cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.7807/immo:redx:suf:v14.1
title: Regional Real Estate Price Index for Germany - SUF, 2008-05/2024
title: SUF Off-site

description: Based on the RWI-GEO-RED data that base on the data provided by ImmobilienScout24 hedonic housing price indices are estimated. The indices are on the grid level, LMR, district/county and municipality level. We conduct a hedonic price regression that covers characteristics of the object as well as regional fixed effects. The hedonic regression is estimated separately for houses for sale as well as apartments for rent and for sale. We also offer a combined index which combines the individual housing types into one index. There are three different specifications: First, the overall time development from 01/2008 to 05/2024 on grid level given yearly and quaterly; Second, cross-regional differences for each year separately and time development within one region from 01/2018 to 05/2024 (municipality, district, LMR, and grid level); third, the time-region fixed effect between 2008 and 2024, which is used to determine the price changes for all three region types to the base year of 2008.
description: Sampled Universe: The data is based on the data set RWI-GEO-RED, that collects all offers for private housing on ImmobilienScout24 between January 2008 and May 2024. ImmobilienScout24 is the largest listing website for real estate in Germany. The price indices are estimated labor market region, district and municipality level

Sampling: Stratified random sampling
Collection Mode: Other
description: Unit Type: GeographicUnit, Number of Units: 1047014
DOI: 10.15468/dl.6ze8tq
title: Occurrence Download

description: A dataset containing 2957 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United States of America",
 "OccurrenceStatus is Present",
 "TaxonKey is Necturus maculosus"
 ]
}

 The dataset includes 2957 records from 74 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007462-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k2azdn
title: Occurrence Download

description: A dataset containing 40572 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (function (name, pos = -1, envir = as.environment(pos), all.names = FALSE, pattern, sorted = TRUE) \n{\n if (!missing(name)) {\n pos &lt;- tryCatch(name, error = function(e) e)\n if (inherits(pos, \"error\")) {\n name &lt;- substitute(name)\n if (!is.character(name)) \n name &lt;- deparse(name)\n warning(gettextf(\"%s converted to character string\", sQuote(name)), domain = NA)\n pos &lt;- name\n }\n }\n all.names &lt;- .Internal(ls(envir, all.names, sorted))\n if (!missing(pattern)) {\n if ((ll &lt;- length(grep(\"[\", pattern, fixed = TRUE))) && ll != length(grep(\"]\", pattern, fixed = TRUE))) {\n if (pattern == \"[\") {\n pattern &lt;- \"\\\\[\"\n warning(\"replaced regular expression pattern '[' by '\\\\\\\\['\")\n }\n else if (length(grep(\"[^\\\\\\\\]\\\\[&lt;-\", pattern))) {\n pattern &lt;- sub(\"\\\\[&lt;-\", \"\\\\\\\\\\\\[&lt;-\", pattern)\n warning(\"replaced '[&lt;-' by '\\\\\\\\[&lt;-' in regular expression pattern\")\n }\n }\n grep(pattern, all.names, value = TRUE)\n }\n else all.names\n}, Bidens pilosa, Ageratina adenophora, Chromolaena odorata, Praxelis clematidea, Leucaena leucocephala, Mimosa diplotricha, Trifolium repens, Oenothera biennis, Malvastrum coromandelianum, Amaranthus blitum, Amaranthus viridis, Opuntia dillenii, Solanum erianthum, Synedrella nodiflora, Sphagneticola trilobata, Tridax procumbens, Calopogonium mucunoides, Euphorbia hypericifolia, Euphorbia peplus, Phyllanthus amarus, Waltheria indica, Sieruela rutidosperma, Mitracarpus hirtus, Coreopsis lanceolata)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Living Specimen, Machine Observation, Literature Occurrence)",
 "Country is one of (China, Chinese Taipei)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 40572 records from 70 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007463-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7807/microm:v15
title: Socio-economic data on grid level ( SUF On-site)

description: The RWI-GEO GRID dataset provides socio-economic data on 1x1 km grid cells in which residential and commercial properties in Germany are located. For each grid cell, the data set contains a large number of variables on households, household structure, demographics, the proportion of foreigners, mobility, purchasing power, unemployment rate and credit default risk. The data is currently available for the years 2005 and 2009-2023.
description: Sampled Universe: 
Microm uses more than a billion individual datapoints for the aggregation of the microm dataset. These are anonymised and stem from various data sources. The datatapoints are are available for the over 40 million households in Germany, while the final data product contains information on approximately 20 million houses.

Sampling: 
For data privacy reasons, houses within a residential environment are summed up to a "virtual" micro-geographic segment (so-called micro-cell). If necessary, houses are combined with similar houses on the same street. Combined houses are as close as possible in spatial terms. Structural indicators are aggregated on the micro cell level and subsequently computed household level averages are computed. If such data exist, the calculated data is made consistent with official data sources.
description: Collection Mode: Aggregation
description: Unit Type: GeographicUnit, Number of Units: 224613
DOI: 10.15468/dl.2js875
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Artemisia pontica",
 "Country is Lithuania",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007465-250920141307145/datasets/export for details.
DOI: 10.15468/dl.sr6wdj
title: Occurrence Download

description: A dataset containing 17 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Artemisia pontica",
 "Country is Norway",
 "HasCoordinate is true"
 ]
}

 The dataset includes 17 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007466-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.usbbs6
title: Occurrence Download

description: A dataset containing 134 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Artemisia pontica",
 "Country is Sweden",
 "HasCoordinate is true"
 ]
}

 The dataset includes 134 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007467-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hq8n8n
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Living Specimen)",
 "DatasetKey is Inventario de Peces del Santuario de Fauna y Flora de Malpelo",
 "Geometry POLYGON((-111.48673 21.00035,-105.26498 15.95001,-90.22434 8.64736,-83.90307 1.97263,-82.29142 0.07504,-80.17771 -0.01235,-76.94096 4.01516,-77.2275 4.59037,-77.33119 6.5443,-77.78263 6.87851,-78.49985 8.69983,-79.30637 8.92253,-79.80695 8.6276,-81.07391 7.82447,-83.54743 9.9782,-86.98186 12.96861,-94.35711 16.26777,-105.30103 20.8522,-109.59644 22.02147,-111.48673 21.00035))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Issue is Coordinate rounded",
 "OccurrenceStatus is Present",
 "PublishingOrg is ef3ec46c-c2e6-4674-a663-77b334fa6003",
 "TaxonKey is Mustelus lunulatus"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007468-250920141307145/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.30184141
title: <b>Genomics of Soil Animal Adaptation: Insights from Collembola Evolution</b>

description: This dataset contains genome annotations for ten Collembolan species and strains used in our genomic studies, as part of the supplementary materials for the manuscript titled "Genomics of soil animal adaptation: Insights from Collembola evolution."
DOI: 10.6084/m9.figshare.30184141.v1
title: <b>Genomics of Soil Animal Adaptation: Insights from Collembola Evolution</b>

description: This dataset contains genome annotations for ten Collembolan species and strains used in our genomic studies, as part of the supplementary materials for the manuscript titled "Genomics of soil animal adaptation: Insights from Collembola evolution."
DOI: 10.5281/zenodo.17178713
title: CGMap can obtain parallel multi-order propagation matrices through preprocessing (OPP_info)

description: The resource is the multi-order parallel propagation matrices preprocessed by CGMap, which can be directly copied to OPP_info in CGMap.
DOI: 10.5281/zenodo.17178712
title: CGMap can obtain parallel multi-order propagation matrices through preprocessing (OPP_info)

description: The resource is the multi-order parallel propagation matrices preprocessed by CGMap, which can be directly copied to OPP_info in CGMap.
DOI: 10.7807/immo:red:cross:v6
title: RWI Real Estate Data - Campus File Cross-Section
title: CUF

description: ImmobilienScout24 is the largest real estate internet platform in Germany. Properties for private as well as commercial use are offered on the website. However, the data only cover residential properties. The dataset covers most characteristics collected on the platform like price, size and characteristics of the housing unit but also automatically generated items like the duration of the advertisement spell.
description: Sampled Universe: All houses for sale, all apartments for sale and all apartments for rent at ImmobilienScout24

Sampling: Stratified random sample
description: Collection Mode: Observation.ComputerBased
description: Unit Type: HousingUnit, Number of Units: 763013
DOI: 10.57967/hf/6568
title: reef-guidance-system
DOI: 10.15468/dl.kfx24g
title: Occurrence Download

description: A dataset containing 3178 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Malaysia",
 "DatasetKey is iNaturalist Research-grade Observations",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Nepenthes"
 ]
}

 The dataset includes 3178 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007469-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17180830
title: Dataset
DOI: 10.5281/zenodo.17180831
title: Dataset
DOI: 10.7807/ghhp:building:v2
title: The German Heating and Housing Panel (GHHP) - Wave 2
title: Wärme- und Wohnen-Panel - Welle 2
title: SUF Off-site

description: The results of the German Heating and Housing Panel (GHHP) 2022 build on the first wave of the GHHP, which was surveyed in 2021. The GHHP creates a new type of data basis for the heating and energy infrastructure in Germany. The second survey wave for 2022 consists of a sample of 15,321 households. Almost 80% of respondents already took part in the first survey in 2021. 65% of respondents are owner-occupiers, 25% of whom are also renters of residential property. 35% of respondents are renters. In addition to detailed information on the building stock, existing heating systems and heating costs as well as the socio-economic characteristics of households, the survey also examines modernization measures that have already been carried out or are planned. In addition to a repeated survey of support for various discussed and already introduced policy instruments in the building sector, the focus of the second survey was on the obstacles to energy-efficient renovation for private households, the reaction of households to the energy crisis and an experiment on energy-saving premiums. This data set only contains information on the building characteristics, which can be used to calculate final energy requirements for the buildings, among other things. Repeat participants who did not move were not asked about their building characteristics again in 2022. Therefore, the information from the first wave was used here and also updated if a household stated that it had replaced/renewed relevant components since the last survey.
description: Sampled Universe: private households in Germany

Sampling: forsa.omninet: largely previos participants from GHHP wave 1, partially from sample "Private households in Germany"
description: Collection Mode: Interview.WebBased
description: Building Characteristics, Unit Type: Household, Number of Units: 15321
DOI: 10.5281/zenodo.17059731
title: Multilingual encryption of WebShell malicious traffic datasets

description: 该数据集通过模拟C/S业务系统和外部访问加密Webshell的恶意流量收集,总大小为684MB,编码为base64,Xor,涵盖了不同语言类型的PHP/JSP/ASP的恶意流量
DOI: 10.5281/zenodo.17059732
title: Multilingual encryption of WebShell malicious traffic datasets

description: 该数据集通过模拟C/S业务系统和外部访问加密Webshell的恶意流量收集,总大小为684MB,编码为base64,Xor,涵盖了不同语言类型的PHP/JSP/ASP的恶意流量
DOI: 10.6084/m9.figshare.30184165
title: AI-Chatbot Adoption and Continuance Intention in the Banking Sector: An Empirical Study

description: Data set
DOI: 10.6084/m9.figshare.30184165.v1
title: AI-Chatbot Adoption and Continuance Intention in the Banking Sector: An Empirical Study

description: Data set
DOI: 10.7807/ghhp:experiment:v2
title: The German Heating and Housing Panel (GHHP) - Wave 2
title: Wärme- und Wohnen-Panel - Welle 2
title: SUF Off-site

description: The results of the German Heating and Housing Panel (GHHP) 2022 build on the first wave of the GHHP, which was surveyed in 2021. The GHHP creates a new type of data basis for the heating and energy infrastructure in Germany. The second survey wave for 2022 consists of a sample of 15,321 households. Almost 80% of respondents already took part in the first survey in 2021. 65% of respondents are owner-occupiers, 25% of whom are also renters of residential property. 35% of respondents are renters. In addition to detailed information on the building stock, existing heating systems and heating costs as well as the socio-economic characteristics of households, the survey also examines modernization measures that have already been carried out or are planned. In addition to a repeated survey of support for various discussed and already introduced policy instruments in the building sector, the focus of the second survey was on the obstacles to energy-efficient renovation for private households, the reaction of households to the energy crisis and an experiment on energy-saving premiums. This data set only contains information on the building characteristics, which can be used to calculate final energy requirements for the buildings, among other things. Repeat participants who did not move were not asked about their building characteristics again in 2022. Therefore, the information from the first wave was used here and also updated if a household stated that it had replaced/renewed relevant components since the last survey.
description: Sampled Universe: private households in Germany

Sampling: forsa.omninet: largely previos participants from GHHP wave 1, partially from sample "Private households in Germany"
description: Collection Mode: Interview.WebBased
description: Socioeconomic Characteristics and Experiments

Unit Type: Household

Number of Units: 15321
DOI: 10.7807/ghhp:cuf:v1
title: The German Heating and Housing Panel (GHHP) Campus File - Wave 1
title: Wärme- und Wohnen-Panel Campus-File Welle 1
title: CUF

description: The results of the German Heating and Housing Panel 2021 lay the foundation for the establishment of a new type of data basis on the heating and energy infrastructure in Germany. The first survey wave for 2021 consists of a sample of 15,416 households. 65 percent of respondents are owner-occupiers, 25 percent of whom are also renters of residential property. 35 percent of respondents are renters. In addition to detailed information on the building stock, existing heating systems and heating costs as well as socioeconomic characteristics of the households, the survey also examines modernization measures that have already been carried out or are planned. Households were also asked, among other things experimentally, about their assessment of and attitude toward policy instruments already introduced or planned, as well as CO2 pricing. This dataset is a subset of the Scientific Use File (SUF) and includes 50% of the original GHHP sample, randomly drawn to reflect the population distribution of homeownership in Germa-ny. The Campus File contains the same variables as the SUF, with a few exceptions: several variables were excluded due to redundancy or limited analytical relevance, including all varia-bles from Module 2 and Module 3 (except the PK3 time discounting variables).
description: Sampled Universe: private households in Germany
Sampling: forsa.omninet: partially participants from GRECS, partially from sample "Private households in Germany"
Collection Mode: Interview.WebBased
description: Unit Type: Household
Numer of Units: 7708
DOI: 10.6084/m9.figshare.30184129
title: Seroprevalence of Human Cytomegalovirus IgG Antibodies and Risk Assessment of the Virus Infection among Pregnant Women in Tripoli, Libya

description: Abstract<b>Background</b>: HCMV infection is the most prevalent congenital viral infection around the world and the leading cause of sensorineural hearing loss in infants and young children. In Libya, only a few studies investigated the prevalence of HCMV infection among pregnant women. Due to these reasons, the purpose of this study is to identify the seroprevalence of anti-HCMV IgG in pregnant women who attended the reference medical laboratory—Tripoli. Additionally, to determine risk factors linked to HCMV IgG positivity in these pregnant women.<b>Material and methods</b>: A total of 97 serum samples were collected from pregnant women. The socioeconomic characteristics and risk factors for HCMV infection of every pregnant woman were collected via a questionnaire. Using the VIDAS CMV IgG (CMVG) assay, the sera of the pregnant women were tested for anti-HCMV IgG. The Statistical Package for Social Sciences (SPSS) version 26.0 statistical program was used to analyze the results.<b>Results:</b> Out of 97 pregnant women who participated in the study, 93 tested positive for an anti-HCMV IgG, yielding a seroprevalence of 95.8%. The seroprevalence of anti-HCMV IgG has no significant association with the type of ABO system, presence of antigen D, age group, place of residence, educational level, occupation, monthly income, gestational age, parity, abortion, stillbirths, and blood transfusion.<b>Conclusion:</b> The seroprevalence of anti-HCMV IgG among pregnant women in Tripoli, Libya, is high (95.8%), consistent with previous studies from underdeveloped nations. There was no significant association between HCMV IgG positivity and any risk factors associated with it An awareness program regarding HCMV infection, its potential risks, and transmission route is recommended.<b>DOI:</b> https://doi.org/10.54361/LJMR.19.1.22
DOI: 10.6084/m9.figshare.30184129.v1
title: Seroprevalence of Human Cytomegalovirus IgG Antibodies and Risk Assessment of the Virus Infection among Pregnant Women in Tripoli, Libya

description: Abstract<b>Background</b>: HCMV infection is the most prevalent congenital viral infection around the world and the leading cause of sensorineural hearing loss in infants and young children. In Libya, only a few studies investigated the prevalence of HCMV infection among pregnant women. Due to these reasons, the purpose of this study is to identify the seroprevalence of anti-HCMV IgG in pregnant women who attended the reference medical laboratory—Tripoli. Additionally, to determine risk factors linked to HCMV IgG positivity in these pregnant women.<b>Material and methods</b>: A total of 97 serum samples were collected from pregnant women. The socioeconomic characteristics and risk factors for HCMV infection of every pregnant woman were collected via a questionnaire. Using the VIDAS CMV IgG (CMVG) assay, the sera of the pregnant women were tested for anti-HCMV IgG. The Statistical Package for Social Sciences (SPSS) version 26.0 statistical program was used to analyze the results.<b>Results:</b> Out of 97 pregnant women who participated in the study, 93 tested positive for an anti-HCMV IgG, yielding a seroprevalence of 95.8%. The seroprevalence of anti-HCMV IgG has no significant association with the type of ABO system, presence of antigen D, age group, place of residence, educational level, occupation, monthly income, gestational age, parity, abortion, stillbirths, and blood transfusion.<b>Conclusion:</b> The seroprevalence of anti-HCMV IgG among pregnant women in Tripoli, Libya, is high (95.8%), consistent with previous studies from underdeveloped nations. There was no significant association between HCMV IgG positivity and any risk factors associated with it An awareness program regarding HCMV infection, its potential risks, and transmission route is recommended.<b>DOI:</b> https://doi.org/10.54361/LJMR.19.1.22
DOI: 10.15468/dl.a2gnma
title: Occurrence Download

description: A dataset containing 38 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Artemisia pontica",
 "Country is United States of America",
 "HasCoordinate is true"
 ]
}

 The dataset includes 38 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007470-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.q3b9c6
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Living Specimen)",
 "DatasetKey is Inventario de Peces del Santuario de Fauna y Flora de Malpelo",
 "Geometry POLYGON((-111.48673 21.00035,-105.26498 15.95001,-90.22434 8.64736,-83.90307 1.97263,-82.29142 0.07504,-80.17771 -0.01235,-76.94096 4.01516,-77.2275 4.59037,-77.33119 6.5443,-77.78263 6.87851,-78.49985 8.69983,-79.30637 8.92253,-79.80695 8.6276,-81.07391 7.82447,-83.54743 9.9782,-86.98186 12.96861,-94.35711 16.26777,-105.30103 20.8522,-109.59644 22.02147,-111.48673 21.00035))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Issue is Coordinate rounded",
 "OccurrenceStatus is Present",
 "PublishingOrg is ef3ec46c-c2e6-4674-a663-77b334fa6003",
 "TaxonKey is Squatina californica"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007472-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.