Arizona State University Research Data Repository
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COVID Future Wave 3 Survey Data v1.1.0
No full textThis dataset is the product of the third wave of a nationwide longitudinal survey collecting information about travel-related behaviors and attitudes before, during, and after the COVID-19 pandemic. The survey questions cover a wide range of topics including commuting, daily travel, air travel, working from home, online learning, shopping, and risk perception, along with attitudinal, socioeconomic, and demographic information. Version 1.1 of the survey data contains 2,728 responses that are publicly available. Of these, 304 are from Wave 1A respondents and 2,424 are from Wave 1B respondents. The survey is deployed over multiple waves to the same respondents to monitor how behaviors and attitudes evolve over time. In addition, the data are weighted to be representative of national and regional demographics
Artificial Social Intelligence for Successful Teams (ASIST) Study 2
No full textThe ASIST Study-2 dataset was developed in a human subjects research study designed to assess the capability of artificial intelligence to infer the state and predict the actions of members of a three-person team executing an urban search and rescue task in Minecraft. The data were developed under Contract No. HR001119C0130 to the Defense Advanced Research Projects Agency (DARPA). The dataset comprises approximately 2,100 files and 300GB of data. We have partitioned the full dataset into folders that support research in specific areas. Thus, researchers can more easily download only the files of value to them.
A readme file in each folder (e.g., readme_audio.txt) describes the folder's contents in detail.
(1) Data in the studywide folder will be of interest to researchers who conduct any analysis with any data from ASIST Study-2, because these files contain data that describe the study overall, the data used to evaluate AI, or the coding of data.
(2) Data in the surveys folder will be of interest to researchers who study individual differences and their effects on behavior.
(3) Data in the testbedmessages folder will be of interest to researchers who study individual and team behavior or who use any other components of this dataset, because these are machine- and human-readable text (json) records of the state and behaviors of study participants, and of the state of the task environment.
(4) Data in the transcriptions folder will be of interest to researchers who study language use. The audio source of these imperfect machine transcriptions can be found in study video files and audio files.
(5) Data in the audio folder will be of interest to researchers who study language use, or who wish to validate, contextualize, or specify transcriptions, testbed messages, and certain survey data.
(6) Data in the video folder will be of interest to researchers who study machine vision, or who wish to validate, contextualize, or specify transcriptions, testbed messages, and certain survey data.
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Replication Data for: Emergency Fostering of Dogs From Animal Shelters During the COVID-19 Pandemic: Shelter Practices, Foster Caregiver Engagement, and Dog Outcomes
No full textEach year, millions of dogs enter thousands of animal shelters across the United States. Life in the shelter can be stressful, and one type of intervention that improves dogs’ experience is human interaction, particularly stays in foster homes. Prior research has demonstrated that fostering can reduce dogs’ cortisol and increase their resting activity. Despite these benefits, little is understood about the utilization of foster caregiving in animal shelters, and even less so during a crisis. On March 11, 2020, the World Health Organization deemed the coronavirus outbreak a worldwide pandemic, and subsequently, a nationwide emergency was declared in the United States. Nearly all states issued stay-at-home orders to curb the spread of the virus. During this time, media outlets reported increased interest in the adoption and fostering of shelter pets. This study explores canine foster caregiving at 19 US animal shelters during the first 4 months of the COVID-19 pandemic. In our investigation, we found that shelters’ utilization of foster caregiving increased from March to April 2020 but returned to initial pandemic levels by June 2020. Slightly less than two-fifths of foster caregivers were community members with no prior relationship with the shelter, and these caregivers were over four times more likely to adopt their fostered dogs than those with a pre-existing relationship with the shelter. Individuals fostering with the intention to adopt, in fact, adopted their dogs in nearly three-quarters of those instances. With regards to shelters’ available resources, we found that very low-resource shelters relied more heavily on individuals with prior relationships to provide foster caregiving while very high-resource shelters more often recruited new community members. We also found that our lowest resourced shelters transferred more dogs out of their facilities while more resourced shelters rehomed dogs directly to adopters. To our knowledge, these findings represent the first in-depth reporting about dog fostering in US animal shelters and, more specifically, foster caregiving during the COVID-19 pandemic. In total, they provide a greater understanding of how monetary and human resources were utilized to affect the care and ultimately, the outcomes of shelter dogs during this time
Parler and the Road to the Capitol Attack: Parler Influencer Dataset
No full textThis dataset consists of publicly available Parler posts of prominent and prolific Parler users, selected for their influence on the platform as determined by either their close ties to the Trump White House or President Trump’s presidential campaign, or links to militia groups such as the Proud Boys, Oath Keepers, and Three-Percenters. This specially curated dataset of Parler influencers contains approximately 40,000 posts, with about 30,000 containing text. While this sample cannot be categorized as representative because it is small relative to the roughly 183 million Parler posts in publicly available datasets, it does offer a window into how key Trump supporters framed their concerns about the elections and other polarizing causes that roiled the nation in the lead up to January 6.
The dataset supports the report Parler and the Road to the Capitol Attack, the first in a series of investigations into the impact of the "alt-tech" movement on U.S. national security. The report presents an initial snapshot of observations culled from an ongoing analysis of open source data related to the January 6, 2021, United States Capitol attack.
Funded by New America Foundation
Dataset is comprised of approximately 200 JSON files totaling 83 MB
For the creation of the dataset and for analysis, the team used Python programming language and the pandas Data Analysis Library.</p
The Effects of Unsteady Effusion Rates on Lava Flow Emplacement
No full textThis dataset consists of observations from 150 lava flow simulation experiments performed to understand lava flow propagation. The crux of the dataset is two spreadsheets detailing the calculation, observations, and data visualizations from this experimental dataset. Also included are photographs from these experiments taken at the conclusion of each experimental run.
Project: The effects of unsteady effusion rates on lava flow emplacement: insights from laboratory analogue experiments
The data was collected by performing experiments to simulate lava flow emplacement using polyethylene glycol (PEG) 600 wax in the Volcano Lab at Arizona State University.
This methodology has previously been documented in Fink and Griffiths [1990], Gregg and Fink [1996], and more recently with methods similar to ours in Rader et al. [2017]. The experiments were produced by erupting PEG 600 wax into a
chilled water bath via a peristaltic pump. Experiments were measured, characterized, and photographed and/or recorded. Experiments were photographed and recorded using a Nikon digital camera.</p
Zelinski Lab: Cynomolgus Macaque Ovary
No full textDataset for histology images from the ovaries of Cynomolgus macaque (Macaca fascicularis). These images are associated with the Multispecies Ovary Tissue Histology Electronic Repository (MOTHER), an online repository (https://mother-db.org) of ovary tissue histology digital images, funded by NSF (DBI-2054061).
Sharing these histology images will facilitate comparative studies of
female reproductive strategies, enable the development of computational models to test hypotheses related to ovarian development and female reproduction, and serve as an educational resource, thereby reducing the use of animals in research.
See the README for an overview of the dataset, including naming conventions
Homeless Management Information System (HMIS) Usage
No full textThis dataset is derived from the Homeless Management Information System (HMIS), which is a government-run database to collect client-level data on housing and services to homeless individuals and families. This particular dataset counts the number of times each homeless individual (rows) attends each of the different services/projects (columns) available to them. Suggested dataset use is for unsupervised learning tasks
Replication Data for: Geospatial assessment of freshwater invasive species to inform turtle conservation and management
No full textOccurrence data for invasive bullfrog and crayfish species in Arizona.
Occurrence data obtained from Arizona Game and Fish Department reports and the public databases: iNaturalist Research-grade Observations,
iMapInvasives: NatureServe’s online data system supporting strategic invasive species management and Arizona State University Herpetology Collection (2020).
Methods for processing the data: Data was deduplicated by locality and date (if two points were from the same locality but on a different date, both were retained). The data is presented in UTM NAD83 12S coordinate system.
See README for information on variables and abbreviations.</p
WallStreetBets Subreddit dataset
No full textThis dataset is an extract of the subreddit /s/wallstreetbets from the website Reddit.com. It contains all of the non-deleted posts from all of January and February 2021. Suggested uses for this dataset is great for all types of natural language processing (NLP)
Microplastics Images dataset
No full textThis dataset is a collection of images of microplastics. Microplastics are small fragments of plastic (<5mm) that potentially have a negative impact on our health and the environment. Suggested dataset uses are for image classification, image segmentation, or any other image processing tasks.
ZIP file contains color images. Size: 34.1 MB Type: JPE