Welcome to the website for DAIS ITA - The Distributed Analytics and Information Science International Technology Alliance. You can read more about DAIS ITA on wikipedia and you can view all of our publications, structure and membership on the DAIS ITA science library. You can also visit the previous project's (NIS ITA) science library.
News
- Solving the Hard Science for Future Coalitions (Signal-Digital, Feb 2017)
- US-UK DAIS ITA (RISS Group - Imperial College Lodon, 18th Dec 2016)
- Bertino part of collaboration between U.S., U.K. governments, industry and academia (Purdue Computer Science, 12th Dec 2016)
- Meeting of 'big data' alliance (Cardiff University, 5th Dec 2016)
- New International Alliance on Distributed “Big Data” Analytics (Crime and Security Research Institute, Cardiff University, 14th Nov 2016)
- Felmlee part of new collaboration with U.S., UK governments, industry and academia (PennState Social Science Research Institute, 1st Nov 2016)
- Army Research Lab, UK MoD Form Distributed Analytics & Info Science Alliance (ARL, 26th Sept 2016)
- World class research alliance in distributed analytics and information science (IBM, 26th Oct 2016)
- Army Lab Announces New Alliance with UK Ministry of Defence (science.dodlive.mil, 1st Oct 2016)
- ARL, UK collaboration: Distributed analytics will aid coalition forces (DefenseSystems.com, 28th Sep 2016)
Logging in
If you are a member of the DAIS consortium you can login using the "Log in with BlueID" button to your left. If you need to create a new account please follow the instructions below:
- Click on “Log in with BlueID” on dais-ita.org. This will redirect you to an IBMid account login page.
- If you have already registered an IBMid simple enter the userid and password in the normal way to login.
- If you have not yet created an IBMid then click “Create an IBMid” to do so.
- Enter your email address, first name and last name and choose a password.
- Check your email for a confirmation code required to complete the process and enter the code to complete the process and login.