cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.15794725
title: CASAS ArWISE smartwatch dataset - free living, activity labels: Volume 1

description: Description

The Activity recognition from in-the-WIld SmartwatchEs (ArWISE) dataset is based on sensor data and activity labels collected from smart watches. Sensor data consist of 10Hz accelerometer, gyroscope, and relative location (distance from home location). Portions of the data are annotated with user-provided labels of their current activity.

Note: Other CASAS smart home and smartwatch datasets are also available, look for more at https://zenodo.org/communities/casas.

Csv files for each person’s data are organized into zip files by study collection dates. Volume 1 contains data collected for 69 participants between 2017 and 2022, divided into 7 distinct data collections. Each file includes a header with feature names. 

 

Features



stamp: date and time of the sensor reading (string)

yaw, pitch, roll, rotation_rate_x, rotation_rate_y, rotation_rate_z, user_acceleration_x, user_acceleration_y, user_acceleration_z: 3d movement (float)

distance_from_home: Haversine distance from the person's extracted home location (float)

course, speed, horizontal_accuracy, vertical_accuracy: float

battery_state: unplugged or charging (string)

user_activity_label: string


 

This dataset currently has 4 volumes:



Volume 1 doi: 10.5281/zenodo.15794726

Volume 2 doi: 10.5281/zenodo.15802788

Volume 3 doi: 10.5281/zenodo.15803341

Volume 4 doi: 10.5281/zenodo.15809156
description: Citation: Please cite the following paper when using this dataset:

Minor, B., Greeley, C., Holder, R., Thomas, B., Holder, L., & Cook, D. (2025). A feature-augmented transformer model to recognize functional activities from in-the-wild smartwatch data. IEEE Journal of Behavioral and Health Informatics. https://doi.org/10.1109/JBHI.2025.3586074
description: A larger version of ArWISE, containing labeled and unlabeled data for 854 participants across 20 cohorts, is available at https://datadryad.org/dataset/doi:10.5061/dryad.jdfn2z3nm. In the larger version, data are aggregated into one-minute intervals and described by extracted features.
DOI: 10.5281/zenodo.15794726
title: CASAS ArWISE smartwatch dataset - free living, activity labels: Volume 1

description: Description

The Activity recognition from in-the-WIld SmartwatchEs (ArWISE) dataset is based on sensor data and activity labels collected from smart watches. Sensor data consist of 10Hz accelerometer, gyroscope, and relative location (distance from home location). Portions of the data are annotated with user-provided labels of their current activity.

Note: Other CASAS smart home and smartwatch datasets are also available, look for more at https://zenodo.org/communities/casas.

Csv files for each person’s data are organized into zip files by study collection dates. Volume 1 contains data collected for 69 participants between 2017 and 2022, divided into 7 distinct data collections. Each file includes a header with feature names. 

 

Features



stamp: date and time of the sensor reading (string)

yaw, pitch, roll, rotation_rate_x, rotation_rate_y, rotation_rate_z, user_acceleration_x, user_acceleration_y, user_acceleration_z: 3d movement (float)

distance_from_home: Haversine distance from the person's extracted home location (float)

course, speed, horizontal_accuracy, vertical_accuracy: float

battery_state: unplugged or charging (string)

user_activity_label: string


 

This dataset currently has 4 volumes:



Volume 1 doi: 10.5281/zenodo.15794726

Volume 2 doi: 10.5281/zenodo.15802788

Volume 3 doi: 10.5281/zenodo.15803341

Volume 4 doi: 10.5281/zenodo.15809156
description: Citation: Please cite the following paper when using this dataset:

Minor, B., Greeley, C., Holder, R., Thomas, B., Holder, L., & Cook, D. (2025). A feature-augmented transformer model to recognize functional activities from in-the-wild smartwatch data. IEEE Journal of Behavioral and Health Informatics. https://doi.org/10.1109/JBHI.2025.3586074
description: A larger version of ArWISE, containing labeled and unlabeled data for 854 participants across 20 cohorts, is available at https://datadryad.org/dataset/doi:10.5061/dryad.jdfn2z3nm. In the larger version, data are aggregated into one-minute intervals and described by extracted features.
DOI: 10.17026/ar/kcyyap
title: PAN-00173386 - D-shaped single looped buckle

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00173386&lt;/p&gt;
description: Modified: 2025-04-28T13:05:51+02:00
DOI: 10.18112/openneuro.ds006833.v1.0.1
title: DeepMReye
DOI: 10.25824/redu/vjnfxs
title: Simulation results for 3GPP access technology with massive-type communication

description: These files captures detailed contextual metrics for random access procedure, data transmission, and control channel behavior across a large number of devices. The data were collected using a simulator developed for 3GPP access technologies. These dataset was obtained from a doctoral thesis evaluating the impact of MTC devices on 3GPP access technologies.
DOI: 10.57761/6jpq-ra79
title: Item Response Warehouse 2
DOI: 10.15468/dl.u9rf94
title: Occurrence Download

description: A dataset containing 12109 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cytospora",
 "HasCoordinate is true"
 ]
}

 The dataset includes 12109 records from 201 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020706-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15713578
title: CASAS Smart Home dataset - scripted complex activities, activity scores, and cognitive diagnosis

description: We hypothesize cognitive impairment can be evident in everyday task performance. We also postulate that differences in task performance can be automatically detected between cognitively healthy individuals and those with dementia and mild cognitive impairment (MCI) using smart home and ubiquitous computing technologies. This dataset contains ambient sensor readings collected in the CASAS smart apartment testbed at Washington State University for 179 participants with corresponding cognitive diagnoses.

Note: Other CASAS smart home and smartwatch datasets are also available, look for more at https://zenodo.org/communities/casas.

Data are collected continuously from ambient sensors while participants perform 24 scripted activities. Each sensor reading is reported on a separate line and is described by fields date, time, sensor, and message. The first 8 activities are performed without cues (task step reminders), the second 8 activities are performed with cues when needed, and the last 8 activities, part of a complex day out task, are interwoven in a natural manner without cues. The task list is included in the file activitylist.txt.

The file activityscores.txt provides numeric values for activities 1-8 that are based on experimenter assessment of task quality. The file also gives scores for the day out task. Finally, the file diagnosis.txt lists the diagnosis for each participant, coded as the following:

1 = dementia2 = MCI3 = middle age 45-594 = young-old 60-745 = old-old 75+6 = other medical7 = watch/at risk - follow longitudinally8 = younger adult9 = younger adult, English second language10 = diagnosis not available

The sensors are categorized (and named) as:



M01 - M51: PIR motion detectors (ON when detected motion starts and OFF when it stops)

I01 - I10: item use sensors (PRESENT or ABSENT indicating item is on sensor or not)

D01 - D019: door sensor on cabinets and doors (OPEN or CLOSE)

P001 and P002: current eletricity consumption

T001 - T006: ambient temperature sensors

BATP and BATV: sensor battery levels


The floorplan and sensor layout are provided in the file Chinook.jpg.
description: Citation: Please cite the following paper when using this dataset:Dawadi, P., Cook, D., & Schmitter-Edgecombe, M. (2013). Automated cognitive health assessment using smart home monitoring of complex tasks. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 43(6):1302-1313. doi: 10.1109/TSMC.2013.2252338
DOI: 10.5281/zenodo.15717153
title: CASAS Smart Home dataset - scripted complex activities, activity scores, and cognitive diagnosis

description: We hypothesize cognitive impairment can be evident in everyday task performance. We also postulate that differences in task performance can be automatically detected between cognitively healthy individuals and those with dementia and mild cognitive impairment (MCI) using smart home and ubiquitous computing technologies. This dataset contains ambient sensor readings collected in the CASAS smart apartment testbed at Washington State University for 179 participants with corresponding cognitive diagnoses.

Note: Other CASAS smart home and smartwatch datasets are also available, look for more at https://zenodo.org/communities/casas.

Data are collected continuously from ambient sensors while participants perform 24 scripted activities. Each sensor reading is reported on a separate line and is described by fields date, time, sensor, and message. The first 8 activities are performed without cues (task step reminders), the second 8 activities are performed with cues when needed, and the last 8 activities, part of a complex day out task, are interwoven in a natural manner without cues. The task list is included in the file activitylist.txt.

The file activityscores.txt provides numeric values for activities 1-8 that are based on experimenter assessment of task quality. The file also gives scores for the day out task. Finally, the file diagnosis.txt lists the diagnosis for each participant, coded as the following:

1 = dementia2 = MCI3 = middle age 45-594 = young-old 60-745 = old-old 75+6 = other medical7 = watch/at risk - follow longitudinally8 = younger adult9 = younger adult, English second language10 = diagnosis not available

The sensors are categorized (and named) as:



M01 - M51: PIR motion detectors (ON when detected motion starts and OFF when it stops)

I01 - I10: item use sensors (PRESENT or ABSENT indicating item is on sensor or not)

D01 - D019: door sensor on cabinets and doors (OPEN or CLOSE)

P001 and P002: current eletricity consumption

T001 - T006: ambient temperature sensors

BATP and BATV: sensor battery levels


The floorplan and sensor layout are provided in the file Chinook.jpg.
description: Citation: Please cite the following paper when using this dataset:Dawadi, P., Cook, D., & Schmitter-Edgecombe, M. (2013). Automated cognitive health assessment using smart home monitoring of complex tasks. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 43(6):1302-1313. doi: 10.1109/TSMC.2013.2252338
DOI: 10.15468/dl.9qjwea
title: Occurrence Download

description: A dataset containing 437 species occurrences available in GBIF matching the query:
{
 "and" : [
 "CoordinateUncertaintyInMeters 0.0-106300.0",
 "Country is Spain",
 "Geometry POLYGON((-8.35859 43.68866,-9.65263 42.93541,-8.8762 41.20652,-9.70439 39.47069,-9.44558 38.01741,-8.6174 37.0322,-6.59869 37.07351,-5.66698 35.99217,-3.64828 36.4515,-1.83662 36.61786,-1.26724 37.40318,-0.43906 37.48537,0.44089 38.82844,0.33737 39.9882,1.47612 41.08959,3.23602 41.78805,3.33954 42.36435,-1.62958 43.35085,-5.61522 43.65122,-8.35859 43.68866))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "PublishingOrg is one of (ebda1cab-dda8-418b-8f25-df1e71ff5bc2, 0363cbd4-f666-455e-8e86-0bbddcf51950, 8209258a-80e8-4094-aba2-a3febe5ed45b, c809c047-2f7f-4da4-a284-35d2e7d44c36, 30b36805-4849-4abb-a39c-01b3a7fa3f2e, 7fadb370-f921-11dd-af50-b8a03c50a862, 6f3ccc65-0a54-4e65-ae7e-13b92d618e7c)",
 "TaxonKey is Senecio angulatus"
 ]
}

 The dataset includes 437 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020707-251120083545085/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.30752882
title: Data for: Co-Creating a Socially Assistive Walker: Collaborating with Older Adults and Carers

description: Anonymised data and surveys can be accessed through the Figshare repository.
DOI: 10.6084/m9.figshare.30752882.v1
title: Data for: Co-Creating a Socially Assistive Walker: Collaborating with Older Adults and Carers

description: Anonymised data and surveys can be accessed through the Figshare repository.
DOI: 10.6084/m9.figshare.29060766
title: Association of air pollution and green space with endometriosis among women undergoing assisted reproductive technology: a cross-sectional study in Anhui, China

description: Air pollution has reproductive toxicity, while green space could lessen such harmful consequences. However, the current research on the link between air pollution/green space, and endometriosis remains scarce. Therefore, we investigated the separate and interactive relationships between air pollution, green space and endometriosis-related infertility. We collected data on 20,981 women from a large assisted reproductive center in Anhui, China, of whom 1,201 were diagnosed with endometriosis-related infertility. air pollution (PM<sub>2.5</sub>, PM<sub>10</sub>, NO<sub>2</sub>, CO, and SO<sub>2</sub>) and Green space (quantified using the normalized difference vegetation index [NDVI]) were evaluated using spatiotemporal models developed from satellite data. We employed multivariable logistic regression to calculate adjusted odds ratios (aOR) with 95% confidence intervals (CI). Per interquartile range (IQR) increase in exposure was associated with elevated odds of endometriosis prevalence for PM<sub>2.5</sub> (aOR = 1.20, 95%CI:1.11–1.30), PM<sub>10</sub> (1.17, 1.08–1.27), SO<sub>2</sub> (1.12, 1.02–1.24), NO<sub>2</sub> (1.18, 1.08–1.38), and CO (1.12, 1.05–1.19). Conversely, each IQR increase in NDVI<sub>500 m</sub> showed protective effects (0.72, 0.63–0.83). Notably, an additive antagonistic effect was observed between NDVI<sub>500 m</sub> and CO. Our findings indicated that air pollution could potentially increase the risk of endometriosis, while green space is its protective factor. Besides, green space might attenuate the negative impact of air pollution on endometriosis.
DOI: 10.6084/m9.figshare.29060766.v1
title: Association of air pollution and green space with endometriosis among women undergoing assisted reproductive technology: a cross-sectional study in Anhui, China

description: Air pollution has reproductive toxicity, while green space could lessen such harmful consequences. However, the current research on the link between air pollution/green space, and endometriosis remains scarce. Therefore, we investigated the separate and interactive relationships between air pollution, green space and endometriosis-related infertility. We collected data on 20,981 women from a large assisted reproductive center in Anhui, China, of whom 1,201 were diagnosed with endometriosis-related infertility. air pollution (PM<sub>2.5</sub>, PM<sub>10</sub>, NO<sub>2</sub>, CO, and SO<sub>2</sub>) and Green space (quantified using the normalized difference vegetation index [NDVI]) were evaluated using spatiotemporal models developed from satellite data. We employed multivariable logistic regression to calculate adjusted odds ratios (aOR) with 95% confidence intervals (CI). Per interquartile range (IQR) increase in exposure was associated with elevated odds of endometriosis prevalence for PM<sub>2.5</sub> (aOR = 1.20, 95%CI:1.11–1.30), PM<sub>10</sub> (1.17, 1.08–1.27), SO<sub>2</sub> (1.12, 1.02–1.24), NO<sub>2</sub> (1.18, 1.08–1.38), and CO (1.12, 1.05–1.19). Conversely, each IQR increase in NDVI<sub>500 m</sub> showed protective effects (0.72, 0.63–0.83). Notably, an additive antagonistic effect was observed between NDVI<sub>500 m</sub> and CO. Our findings indicated that air pollution could potentially increase the risk of endometriosis, while green space is its protective factor. Besides, green space might attenuate the negative impact of air pollution on endometriosis.
DOI: 10.5281/zenodo.17780316
title: Raid AU Data Archive

description: Automated monthly data collection from API
DOI: 10.5281/zenodo.15713496
title: CASAS Smart Home dataset - unscripted office behavior, motion, door, light

description: This dataset represents ambient data collected longitudinally in 11 office settings. The data are collected over 19 years, from 2007 to 2025. This is a resource for analyzing naturalistic behavior in work settings.

Data are collected continuously from ambient sensors while residents perform their normal routines. The data fields are date, time, sensor identifier, and message. The sensors consist of PIR (motion) sensors and magnetic door (open/close) sensors.

Note: Other CASAS smart home and smartwatch datasets are also available, look for more at https://zenodo.org/communities/casas.

The office settings are:



ac1: shared work space in an academic building

ac2: conference room in an academic building

ac3: accessible student lab in an academic building

ac4: office in an academic building

museum: science museum

scone: commercial shared office space

stair01 through stair04: stairwells in an academic building

tokyo: research lab in an academic building (the floorplan and sensor layout for this office setting is provided in tokyo_floorplan.jpg)
description: Citation: Please cite the following paper when using this dataset:Cook, D., Crandall, A., Thomas, B., & Krishnan, N. (2013). CASAS: A smart home in a box. IEEE Computer, 46(7):62-69, 2013. https://doi.org/10.1109/MC.2012.328
DOI: 10.5281/zenodo.15713495
title: CASAS Smart Home dataset - unscripted office behavior, motion, door, light

description: This dataset represents ambient data collected longitudinally in 11 office settings. The data are collected over 19 years, from 2007 to 2025. This is a resource for analyzing naturalistic behavior in work settings.

Data are collected continuously from ambient sensors while residents perform their normal routines. The data fields are date, time, sensor identifier, and message. The sensors consist of PIR (motion) sensors and magnetic door (open/close) sensors.

Note: Other CASAS smart home and smartwatch datasets are also available, look for more at https://zenodo.org/communities/casas.

The office settings are:



ac1: shared work space in an academic building

ac2: conference room in an academic building

ac3: accessible student lab in an academic building

ac4: office in an academic building

museum: science museum

scone: commercial shared office space

stair01 through stair04: stairwells in an academic building

tokyo: research lab in an academic building (the floorplan and sensor layout for this office setting is provided in tokyo_floorplan.jpg)
description: Citation: Please cite the following paper when using this dataset:Cook, D., Crandall, A., Thomas, B., & Krishnan, N. (2013). CASAS: A smart home in a box. IEEE Computer, 46(7):62-69, 2013. https://doi.org/10.1109/MC.2012.328
DOI: 10.15468/dl.d2qv7j
title: Occurrence Download

description: A dataset containing 15108 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Spain",
 "TaxonKey is Sciurus vulgaris"
 ]
}

 The dataset includes 15108 records from 46 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020708-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17026/ar/ktvv6z
title: PAN-00173284 - devotional pendant Modern period

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00173284&lt;/p&gt;
description: Modified: 2025-04-25T12:29:04+02:00
DOI: 10.7910/dvn/9njh9e
title: Replication Data for: Friedrich, L. & Eckhard, S. (2025). Bureaucrats talk differently to men and women: Inequality in frontline communication. Journal of Public Administration Research and Theory

description: Replication Data for: Friedrich, L. & Eckhard, S. (2025). Bureaucrats talk differently to men and women: Inequality in frontline communication. Journal of Public Administration Research and Theory
DOI: 10.15468/dl.3z7cn3
title: Occurrence Download

description: A dataset containing 272 species occurrences available in GBIF matching the query:
{
 "and" : [
 "EventDate is 2005-08-14",
 "Month is August",
 "RecordedBy is Samuel Vilca C.",
 "Year 2005-2005"
 ]
}

 The dataset includes 272 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020710-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dtthkn
title: Occurrence Download

description: A dataset containing 3754 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is one of (Madhuca indica, Madhuca longifolia latifolia)"
 ]
}

 The dataset includes 3754 records from 35 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020709-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8ehrr3
title: Occurrence Download

description: A dataset containing 32 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Valsalnicola",
 "HasCoordinate is true"
 ]
}

 The dataset includes 32 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020711-251120083545085/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.28646141.v1
title: Data and code for "<b>The ecological and developmental foundations of brood</b><b> </b><b>parasitism in a catfish"</b>

description: Data on ecological, reproductive, and developmental data from the Lake Tanganyika radiation of <i>Synodontis</i> catfishes, where one species, the cuckoo catfish, exhibits brood parasitism of mouthbrooding cichlid fishes, and associated analyses.
DOI: 10.7910/dvn/q9d6mz
title: Dataset of flight schedules, passenger flow, indoor and outdoor environment, HVAC systems in airport

description: The dataset includes flight schedules, passenger security-check information (no privacy), HVAC systems, and indoor and outdoor environment in airport terminals.
DOI: 10.5519/qd.wbe7f666
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (190 records)