I helped a university in the West Coast (US) to identify spaces for the users of its new interdisciplinary building for computing and data science. 

Through a series of themed User Experience workshops with leadership, department heads, faculty, institute directors, and students, I, along with the rest of the strategy team, probed on space needs and associated activities related to the three key themes of Teaching & Learning, Research & Workspace, and Data Science Commons. Our workshop series were attended by more than 70+ participants and involved the following activities:

• Semantic Differentials - probed on high-level vision for the space based on contrasting concepts located at two ends of the spectrum 

• Space Type Voting - probed on preferences of space types that best support needs 

• Percentage Voting - probed on the ideal combination of a specific space type that best supports activities (e.g. 100-person lecture meeting hall vs. multiple 6-person meeting rooms)  

The findings of this workshop led to an initial list of key spaces and design principles that served as the basis for the final recommendation of 30 different combinations of space types that total 249,000 ASF* and accommodates more than 1,765 future building occupants.