Intelligence and Security Informatics Data Sets
Data Infrastructure Building Blocks for ISI. A Project of the University of Arizona (NSF #ACI-1443019), Drexel University,
University of Virginia, University of Texas at Dallas, and University of Utah
Our quarterly newsletter will keep you updated on the datasets that are added each quarter and other changes to the DIBBs-ISI portal.
Contact the AZSecure-data project manager with your suggestions and ideas on data we you would like to see added to the collection, a data set you have to offer, or ideas on functionality you would like to see added to this portal. We would also like to know if you had any difficulty in downloading the data currently available, and if you have opinions on the format or other issues related to how we are making the data available.
Comments, questions, and suggestions may be emailed directly to the project manager and webmaster at firstname.lastname@example.org.
Written correspondence may be directed to the following address:
AI Lab - MIS Dept.
ATTN: Hsinchun Chen, re AZSecure-data
1130 E. Helen Street - MCCL 430
Tucson AZ 85721 US
This project is funded in part with a grant from the National Science Foundation (NSF #ACI-1443019).
We are also grateful for support from the UA Management Information Systems Department and the Eller College of Management.
Project Team Members:
- Dr. Hsinchun Chen, UA, PI
- Dr. Ahmed Abbasi, U. Virginia, Co-PI
- Dr. Bhavani Thuraisingham, UTD, Co-PI
- Dr. Chris Yang, Drexel, Co-PI
- Dr. Paul Hu, U. Utah, Co-PI
This NSF-funded Data Infrastructure Building Blocks project is intended to address a large gap in the availability of open source research data for researchers in ISI. The University of Arizona Artificial Intelligence Lab and its partners, the University of Virginia, the University of Texas at Dallas, Drexel University, and the University of Utah, were awarded $1,499,531 for a three-year Pilot Demonstration Project to make available a significant archive of data and analysis tools to serve the ISI community.
The primary focus of the AZSecure-data project is on data collection and management, access, and data analysis. The goal is to identify and collect data that will be of the highest interest to the research community and providing the data to the community in the easiest, most useful, and most direct way possible.
Read more about the project plan and activities on the DIBBs project page on the Artificial Intelligence Lab's website at https://ai.arizona.edu/research/dibbs.