Metrics
103,277 Downloads

Share, discover, and cite research data from Arizona State University.

The ASU Research Data Repository is a platform for ASU-affiliated researchers to share, preserve, and publish research data in a way that ensures long-term accessibility, usability, and citation. Our team supports researchers in preparing high-quality, well-documented datasets that comply with funder and publisher data sharing requirements.

Curated by ASU Library data professionals, the repository enables global discovery of research data through permanent digital identifiers (DOIs). It is powered by the open-source Dataverse application developed by Harvard University and complements the KEEP Institutional Repository to support the full range of ASU research outputs.

Ready to share your data? Visit the ASU Research Data Repository home to learn more and request a consultation.

Featured Dataverses

In order to use this feature you must have at least one published or linked dataverse.

Publish Dataverse

Are you sure you want to publish your dataverse? Once you do so it must remain published.

Publish Dataverse

This dataverse cannot be published because the dataverse it is in has not been published.

Delete Dataverse

Are you sure you want to delete your dataverse? You cannot undelete this dataverse.

Advanced Search

12,001 to 12,010 of 12,654 Results
Tabular Data - 11.6 MB - 9 Variables, 296460 Observations - UNF:6:eZlkMnxUITJt6PaTvKGnVQ==
Ants' trajectories in the video of post-dropping alarmed seed ants.
Tabular Data - 13.3 MB - 9 Variables, 327570 Observations - UNF:6:enoEDa2Zla6DH0ZKfM41DA==
Ants' trajectories in the video of pre-dropping alarmed seed ants.
MPEG-4 Video - 60.9 MB - MD5: a6d05e07ae1f292b67584f600901e7b2
Animations for the estimates of ants' alarm strength from the ML model, and the propagation network. (Left) A distribution of alarmed and unalarmed ants over time (blue bars: the number of unalarmed ants in each bin (Alarm strength < 0.749); pink bars: the number of alarmed ants in each bin (Alarm strength >= 0.749)); (Middle) An animation by overl...
Tabular Data - 3.6 MB - 9 Variables, 64260 Observations - UNF:6:Swx+5/1iaRALmSwzFtUNNQ==
Training dataset for Randomforest machine learning regression model.
MS Excel Spreadsheet - 1.6 MB - MD5: f8e48d01b8711ee2e1aedb2f30cc2ceb
Tabular Data - 395.5 KB - 166 Variables, 919 Observations - UNF:6:DDw+hW9QfNjFMoeIYVlcbg==
Add Data

Log in to create a dataverse or add a dataset.

Share Dataverse

Share this dataverse on your favorite social media networks.

Link Dataverse
Reset Modifications

Are you sure you want to reset the selected metadata fields? If you do this, any customizations (hidden, required, optional) you have done will no longer appear.