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The MINDS group laboratory is well equipped for supporting numerous graduate students, running controlled human subject experiments, and conducting qualitative knowledge elicitations.

In our experimental laboratory space, we have 6 partitioned computer workstations which can be used for individual experimentation or to simulate the environment of a distributed team. Each workstation is equipped with a computer terminal, headphones to deliver training and/or isolate participants from environmental noise, and a partition that can be used to present instructional materials. In addition to the experimental computers, the laboratory space includes an area with two computers for the researcher to control the experiments and observe participants.

The other section of our facilities includes workstations for graduate students, as well as a large conference table with whiteboards that can be used for meetings, brainstorming sessions, or knowledge elicitation research. Additionally, this area includes a large screen display which has been used in more complex experimental research tasks focusing on common operational pictures.

Both areas of the lab have been used for numerous studies and research projects.



The NeoCITIES simulation is the primary research test bed used by the MINDS Group. The original NeoCITIES simulations were developed based on an ethnographic study and knowledge elicitation of emergency 911 dispatchers. Using the data and knowledge gained from these studies, the first iteration, NeoCITIES 1.0 was designed. In addition to furthering the understanding of team decision making in the context of emergency response, NeoCITIES 1.0 served as a platform to study intelligent group interfaces, information overload, and team communications. Based on the experiences with the first iteration, NeoCITIES 2.0 was developed with a focus on geo-collaborative and their impact on team collaboration.

The newest iteration of NeoCITIES (3.0) was built using Web 2.0 technologies and was designed as a more flexible research tool than the previous versions. The initial research using NeoCITIES 3.0 was focused on how Information Overload affects team performance and how interface artifacts can mitigate its effects. This version of NeoCITIES was later modified (to NeoCITIES 3.1) to study the effects of storytelling and reflexivity on situation awareness and team mental models. Of all the previous versions, NeoCITIES 3.1 was the most widely used, with over 500 participants in its 3-year timeframe.

While there have been several iterations of NeoCITIES throughout the years, it has for the most part remained the same. In NeoCITIES, teams consist of three players, representing Fire, Police and HazMat dispatch officers. Each player has a set of unique resources with different abilities, and are responsible for identifying events, and allocating appropriate resources to solve the events. While this platform has served as an excellent test-bed for numerous research projects, its overall simplicity limits our abilities to use it to answer questions about more complex collaborations and environments.

Similar to the development of the original NeoCITIES, the NETS platform was designed based on interviews and observations of cyber security experts. The overall architecture of NETS is built upon the same general principles of NeoCITIES, resource allocation and situation assessment, but has been expanded to better support more complex decision making and richer scenario definitions.


NETS-DART is an offshoot of idsNETS built to study the effect of a cognitive-aid on attention-allocation in a dual-task context. DART is the acronym for Dual-Task Attention Research Testbed. The scaled-world task emulates a decision-making task involving categorizing cyber-threats in an organizational network. For the purpose of studying attention-allocation, it presents network locations through primary and secondary layers that represent primary and secondary sub-tasks. The Task-State Overview provides a comparison of severity between primary and secondary tasks that primarily guides human selective attention. The simulation can be adapted for future research in cyber-security, attention-allocation, multitasking or workload.