cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.17777971
title: Fall detection dataset UG (Underground GATE)

description: Fall Detection Dataset UG (Underground GATE)

This dataset contains 40 short videos (~5 seconds each) that contain a person either falling or some other activity (walking, sitting, standing, jumping, etc.). Its main purpose is performance evaluation of fall detection methods.

Contents

- videos/: 40 `.avi` files (fall and non-fall events)- labels.csv: A CSV file mapping each video to its class label (`fall` or `not_fall`)- LICENSE.txt: Dataset license (CC BY 4.0)- citation.bib: BibTeX citation entry

Motivation

Fall detection from video data is a very active topic in the field of Computer Vision. This dataset is made specifically for testing an already trained ML method. The videos are short and contain only one type of movement. This removes the need to implement sliding (and overlaping) windows which extract portions of the video and allows the user to focus only on the peroformance of the fall detection method. The following points characterize the set:

- Indoor scenario- Constant brightness- Only one moving person- Static background- High contrast between the moving person and the background

Recording Details

- Resolution: 1920×1080 - Frame Rate: 30 FPS- Video Duration: ~5 seconds each- Format: AVI- Camera: Lenovo ThinkPad E14 Gen5 Webcam- Lighting: Constant indoor LED lighting- Scene: Indoor, static camera, single moving person/object

Labels

The `labels.csv` file contains:

filename,labelvideo_01.avi,not_fall...video_21.avi,fall...
DOI: 10.5281/zenodo.17777970
title: Fall detection dataset UG (Underground GATE)

description: Fall Detection Dataset UG (Underground GATE)

This dataset contains 40 short videos (~5 seconds each) that contain a person either falling or some other activity (walking, sitting, standing, jumping, etc.). Its main purpose is performance evaluation of fall detection methods.

Contents

- videos/: 40 `.avi` files (fall and non-fall events)- labels.csv: A CSV file mapping each video to its class label (`fall` or `not_fall`)- LICENSE.txt: Dataset license (CC BY 4.0)- citation.bib: BibTeX citation entry

Motivation

Fall detection from video data is a very active topic in the field of Computer Vision. This dataset is made specifically for testing an already trained ML method. The videos are short and contain only one type of movement. This removes the need to implement sliding (and overlaping) windows which extract portions of the video and allows the user to focus only on the peroformance of the fall detection method. The following points characterize the set:

- Indoor scenario- Constant brightness- Only one moving person- Static background- High contrast between the moving person and the background

Recording Details

- Resolution: 1920×1080 - Frame Rate: 30 FPS- Video Duration: ~5 seconds each- Format: AVI- Camera: Lenovo ThinkPad E14 Gen5 Webcam- Lighting: Constant indoor LED lighting- Scene: Indoor, static camera, single moving person/object

Labels

The `labels.csv` file contains:

filename,labelvideo_01.avi,not_fall...video_21.avi,fall...
DOI: 10.5281/zenodo.17777415
title: Effect Data - Assessing the impact of carrier solvent and solid phase extraction blank toxicity on fish embryo testing

description: Dataset for the publication "Assessing the impact of carrier solvent and solid phase extraction blank toxicity on fish embryo testing"

 
description: UFZ-mortality-solvents



Results for the different sample preparation and carrier solvents



Goethe-mortality-pH



Results of the different pH (6.8, 7.4, 8.2)



pH-QAQC



Quality control for pH along the exposure
DOI: 10.5281/zenodo.17777414
title: Effect Data - Assessing the impact of carrier solvent and solid phase extraction blank toxicity on fish embryo testing

description: Dataset for the publication "Assessing the impact of carrier solvent and solid phase extraction blank toxicity on fish embryo testing"

 
description: UFZ-mortality-solvents



Results for the different sample preparation and carrier solvents



Goethe-mortality-pH



Results of the different pH (6.8, 7.4, 8.2)



pH-QAQC



Quality control for pH along the exposure
DOI: 10.15468/dl.v5qpfv
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Mammalia",
 "HasCoordinate is true",
 "Geometry POLYGON ((-119.8054 35.2338, -119.8052 35.23345, -119.8049 35.23312, -119.8047 35.2328, -119.8044 35.23249, -119.8041 35.2322, -119.8037 35.23192, -119.8034 35.23165, -119.803 35.2314, -119.8027 35.23116, -119.8023 35.23095, -119.8019 35.23074, -119.8014 35.23056, -119.801 35.2304, -119.8006 35.23025, -119.8001 35.23012, -119.7997 35.23002, -119.7992 35.22993, -119.7987 35.22986, -119.7982 35.22982, -119.7978 35.22979, -119.7973 35.22978, -119.7968 35.2298, -119.7963 35.22984, -119.7959 35.22989, -119.7954 35.22997, -119.7837 35.23215, -119.7832 35.23225, -119.7828 35.23236, -119.7824 35.23249, -119.7819 35.23264, -119.7815 35.23281, -119.7811 35.233, -119.7807 35.2332, -119.7803 35.23342, -119.78 35.23366, -119.7796 35.23391, -119.7793 35.23418, -119.779 35.23446, -119.7787 35.23475, -119.7784 35.23506, -119.7781 35.23537, -119.7779 35.2357, -119.7777 35.23604, -119.7775 35.23638, -119.7773 35.23674, -119.7771 35.2371, -119.777 35.23747, -119.7769 35.23784, -119.7768 35.23821, -119.7768 35.23859, -119.7767 35.23897, -119.7767 35.23936, -119.7767 35.23974, -119.7768 35.24012, -119.7768 35.2405, -119.7769 35.24087, -119.777 35.24124, -119.7772 35.24161, -119.7773 35.24197, -119.7775 35.24232, -119.7777 35.24266, -119.7817 35.249, -119.7819 35.24933, -119.7822 35.24966, -119.7824 35.24998, -119.7827 35.25028, -119.783 35.25058, -119.7834 35.25085, -119.7837 35.25112, -119.7841 35.25137, -119.7845 35.2516, -119.7848 35.25182, -119.7852 35.25202, -119.7857 35.2522, -119.7861 35.25236, -119.7865 35.25251, -119.787 35.25263, -119.7874 35.25274, -119.7879 35.25283, -119.7883 35.25289, -119.7888 35.25294, -119.7893 35.25297, -119.7898 35.25298, -119.7902 35.25296, -119.7907 35.25293, -119.7912 35.25287, -119.7916 35.2528, -119.7921 35.25271, -119.7925 35.2526, -119.8033 35.24965, -119.8037 35.24952, -119.8042 35.24937, -119.8046 35.24921, -119.805 35.24902, -119.8054 35.24882, -119.8058 35.2486, -119.8061 35.24837, -119.8065 35.24812, -119.8068 35.24785, -119.8072 35.24757, -119.8075 35.24728, -119.8077 35.24698, -119.808 35.24666, -119.8082 35.24634, -119.8085 35.246, -119.8087 35.24565, -119.8088 35.2453, -119.809 35.24494, -119.8091 35.24457, -119.8092 35.2442, -119.8093 35.24383, -119.8094 35.24345, -119.8094 35.24307, -119.8094 35.24269, -119.8094 35.24231, -119.8094 35.24192, -119.8093 35.24155, -119.8092 35.24117, -119.8091 35.2408, -119.809 35.24043, -119.8088 35.24007, -119.8086 35.23972, -119.8056 35.23415, -119.8054 35.2338))",
 "Year is greater than or equal to 2001",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020527-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17026/ar/iww06b
title: PAN-00173275 - devotional pendant Modern period

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00173275&lt;/p&gt;
description: Modified: 2025-04-26T11:16:27+02:00
DOI: 10.6084/m9.figshare.28318715.v1
title: Women’s experiences collecting and accessing water in Guatemala, Honduras, Kenya, and Zimbabwe: A mixed-methods investigation

description: 1.8 billion people live in households that collect water from sources off household premises, creating burdens that disproportionately affect women. A current and comprehensive investigation of women’s water collection experiences is needed to understand the gendered burden of this labor. This study used mixed methods, including (a) go-along, in-depth interviews (IDIs), (b) semi-structured observation, (c) activity-tracking smart watches, and (d) scales, to (1) understand women’s practices, perspectives, and experiences going to water sources; (2) determine actual water collection time, distance, caloric expenditure, total elevation ascended, weight carried, and water volume collected; and (3) assess alignment of women’s estimated and actual water journey times. Ninety-four women participated across four countries: Guatemala (n=22), Honduras (n=17), Kenya (n=22), Zimbabwe (n=33). Women reported accessing various sources depending on season and needs, faced risks due to terrain and animals, and experienced physical injury and mental burden. Experiences varied within and by country. The mean water journey time (including going to the source, activities at the source, and returning) was 82 minutes (range: 13 minutes (Guatemala) – 287 minutes (Kenya)). The mean distance traveled was 3.5km (range: 0.2km (Guatemala, Honduras, Zimbabwe) - 15.8km (Kenya)). Mean caloric expenditure was 231cal (range: 36 (Guatemala) – 952 (Zimbabwe)). The mean volume of water collected was 16.1L. (range: 3.7L (Kenya) - 38.2L (Zimbabwe). Women also carried children, wet laundry, and other items resulting in heavy loads. The mean total weight of loads brought from water sources was 19.3kg (range: 5.0kg (Honduras) - 50.1kg (Zimbabwe). Findings demonstrate how a lack of adequate and accessible water drains women of energy and time and poses risks to their well-being. Our findings reinforce the need to redouble efforts to improve water access in low-resource settings and rigorously measure the impacts of such efforts on women’s lives.
DOI: 10.6084/m9.figshare.28318715
title: Women’s experiences collecting and accessing water in Guatemala, Honduras, Kenya, and Zimbabwe: A mixed-methods investigation

description: 1.8 billion people live in households that collect water from sources off household premises, creating burdens that disproportionately affect women. A current and comprehensive investigation of women’s water collection experiences is needed to understand the gendered burden of this labor. This study used mixed methods, including (a) go-along, in-depth interviews (IDIs), (b) semi-structured observation, (c) activity-tracking smart watches, and (d) scales, to (1) understand women’s practices, perspectives, and experiences going to water sources; (2) determine actual water collection time, distance, caloric expenditure, total elevation ascended, weight carried, and water volume collected; and (3) assess alignment of women’s estimated and actual water journey times. Ninety-four women participated across four countries: Guatemala (n=22), Honduras (n=17), Kenya (n=22), Zimbabwe (n=33). Women reported accessing various sources depending on season and needs, faced risks due to terrain and animals, and experienced physical injury and mental burden. Experiences varied within and by country. The mean water journey time (including going to the source, activities at the source, and returning) was 82 minutes (range: 13 minutes (Guatemala) – 287 minutes (Kenya)). The mean distance traveled was 3.5km (range: 0.2km (Guatemala, Honduras, Zimbabwe) - 15.8km (Kenya)). Mean caloric expenditure was 231cal (range: 36 (Guatemala) – 952 (Zimbabwe)). The mean volume of water collected was 16.1L. (range: 3.7L (Kenya) - 38.2L (Zimbabwe). Women also carried children, wet laundry, and other items resulting in heavy loads. The mean total weight of loads brought from water sources was 19.3kg (range: 5.0kg (Honduras) - 50.1kg (Zimbabwe). Findings demonstrate how a lack of adequate and accessible water drains women of energy and time and poses risks to their well-being. Our findings reinforce the need to redouble efforts to improve water access in low-resource settings and rigorously measure the impacts of such efforts on women’s lives.
DOI: 10.25504/fairsharing.2ad284
title: FAIRsharing record for: eData
title: null

description: This FAIRsharing record describes:  eData is an institutional repository where STFC staff can deposit data and software that support journal articles and other published research. It offers a service for the deposit, registration, preservation, discovery, sharing and citation of these digital objects. eData does not replace subject-based, national, or STFC Facility data repositories already in use, such as ICAT. Researchers should check with their funder or facility for any specific requirements on where to deposit data or software.
description: The source of this description is the metadata record on FAIRsharing.org, an educational and informative resource that describes and links databases, standards, and data policies. FAIRsharing also creates collections of these resources and recommendations of databases and standards based on 3rd party data policies.
DOI: 10.25504/fairsharing.87c9a8
title: FAIRsharing record for: FAIR Metric - software - Software has persistent and unique identifier
title: FM - SOFT_UNIQ_ID

description: This FAIRsharing record describes:  This indicator aims to determine if the software identifier is based on a suitable identifier scheme, and whether it can be resolved. This is usually achieved by checking whether the identifier uses an identifier scheme contained in a list of globally unique identifier schemes
description: The source of this description is the metadata record on FAIRsharing.org, an educational and informative resource that describes and links databases, standards, and data policies. FAIRsharing also creates collections of these resources and recommendations of databases and standards based on 3rd party data policies.
DOI: 10.25504/fairsharing.66c0fb
title: FAIRsharing record for: CMU Graphics Lab Motion Capture Database
title: null

description: This FAIRsharing record describes:  The CMU Graphics Lab Motion Capture Database provides free 3D human and object motion data captured with Vicon cameras containing marker positions and skeleton-based motion files used in graphics animation robotics and biomechanics.
description: The source of this description is the metadata record on FAIRsharing.org, an educational and informative resource that describes and links databases, standards, and data policies. FAIRsharing also creates collections of these resources and recommendations of databases and standards based on 3rd party data policies.
DOI: 10.25504/fairsharing.1050b0
title: FAIRsharing record for: Benchmark Datasets 
title: null

description: This FAIRsharing record describes:  The Benchmark Datasets project is a three-year collaboration between four laboratories to gather and curate high-resolution building systems data from a small set of buildings. These datasets include detailed, well-calibrated time series of operational and environmental conditions, aimed at improving energy efficiency, demand flexibility, and benchmarking algorithms. The project ensures data is documented with collection methods, intended use cases, quality notes, and public availability, making it broadly applicable for high-impact building performance research.
description: The source of this description is the metadata record on FAIRsharing.org, an educational and informative resource that describes and links databases, standards, and data policies. FAIRsharing also creates collections of these resources and recommendations of databases and standards based on 3rd party data policies.
DOI: 10.25504/fairsharing.53fadc
title: FAIRsharing record for: Human Mortality Database
title: HMD

description: This FAIRsharing record describes:  The Human Mortality Database (HMD) is the data resource on mortality in developed countries. The HMD provides detailed high-quality harmonized mortality and population estimates to researchers, students, journalists, policy analysts, and others interested in human longevity. The HMD follows open data principles.
description: The source of this description is the metadata record on FAIRsharing.org, an educational and informative resource that describes and links databases, standards, and data policies. FAIRsharing also creates collections of these resources and recommendations of databases and standards based on 3rd party data policies.
DOI: 10.25504/fairsharing.b5e597
title: FAIRsharing record for: LISS Panel 
title: null

description: This FAIRsharing record describes:  Established in 2007, the LISS panel is managed by Centerdata, an independent non-profit institute based on the campus of Tilburg University. As an official partner of the university, Centerdata uses the panel to collect research data through online surveys. These data primarily support scientific research and policy development in the (experimental) social, economic, and behavioral sciences. However, researchers from other field, such as health, the humanities, and digital science, also make use of the LISS panel.
description: The source of this description is the metadata record on FAIRsharing.org, an educational and informative resource that describes and links databases, standards, and data policies. FAIRsharing also creates collections of these resources and recommendations of databases and standards based on 3rd party data policies.
DOI: 10.25504/fairsharing.f4bfb1
title: FAIRsharing record for: Czech Social Science Data Archive
title: null

description: This FAIRsharing record describes:  The Czech Social Science Data Archive (CSDA) is a national data services center for the social sciences, which acquires, processes, documents, and stores digital data files from scientific projects and makes them available for further analytical use in scientific research and teaching at universities.
description: The source of this description is the metadata record on FAIRsharing.org, an educational and informative resource that describes and links databases, standards, and data policies. FAIRsharing also creates collections of these resources and recommendations of databases and standards based on 3rd party data policies.
DOI: 10.25504/fairsharing.877ad1
title: FAIRsharing record for: RIN Data Repository
title: null

description: This FAIRsharing record describes:  The National Scientific Repository (RIN) is an application for managing data and outputs from research, development, assessment, and application activities. RIN can be used by researchers or research institutions to manage research data. RIN was developed by the Scientific Data and Documentation Centre of the Indonesian Institute of Sciences (PDII LIPI) on the basis of the Dataverse Network project, which is an open platform for scientific data from all fields of science built by the international community with the initiator of IQSS - Harvard University.
description: The source of this description is the metadata record on FAIRsharing.org, an educational and informative resource that describes and links databases, standards, and data policies. FAIRsharing also creates collections of these resources and recommendations of databases and standards based on 3rd party data policies.
DOI: 10.25504/fairsharing.9c92aa
title: FAIRsharing record for: Ocean Barcode Atlas
title: OBA

description: This FAIRsharing record describes:  The Ocean Barcode Atlas (OBA) is a web service to explore the biogeography of marine diversity based on barcodes (or Operational Taxonomic Units: OTU) sequence similarity with environmental metabarcoding datasets.
description: The source of this description is the metadata record on FAIRsharing.org, an educational and informative resource that describes and links databases, standards, and data policies. FAIRsharing also creates collections of these resources and recommendations of databases and standards based on 3rd party data policies.
DOI: 10.25504/fairsharing.066302
title: FAIRsharing record for: ConsensusPathDB
title: CPDB

description: This FAIRsharing record describes:  ConsensusPathDB-human integrates interaction networks in Homo sapiens including binary and complex protein-protein, genetic, metabolic, signaling, gene regulatory and drug-target interactions, as well as biochemical pathways. Data originate from currently 31 public resources for interactions and interactions that we have curated from the literature. The interaction data are integrated in a complementary manner (avoiding redundancies), resulting in a seamless interaction network containing different types of interactions.
description: The source of this description is the metadata record on FAIRsharing.org, an educational and informative resource that describes and links databases, standards, and data policies. FAIRsharing also creates collections of these resources and recommendations of databases and standards based on 3rd party data policies.
DOI: 10.25504/fairsharing.26794d
title: FAIRsharing record for: Badische Landesbibliothek Digital Collections
title: BLB Digital Collections

description: This FAIRsharing record describes:  In the digital collections of the Badische Landesbibliothek we offer you free access to the digitised works from our collections. We are continuously increasing the number of books and manuscripts available online. Use the search function to search the titles and structural data of the works already included, or browse the collections on the left. Special highlights from our collections and current projects can be found on the main page.
description: The source of this description is the metadata record on FAIRsharing.org, an educational and informative resource that describes and links databases, standards, and data policies. FAIRsharing also creates collections of these resources and recommendations of databases and standards based on 3rd party data policies.
DOI: 10.25504/fairsharing.6f7e20
title: FAIRsharing record for: Morphbank :: Biological Imaging
title: null

description: This FAIRsharing record describes:  Morphbank :: Biological Imaging is a database of images that scientists use for international collaboration, research and education. Images deposited in Morphbank :: Biological Imaging document a wide variety of research including: specimen-based research in comparative anatomy, morphological phylogenetics, taxonomy and related fields focused on increasing our knowledge about biodiversity.
description: The source of this description is the metadata record on FAIRsharing.org, an educational and informative resource that describes and links databases, standards, and data policies. FAIRsharing also creates collections of these resources and recommendations of databases and standards based on 3rd party data policies.
DOI: 10.25504/fairsharing.fc1e44
title: FAIRsharing record for: BeeBiome Data Portal
title: BeeBiome

description: This FAIRsharing record describes:  BeeBiome Data Portal is a resource for scientists and the general public on bee-associated microbes/viruses and their impact on bee health.
description: The source of this description is the metadata record on FAIRsharing.org, an educational and informative resource that describes and links databases, standards, and data policies. FAIRsharing also creates collections of these resources and recommendations of databases and standards based on 3rd party data policies.
DOI: 10.25504/fairsharing.4ae2b4
title: FAIRsharing record for: BigBrain Database
title: null

description: This FAIRsharing record describes:  The BigBrain database contains an ultra-high-resolution 3D reconstruction of a human post-mortem brain, created by slicing, staining, and scanning it at microscopic detail. It offers precise anatomical information, such as local morphology, cell densities, and connectivity, beyond what current standard neuroimaging can capture, especially in highly folded cortical and subcortical regions.
description: The source of this description is the metadata record on FAIRsharing.org, an educational and informative resource that describes and links databases, standards, and data policies. FAIRsharing also creates collections of these resources and recommendations of databases and standards based on 3rd party data policies.