vocalizations.</p>

opencc-by-4.0Jul 2024View details →
zenodo40/100

BRAIN Journal-Participative Teaching with Mobile Devices and Social Networks for K-12 Children-Figure 1. An experiment of building a prehistoric house, carried out by Professor Dragoş Gheorghiu in Vădastra

<p>The learning experiment in Vădastra village began by geo-referencing some points of interest in the archaeological area (Gheorghiu &amp; Stefan, 2013a; 2013b), which were identified from the archaeological published materials and from information provided by the villagers, as well as resulting from fieldwork conducted for over a decade (i.e. archaeological experimentation) in this village (Gheorghiu, 2001; 2008). The geographic data (POIs) was collected on the archaeological site by the K-12 children under the coordination of a project team member from the National University of Arts Bucharest (NUA).&nbsp;</p>

opencc-by-4.0Feb 2018View details →
zenodo40/100

BRAIN Journal-Participative Teaching with Mobile Devices and Social Networks for K-12 Children-Figure 3. Augmented Reality with archaeological stratigraphy (a prehistoric house and a Roman villa reconstructed in 3D)

<p>The third stage was represented by the 3D virtual reconstruction process of the historical contexts, in our case a prehistoric village and a complete Roman villa rustica, with the help of students from the Design Department, NUA, coordinated by Professor Arch. Andreea Hasnaş. The AR application was created and tested on two commercial AR platforms, Layar and Junaio, and recently moved on the Aurasma platform (https://www.aurasma.com/). The POIs were augmented with the 3D virtual reconstructions, and also with 2D images and videos representing 3D virtual tours and technological processes (Figures 3, 4, 5). The AR application was connected to teachers&rsquo; emails and to Twitter, Facebook and Google+ project&rsquo;s pages.&nbsp;</p>

opencc-by-4.0Jun 2016View details →
dryad40/100

Vocal communication is seasonal in social groups of wild, free-living house mice

Open the record for dataset details and reuse information.

publicMay 2025View details →
dryad36/100

No, you go first: phenotype and social context affect house sparrow neophobia

<p>Novel object trials are commonly used to assess aversion to novelty (neophobia), and previous work has shown neophobia can be influenced by the social environment, but whether the altered behaviour persists afterwards (social learning) is largely unknown in wild animals. We assessed house sparrow (<i>Passer domesticus</i>) novel object responses before, during, and after being paired with a conspecific of either similar or different behavioral phenotype. During paired trials, animals housed with a similar or more neophobic partner demonstrated an increased aversion to novel objects. This change did not persist a week after unpairing, but neophobia decreased after unpairing in birds previously housed with a less neophobic partner. We also compared novel object responses to non-object control trials to validate our experimental procedure. Our results provide evidence of social learning in a highly successful invasive species, and an interesting asymmetry in the effects of social environment on neophobia behavior depending on the animal's initial behavioral phenotype.</p>

opencc-zeroAug 2020View details →
zenodo36/100

Distances between Brazilian Social Housing and Urban Services

<p>This database presents the results of a survey conducted through research using the Google Maps Platform API for grocery stores, drugstores, bank branches, lottery agencies, public schools, health centers, and parks services in a sample of 2241 social housing developments built under Brazilian government programs. It was developed to evaluate the quality of urban insertion of social housing by the HabLabEEE project.</p> <p>Esta base de dados apresenta os resultados de um levantamento realizado por meio de pesquisa com API do Google Maps Platform por servi&ccedil;os de mercado, farm&aacute;cia, banco, lot&eacute;rica, escola p&uacute;blica, posto de sa&uacute;de e parque em uma amostra de 2241 conjuntos habitacionais constru&iacute;dos no &acirc;mbito de programas governamentais brasileiros. Foi desenvolvida para avaliar a qualidade da inser&ccedil;&atilde;o urbana das HIS brasileiras pelo projeto HabLabEEE.</p> <p>&nbsp;</p> <p>&nbsp;</p>

opencc-by-4.0Mar 2024View details →
ClinicalTrials.gov36/100

A Social Network AOD Intervention for Homeless Youth Transitioning to Housing

ClinicalTrials.gov study NCT04637815. IPD Sharing: Not stated. Countries: 1. Publications: 2.

restrictedIPD-UNDECIDEDFeb 2026View details →
dryad36/100

No, you go first: phenotype and social context affect house sparrow neophobia

Open the record for dataset details and reuse information.

publicFeb 2021View details →
dryad32/100

Data from: How random is social behaviour? Disentangling social complexity through the study of a wild house mouse population

Out of all the complex phenomena displayed in the behaviour of animal groups, many are thought to be emergent properties of rather simple decisions at the individual level. Some of these phenomena may also be explained by random processes only. Here we investigate to what extent the interaction dynamics of a population of wild house mice (Mus domesticus) in their natural environment can be explained by a simple stochastic model. We first introduce the notion of perceptual landscape, a novel tool used here to describe the utilisation of space by the mouse colony based on the sampling of individuals in discrete locations. We then implement the behavioural assumptions of the perceptual landscape in a multi-agent simulation to verify their accuracy in the reproduction of observed social patterns. We find that many high-level features -- with the exception of territoriality -- of our behavioural dataset can be accounted for at the population level through the use of this simplified representation. Our findings underline the potential importance of random factors in the apparent complexity of the mice's social structure. These results resonate in the general context of adaptive behaviour versus elementary environmental interactions.

opencc-zeroDec 2011View details →
zenodo32/100

Distribution. Now restricted to the Channel Country of SW Queensland and the Lake Eyre Basin in NE South Australia. Descriptive notes. Head-body 95-120 mm, tail 105-160 mm, ear 23-29 mm, hindfoot 32-37 mm; weight 30-50 g. The Fawn Hopping Mouse has body form typical of hopping mice, with very long hindfeet, long tail with distal brush of longer hairs, very long ears, and large protruberant eyes. Dorsal fur is of variable color, from pale pinkish fawn to gray; ventral fur white. Unlike most other hopping mice, it has no throat pouch, but males have a glandular area of naked skin on the chest. Habitat. Occurs in low shrublands and tussock grasslands on stony ("gibber") plains and claypans. Shows marked habitat segregation from the Dusky Hopping Mouse (N. fuscus), which is closely associated with sandy substrates. Food and Feeding. The Fawn Hopping Mouse is mostly granivorous, but also eats other plant material (stems, leaves) and occasionally invertebrates. It uses succulent, salt-adapted plants around edges of claypans as a source of water. Breeding. Reproduction is probably largely opportunistic and aseasonal, with high reproductive output from near-continuous breeding after periods of high rainfall; reported littersize is 1-5, most commonly three; gestation period 38-43 days for nonlactating females. Females may mature later than other hopping mice, with reproductive maturity reached at about six months. Activity patterns. Terrestrial and nocturnal. Fawn Hopping Mice shelter during day in burrow systems that are typically simpler and shallower than those of other hopping mice. Movements, Home range and Social organization. Fawn Hopping Mice generally live singly or in small groups; typically uncommon within range, but population density may increase by an order of magnitude following periods of high rainfall. Status and Conservation. Classified as Near Threatened on The IUCN Red List. The Fawn Hopping Mouse has shown marked decline in range (estimated at greater than 50%), and presumably population size, since European settlement of Australia. This is mostlikely due to predation by the introduced house cat and Red Fox (Vulpes vulpes), and to habitat degradation associated with pastoralism. Bibliography. Brazenor (1934), Burbidge et al. (2008), Finlayson (1939), Gould (1853), Jackson & Groves (2015), Murray et al. (1999), Ogilby (1892), Thomas (1921h), Van Dyck & Strahan (2008), Waite (1898), Watts & Aslin (1981), Woinarski et al. (2014), Wood Jones (1925). in Muridae

Distribution. Now restricted to the Channel Country of SW Queensland and the Lake Eyre Basin in NE South Australia. Descriptive notes. Head-body 95-120 mm, tail 105-160 mm, ear 23-29 mm, hindfoot 32-37 mm; weight 30-50 g. The Fawn Hopping Mouse has body form typical of hopping mice, with very long hindfeet, long tail with distal brush of longer hairs, very long ears, and large protruberant eyes. Dorsal fur is of variable color, from pale pinkish fawn to gray; ventral fur white. Unlike most other hopping mice, it has no throat pouch, but males have a glandular area of naked skin on the chest. Habitat. Occurs in low shrublands and tussock grasslands on stony ("gibber") plains and claypans. Shows marked habitat segregation from the Dusky Hopping Mouse (N. fuscus), which is closely associated with sandy substrates. Food and Feeding. The Fawn Hopping Mouse is mostly granivorous, but also eats other plant material (stems, leaves) and occasionally invertebrates. It uses succulent, salt-adapted plants around edges of claypans as a source of water. Breeding. Reproduction is probably largely opportunistic and aseasonal, with high reproductive output from near-continuous breeding after periods of high rainfall; reported littersize is 1-5, most commonly three; gestation period 38-43 days for nonlactating females. Females may mature later than other hopping mice, with reproductive maturity reached at about six months. Activity patterns. Terrestrial and nocturnal. Fawn Hopping Mice shelter during day in burrow systems that are typically simpler and shallower than those of other hopping mice. Movements, Home range and Social organization. Fawn Hopping Mice generally live singly or in small groups; typically uncommon within range, but population density may increase by an order of magnitude following periods of high rainfall. Status and Conservation. Classified as Near Threatened on The IUCN Red List. The Fawn Hopping Mouse has shown marked decline in range (estimated at greater than 50%), and presumably population size, since European settlement of Australia. This is mostlikely due to predation by the introduced house cat and Red Fox (Vulpes vulpes), and to habitat degradation associated with pastoralism. Bibliography. Brazenor (1934), Burbidge et al. (2008), Finlayson (1939), Gould (1853), Jackson &amp; Groves (2015), Murray et al. (1999), Ogilby (1892), Thomas (1921h), Van Dyck &amp; Strahan (2008), Waite (1898), Watts &amp; Aslin (1981), Woinarski et al. (2014), Wood Jones (1925).

opennotspecifiedNov 2017View details →
dryad32/100

Exploring the behaviors and social preferences of a large, multi-generational herd of zoo-housed southern white rhinoceros (Ceratotherium simum simum), 2020–2021

<p><span>The zoo-housed southern white rhinoceros (SWR) population is of special concern due to their lack of consistent breeding success. An enhanced understanding of SWR social preferences could better inform management planning by promoting natural social relationships, which can positively affect their well-being. The large, multigeneration herd housed at the North Carolina Zoo provides an ideal opportunity to examine rhino sociality across different ages, kin types, and social groupings. </span><span>Eight female rhinos' social and nonsocial behaviors were recorded from November 2020 through June 2021 across 242 hours. Activity budget analyses revealed strong seasonal and temporal variations in grazing and resting behaviors, with no stereotypic behaviors recorded. Bond strength calculations suggested that each female maintained strong social bonds with one to two partners. Beyond mother-nursing calf bonds, we found that the strongest social ties were maintained between calf-less adults and subadults in these dyads.</span> <span>Considering these findings, we recommend that management plans attempt to house immature females with calf-less adult females, as they may be necessary to the social landscape of immature females and, ultimately, improve their welfare.</span></p>

opencc-zeroFeb 2023View details →
ClinicalTrials.gov32/100

Enhancing Housing First Programs With a Social Network Substance Use Intervention

ClinicalTrials.gov study NCT02140359. IPD Sharing: Not stated. Countries: 1. Publications: 3.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov32/100

Cardiovascular Health Awareness Program (CHAP) in Subsidized Social Housing

ClinicalTrials.gov study NCT03549845. IPD Sharing: NO. Countries: 1. Publications: 1.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov32/100

Health and Environmental Effects of Boiler Management Systems in Social Housing

ClinicalTrials.gov study NCT00874692. IPD Sharing: Not stated. Countries: 1. Publications: 1.

restrictedIPD-UNDECIDEDFeb 2026View details →
dryad32/100

Exploring the behaviors and social preferences of a large, multi-generational herd of zoo-housed southern white rhinoceros (Ceratotherium simum simum), 2020–2021

Open the record for dataset details and reuse information.

publicFeb 2023View details →
dryad32/100

Data from: How random is social behaviour? Disentangling social complexity through the study of a wild house mouse population

Open the record for dataset details and reuse information.

publicNov 2012View details →

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Allen Brain Atlas

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allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

Annotated Behaviour and Observability Dataset (ABODe)

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abode-home-cage
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Last verified 2026-04-30Open record

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dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

International Brain Laboratory public data

The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

OpenNeuro

OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record