cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.zuuwq5
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((99.61799999999999 3.103173, 99.547635 3.097604, 99.479004 3.081034, 99.41379999999999 3.053872, 99.35363 3.016786, 99.299975 2.970692, 99.25415700000001 2.916726, 99.217304 2.856216, 99.19032199999999 2.790654, 99.173875 2.721655, 99.168364 2.650918, 99.173925 2.580185, 99.19041799999999 2.511197, 99.21743600000001 2.445653, 99.254312 2.385166, 99.300138 2.331224, 99.353785 2.285155, 99.413932 2.248092, 99.4791 2.220947, 99.547685 2.204389, 99.61799999999999 2.198823, 99.688315 2.204389, 99.7569 2.220947, 99.822068 2.248092, 99.882215 2.285155, 99.935862 2.331224, 99.98168800000001 2.385166, 100.018564 2.445653, 100.045582 2.511197, 100.062075 2.580185, 100.067636 2.650918, 100.062125 2.721655, 100.045678 2.790654, 100.018696 2.856216, 99.981843 2.916726, 99.936025 2.970692, 99.88236999999999 3.016786, 99.8222 3.053872, 99.756996 3.081034, 99.688365 3.097604, 99.61799999999999 3.103173))"},{"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/0003527-260120142942310/datasets/export for details.
DOI: 10.15468/dl.yja78j
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is One hundred eighteen taxonomic changes among Xyleborine ambrosia beetles (Coleoptera: Curculionidae: Scolytinae)"
 ]
}

 The dataset includes 4 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003528-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5255/ukda-sn-8066-1
title: ADDResponse: European Social Survey Round 6 (UK) Plus Auxiliary Data, 2010-2014: Secure Access

description: The ADDResponse study appended geocoded auxiliary data from a range of different sources to UK data from Round 6 of the &lt;i&gt;European Social Survey&lt;/I&gt; (ESS, UK Data Archive SN 4732), a methodologically rigorous general population survey of public attitudes and opinion. The ADDResponse dataset was used to explore survey nonresponse – arguably one of the major challenges facing social research today. As non-respondents may be very different from respondents, nonresponse can introduce significant bias into the conclusions drawn from survey data and there is a pressing need, therefore, to understand more about the extent and sources of nonresponse bias. This requires having information about both respondents and non-respondents. In the absence of interview data being available for non-respondents, this information must be obtained from other, external, sources.&lt;br&gt;
&lt;br&gt;
The ADDResponse project explored the opportunities that exist for matching external data from three different sources of survey data: small-area administrative data; commercial marketing data and geocoded information from the Ordnance Survey. Each data source was evaluated in terms of: what information it can provide which may be matched to the survey records of respondents and non-respondents; the accuracy and completeness of this information; and the challenges that matching data presents in terms of the increased risk of individuals or households being identified from the combination of data held about them. ADDResponse focused on the usefulness of these data for nonresponse modelling and adjustment. However, the same data sources may also be useful for substantive analysis, exploring the effect of local context on attitudes and behaviour.&lt;br&gt;
&lt;br&gt;
Further information about the ADDResponse project and the ESS is provided in the &lt;a href="http://www.addresponse.org" title="ADDResponse"&gt;ADDResponse&lt;/a&gt; and the &lt;a href="http://www.europeansocialsurvey.org" title="European Social Survey"&gt;European Social Survey&lt;/a&gt; websites.&lt;br&gt;
&lt;br&gt;
DOI: 10.5255/ukda-sn-8877-2
title: BOOST2018: The Ground-Breaking Study of Student Life, 2015-2020: Secure Access

description: &lt;p class="x_x_x_MsoNormal"&gt;&lt;span style="font-style: italic;"&gt;BOOST2018: The Ground-Breaking Study of Student Life, 2015-2019: Secure Access&lt;/span&gt; is a 13 wave longitudinal survey of a cohort of undergraduate students at one UK university. The data were collected over three years, from October 2015 to June 2018, using online surveys and laboratory tasks. The data are linked to administrative data on demographic characteristics, attendance at lectures and classes, and academic performance. The purpose of the study is to understand the factors determining socio-economic gaps in outcomes from Higher Education, by collecting data on expectations, preferences, access to information, and students' behaviour.&lt;/p&gt;A further online 'Life After University' (wave 14) survey was fielded in 2020 to enable the labour market and subsequent education outcomes of participants in the original BOOST2018 study to be observed after they had completed their undergraduate degrees. Due to the emergence of the coronavirus pandemic in the spring of 2020, a battery of questions on health-related behaviours and expectations was also included.&lt;br&gt;
DOI: 10.15468/dl.5apdp7
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((99.667 3.116173, 99.59663399999999 3.110604, 99.528003 3.094034, 99.46279800000001 3.066872, 99.402626 3.029786, 99.34897100000001 2.983692, 99.30315299999999 2.929725, 99.266299 2.869216, 99.239318 2.803654, 99.22287 2.734655, 99.21736 2.663918, 99.222921 2.593184, 99.239414 2.524197, 99.26643199999999 2.458653, 99.303309 2.398166, 99.349135 2.344224, 99.402782 2.298155, 99.462931 2.261092, 99.528099 2.233947, 99.59668499999999 2.217389, 99.667 2.211824, 99.737315 2.217389, 99.80590100000001 2.233947, 99.87106900000001 2.261092, 99.931218 2.298155, 99.984865 2.344224, 100.030691 2.398166, 100.067568 2.458653, 100.094586 2.524197, 100.111079 2.593184, 100.11664 2.663918, 100.11113 2.734655, 100.094682 2.803654, 100.067701 2.869216, 100.030847 2.929725, 99.985029 2.983692, 99.93137400000001 3.029786, 99.871202 3.066872, 99.805997 3.094034, 99.73736599999999 3.110604, 99.667 3.116173))"},{"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/0003529-260120142942310/datasets/export for details.
DOI: 10.7910/dvn/udkxke
title: Multi-Task Screen Content Image and Video Dataset for Compression and Segmentation

description: This dataset is designed for multi-task learning in screen content image and video coding. It contains screen content images and videos composed of both synthetic and natural regions, together with pixel-level synthetic–natural segmentation maps.
DOI: 10.15468/dl.uqpvfd
title: Occurrence Download

description: A dataset containing 11994 records in GBIF matching the query:
SELECT
 '49' AS fish_cell,
 GBIF_MGRSCode(1000, decimalLatitude, decimalLongitude, 0) AS cell, -- NO randomization
 COUNT(DISTINCT speciesKey) AS species_richness
 FROM occurrence
 WHERE hasCoordinate = TRUE
 AND speciesKey IS NOT NULL
 AND NOT ARRAY_CONTAINS(issue, 'ZERO_COORDINATE')
 AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_OUT_OF_RANGE')
 AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_INVALID')
 AND NOT ARRAY_CONTAINS(issue, 'COUNTRY_COORDINATE_MISMATCH')
 AND decimalLatitude &gt;= -24.552553756517728
 AND decimalLatitude &lt;= -20.3845909579754
 AND decimalLongitude &gt;= -74.06064323322255
 AND decimalLongitude &lt;= -67.49993166964197
 AND "year" &gt;= 2015
 AND "year" &lt;= 2026
 AND (coordinateUncertaintyInMeters &lt;= 100 OR coordinateUncertaintyInMeters IS NULL)
 GROUP BY fish_cell, cell

 The dataset's 11994 records were derived from 48 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003522-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wzdt76
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((117.746 3.124173, 117.675633 3.118604, 117.607002 3.102034, 117.541796 3.074871, 117.481625 3.037786, 117.427969 2.991692, 117.38215 2.937725, 117.345297 2.877215, 117.318315 2.811653, 117.301867 2.742654, 117.296357 2.671917, 117.301918 2.601184, 117.318411 2.532197, 117.34543 2.466653, 117.382307 2.406165, 117.428133 2.352224, 117.481781 2.306155, 117.541929 2.269092, 117.607098 2.241947, 117.675684 2.225389, 117.746 2.219824, 117.816316 2.225389, 117.884902 2.241947, 117.950071 2.269092, 118.010219 2.306155, 118.063867 2.352224, 118.109693 2.406165, 118.14657 2.466653, 118.173589 2.532197, 118.190082 2.601184, 118.195643 2.671917, 118.190133 2.742654, 118.173685 2.811653, 118.146703 2.877215, 118.10985 2.937725, 118.064031 2.991692, 118.010375 3.037786, 117.950204 3.074871, 117.884998 3.102034, 117.816367 3.118604, 117.746 3.124173))"},{"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 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003530-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/14574960
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.dahahe
title: Occurrence Download

description: A dataset containing 20592 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Erethizon dorsatus",
 "Year 1986-2026"
 ]
}

 The dataset includes 20592 records from 87 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003531-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hcndd8
title: Occurrence Download

description: A dataset containing 14 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Psychrolutes marcidus",
 "Year 2000-2026"
 ]
}

 The dataset includes 14 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003532-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/11617927
title: An even smaller dataset
DOI: 10.15468/dl.vztcnt
title: Occurrence Download

description: A dataset containing 38654 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Thuja plicata",
 "Year 2000-2026"
 ]
}

 The dataset includes 38654 records from 287 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003533-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rzwhrh
title: Occurrence Download

description: A dataset containing 12111 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Tamiasciurus douglasii",
 "Year 1975-2026"
 ]
}

 The dataset includes 12111 records from 48 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003535-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18319060
title: Referential and Temporal Cohesion Dataset: 10 ChatGPT + 10 Grok Narrative Texts (500 Words) with Coh-Metrix Outputs and SPSS Analysis Files

description: This dataset contains 20 original  500 word narrative texts generated by ChatGPT (GTP-5 free tier)  and Grok (Grok-4 free tier) using identical zero-shot prompts. the texts were generated to investigate referential and temporal cohesion differences between the two large language models. Also included are: raw Coh-Metrix 3.0 output tables  (Referential indices CRFNO1-CRFCWOa and temporal indices CNCTemp, SMTEMP), cleaned .txt files and SPSS 2026 dataset.
DOI: 10.5281/zenodo.18319059
title: Referential and Temporal Cohesion Dataset: 10 ChatGPT + 10 Grok Narrative Texts (500 Words) with Coh-Metrix Outputs and SPSS Analysis Files

description: This dataset contains 20 original  500 word narrative texts generated by ChatGPT (GTP-5 free tier)  and Grok (Grok-4 free tier) using identical zero-shot prompts. the texts were generated to investigate referential and temporal cohesion differences between the two large language models. Also included are: raw Coh-Metrix 3.0 output tables  (Referential indices CRFNO1-CRFCWOa and temporal indices CNCTemp, SMTEMP), cleaned .txt files and SPSS 2026 dataset.
DOI: 10.6084/m9.figshare.24285976
title: Pochini_dataset_JGR_2025

description: This archive contains the model output of the simulations run by Enrico Pochini (https://orcid.org/0000-0001-9600-3289), accompanying the paper "Characterization of the Ross Ice Shelf Basal Melting Variability Based on a Mixing Ratios Analysis of Simulated Water Masses", submitted to Geophysical Research Letters.Sub-folders:-basal melting: contains the model freshwater flux (m/y), and its integration, also the contribution obtained with the mixing method among each water mass.-mixing ratios: contains the mixing ratios calculated from the T,S at the ice shelf draft (in range [0,1])-sea ice: contains the model sea ice output fields used to calculated the sea ice formation budget.-mooring F: contains daily output extracted in the area nearby the mooring F, and the raw data of the mooring instrument used for the comparison, showed in Supplementary Material, Figure S19.-transect RIS 95: contains model and CTD data used to produce the transect along the Ross Ice Shelf showed in Figure 1.-file with the time-averaged 3-D model fields-"climate_indices": indices used for correlation analysis<br>
DOI: 10.6084/m9.figshare.24285976.v1
title: Pochini_dataset_JGR_2025

description: This archive contains the model output of the simulations run by Enrico Pochini (https://orcid.org/0000-0001-9600-3289), accompanying the paper "Characterization of the Ross Ice Shelf Basal Melting Variability Based on a Mixing Ratios Analysis of Simulated Water Masses", submitted to Geophysical Research Letters.Sub-folders:-basal melting: contains the model freshwater flux (m/y), and its integration, also the contribution obtained with the mixing method among each water mass.-mixing ratios: contains the mixing ratios calculated from the T,S at the ice shelf draft (in range [0,1])-sea ice: contains the model sea ice output fields used to calculated the sea ice formation budget.-mooring F: contains daily output extracted in the area nearby the mooring F, and the raw data of the mooring instrument used for the comparison, showed in Supplementary Material, Figure S19.-transect RIS 95: contains model and CTD data used to produce the transect along the Ross Ice Shelf showed in Figure 1.-file with the time-averaged 3-D model fields-"climate_indices": indices used for correlation analysis<br>
DOI: 10.5255/ukda-sn-8004-1
title: English House Condition Survey, 1996; 2001 - 2007: Secure Access
title: EHCS

description: The &lt;I&gt;English House Condition Survey&lt;/I&gt; (EHCS) was a national survey of housing in England, commissioned by the Department for Communities and Local Government (DCLG). The survey was originally called the &lt;I&gt;National House Condition Survey&lt;/I&gt; and covered England and Wales. The information obtained through the survey provides an accurate picture of the type, condition and energy efficiency of housing in England, the people living there, and their views on housing and their neighbourhoods. The survey covers all tenure types.&lt;br&gt;
&lt;br&gt;
The EHCS ran quinquennially from 1967-2001. From 2002, the survey moved to a continuous basis and the data were provided as a two-year rolling sample of approximately 16,000 cases (i.e. the data for 2003 cover information collected from April 2002 to March 2004, data for 2004 comprise information collected from April 2003 to March 2005). From April 2008, the EHCS merged with the &lt;I&gt;Survey of English Housing&lt;/I&gt; (SEH) (available at the UK Data Archive under GN 33277) to form the &lt;I&gt;English Housing Survey&lt;/I&gt; (EHS) (available at the Archive under GN 33422).&lt;br&gt;
&lt;br&gt;
Further information can be found on the &lt;a class="external" href="https://www.gov.uk/government/organisations/department-for-communities-and-local-government/about/statistics" title="Statistics at DCLG"&gt;Statistics at DCLG&lt;/a&gt; webpage and the &lt;a class="external" href="https://www.gov.uk/government/collections/english-housing-survey" title="English Housing Survey"&gt;English Housing Survey&lt;/a&gt; web page.&lt;br&gt;
&lt;br&gt;
&lt;b&gt;Secure Access EHCS Data:&lt;/b&gt;&lt;br&gt;
Secure Access datasets for the EHCS include two detailed geographical variables that are not available in the standard End User Licence (EUL) versions: Postcodes and Lower Layer Super Output Areas. The two variables are available in separate Geographical Information data files, along with the key variable 'aacode', allowing the user to merge with other files of their choice. All other files are the same as in the EUL versions.&lt;br&gt;
&lt;br&gt;
Prospective users of the Secure Access version of the EHCS will need to fulfil additional requirements, commencing with the completion of an extra application form to demonstrate to the data owners exactly why they need access to the extra, more detailed variables, in order to obtain permission to use that version. Secure Access users must also complete face-to-face training and agree to Secure Access' User Agreement and Licence Compliance Policy (see 'Access' section below). Therefore, users are encouraged to download and inspect the EUL versions of the data prior to ordering the Secure Access version.&lt;br&gt;
&lt;br&gt;
DOI: 10.5255/ukda-sn-8492-1
title: Further Education Learners and Apprentices Survey, 2018: Secure Access

description: &lt;p&gt;The &lt;span style="font-style: italic;"&gt;Further Education Learners and Apprentices Survey, 2018: Secure Access&lt;/span&gt; involved 12,872 adult learners and apprentices. The research aimed to provide a full and detailed picture of learners’ and apprentices’ journeys: to provide a detailed understanding of the background of FE learners and apprentices; to capture information from learners and apprentices on their experiences and perceptions, and; to obtain consent from respondents to match their responses to the Longitudinal Educational Outcome (LEO) dataset.&lt;br&gt;&lt;br&gt;Further information and publications can be found on the &lt;a href="https://www.gov.uk/government/publications/fe-learners-and-apprentices-survey" target="_blank"&gt;FE Learners and Apprentices Survey&lt;/a&gt; webpage.&lt;/p&gt;
DOI: 10.5255/ukda-sn-9405-1
title: Glasgow Mobility App Survey, 2022: Secure Access
title: GlaMAS

description: &lt;p&gt;The &lt;span style="font-style: italic;"&gt;Glasgow Mobility App Survey&lt;/span&gt; (GlaMAS) is a cross-sectional survey based on a sample of the general adult population living in private residences across the Glasgow city region. &lt;span&gt;The data collection aimed to capture information about individuals' travel behaviour through three methods. First, the researchers conducted a household survey to get information on socio-demographic characteristics and travel-related attitudes and behaviours. Second, each participant was asked to install TravelAI's 'MyWays' app on their mobile phone. The app automatically tracks the locations of individuals, detects stops, and estimates the mode of travel. Third, participants were asked to complete a one-day travel diary administered through the 'MyWays' app so that this could be compared to the automatically-detected travel records.&lt;/span&gt;&lt;/p&gt;
DOI: 10.5255/ukda-sn-8475-1
title: METER: UK Household Electricity and Activity Survey, 2016-2019: Secure Access
title: METER

description: &lt;p&gt;&lt;span style="font-style: italic;"&gt;Measuring and Evaluating Time-use and Electricity-use Relationships&lt;/span&gt; (METER) is a project collecting and depositing data on UK household electricity use, activities and other contextual and demographic information. METER seeks to improve our understanding of household electricity use, it's timing, flexibility and societal importance.&lt;/p&gt;&lt;p&gt;This study is subject to restrictive Secure Access conditions as it contains an additional detailed activities variable. The End User Licence (EUL) version which is the same, but excludes this detailed variable, is available from the UK Data Service under &lt;a href="https://beta.ukdataservice.ac.uk/datacatalogue/studies/study?id=8634" target="_blank"&gt;SN 8634&lt;/a&gt;. Users are advised to first obtain the standard EUL version of the data to see if they are sufficient for their research requirements. &lt;/p&gt;&lt;p&gt; &lt;/p&gt;&lt;p&gt;By combining high-resolution household electricity readings with simultaneous activity records of household members, METER data provides a platform for new analytical insights. These include among others a more detailed understanding of socio-technical drivers behind:&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;&lt;span&gt;high and low electrical consumption&lt;/span&gt;&lt;/li&gt;&lt;li&gt;&lt;span&gt;high peak time consumption&lt;/span&gt;&lt;/li&gt;&lt;li&gt;&lt;span&gt;ability to respond to the load shifting interventions&lt;/span&gt;&lt;/li&gt;&lt;li&gt;&lt;span&gt;impact of interventions on individuals&lt;/span&gt;&lt;/li&gt;&lt;li&gt;&lt;span&gt;trends in electricity user over time and in response to the adoption of new technologies and social practices&lt;/span&gt;&lt;/li&gt;&lt;/ul&gt;
&lt;p&gt;&lt;span&gt;Data was recorded from February 2016 to January 2019. This deposit includes 264 electricity records (28 hours each) with 16378 coded activities from 529 people.&lt;br&gt;&lt;br&gt;Further information about the study can be found on the &lt;a href="https://www.Energy-use.org" target="_blank" style=""&gt;project website&lt;/a&gt;, on its' &lt;a href="https://gtr.ukri.org/projects?ref=EP%2FM024652%2F1" target="_blank" style=""&gt;Gateway to Research webpage&lt;/a&gt; and on its' &lt;a href="https://github.com/PhilGrunewald/MeterData" target="_blank"&gt;GitHub webpage&lt;/a&gt;.&lt;/span&gt;&lt;/p&gt;