Sessions

2023 IA Conference

April 1, 2023

You found a profession that you love. Maybe love is too strong for you, maybe you just enjoy it. You've learned, you've grown, you've arrived. And then, CHANGE.

You get a new boss, and they don't like the way things are done. Or you find out from a peer that the best practices have changed in light of new regulations. Perhaps a global pandemic suddenly changes the way the world works. What do you do? First and foremost, as recommended by the Hitchhiker's Guide to the Galaxy, DON'T PANIC.

As humans, we're wired to have a fear of uncertainty. So when we're doing what we love and we're comfortable, it sometimes takes too long to notice when we're not loving it as much anymore.

When I found Information Architecture, I knew I'd found the right fit for me. But it's taken a lot of resilience, self-learning and willingness to change to be able to go from "Entry level” to "Seasoned Professional”. Join me to learn how.

Sessions

2023 IA Conference

April 1, 2023

One primary tension in taxonomy construction is between best practices (as defined by various taxonomy standards) and practical (business) requirements.

That is: the tension is between categorization according to *what things are* versus *where people will look for them*.

How can we balance or reconcile these priorities? Can we model our way out of them? And what are the options?

This issue is paramount in Topic taxonomies; Topic or Subject taxonomies are very common and present specific modeling challenges.

People are used to navigating topic-oriented structures. It is common sense to put things where people will find them; however, that does not mean that it's also Good Taxonomy Practice.

In this talk, I'll address the difference between Concepts and Topics, outline some of the challenges in building these types of taxonomies, and offer a number of practical solutions for addressing them.

Sessions

2023 IA Conference

March 31, 2023

Driving human-centered change requires resilience, efficiency, energy. In this talk, senior UX research leader, Alesha Arp, will share how to maintain resilience, employ effective collaboration techniques, and recharge your energy to catalyze change.

Sessions

2023 IA Conference

March 31, 2023

When the pandemic caused the Washington Metro to make an abrupt shift to remote work, the focus of a project to eliminate legacy paper records and relocate to much smaller office buildings shifted to helping a bureaucracy which had no culture of remote work be able to work remotely, literally overnight. This presentation discusses what we learned about taxonomy while working on the railroad, and how we helped Metro begin their digital transformation journey. For Metro it was all about location, specifically the Metro map. What we learned, it turns out, is that there are different maps—one for passengers and a multi-layered map that Metro uses internally, for many operational purposes.

Sessions

2023 IA Conference

March 30, 2023

Enterprise software systems create and store massive amounts of data created by the processes carried out within them. But, that data isn't automatically useful information for assessing those processes. System data represents the translation of the reality of the processes as understood and enacted by people into the structure of the system. What data is captured and how it's structured represents what happened in the system, but the relationship of that data to reality outside the system is not always clear. To be useful for answering questions about what's happening in the real world, system data has to be translated back into an information architecture that gives it coherent meaning in terms of the actual workflows, intentions, and concerns of the people managing and doing the work.

This talk is a case study of doing this work to structure analytic data from a new Library Services Platform to be meaningful information about the physical collections and fulfillment processes at a large academic library. I'll talk about what makes data be information, and then show how created an architecture to make our data meaningful information for assessing our processes and to support ""informed"" decision making.

I'll talk about:

  • Working with those who manage and perform the work to create diagrams that model how the parts of the real world workflows create system data
  • Exploring data with pivot tables and Tableau to test assumptions and find edge cases that need clarification
  • Documenting the differences that 'make a difference' and sharing information back to those doing and managing the processes"