(Illustrated above) A financial trader uploads a list of 175 securities in order to search his firm’s expansive holdings. After quickly scanning the available quantities of each item in the list, he then searches within the results to find out what proportion of current holdings for each security has been untouched for over a week.

An architect receives a call from a construction site about a flooring installation process. She uses her building modeling application to search for any project specification content that references “flooring” or “adhesive” in the “northern foyer.” She views the results both in a table and within a 3D wireframe of the structure.

A scientist users her analysis application to search a massive database shared by several cooperating clinical research labs. She is looking for only those clinical data that contain both a certain genetic marker and treatment method.

What types of information retrieval and discovery goals do targeted individuals currently have within the work practices that your team is striving to mediate?

How do these goals fit within the narrative arcs of certain tasks and larger activities?

How variable are targeted workers’ information seeking approaches? What commonalities might your team identify across these behaviors?

What expectations for search functionality have workers developed from using other computing tools?

What larger technology trends and advanced analogies to other domains could valuably inform your team’s ideation around relevant search functionalities?

What inherent data attributes, such as the characteristics of interaction objects, could potentially be searched on in your application concepts?

Where might open, free text searching of these metadata support workers’ existing information seeking goals?

How might the adoption of new computing options into targeted work practices create volumes of content that could benefit from more specific information seeking methods?

What tailored and specialized search functionality might your team envision for workers’ information seeking goals? When might such “advanced” searching represent the norm, not the exception?

What novel representations of search results might your team sketch with the goal of allowing workers to meet their information retrieval or exploration goals more directly and accurately?

How could the underlying algorithms of your search concepts create content biases that could match workers’ information seeking mindsets?

Do you have enough information to usefully answer these and other envisioning questions? What additional research, problem space models, and design concepting could valuably inform your team’s application envisioning efforts?