Session type: 20 minute talk

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"

Companies, governments and humanitarian entities are capturing, storing and sharing an ever increasing volume of identity data, much of it pertaining to "third party" individuals who may never interact directly with the databases where their data is stored. While many countries have enacted legislation to establish baseline safety protocols for protecting personal data, and online privacy and security standards like GDPR are becoming more ubiquitous, the reality is that protecting data about people remains a challenging and underappreciated area of risk for most organizations, particularly when those individuals have no awareness or agency over their data. This talk by Timothy Quinn, founder of the Dark Data Project (darkdataproject.org), discusses the design, storage, management and safe sharing of "non-user” data as part of a greater "non-user experience (N/UX)”, with a particular focus on the challenges of protecting the identities of vulnerable populations.

We gain resilience from each other! In just 20 minutes, you'll learn how to facilitate strong collaboration between CS and UX leaders on your teams. Goodwin brings over 15 years of experience in UX and is passionate about CS as a critical part of the UX practice. By learning each other's "side of the story”, UX and CS can see how they're really both sides of the same coin and how to partner to successfully deliver outstanding customer experiences.