MODERNIZING DATA-DELIVERY TECHNOLOGIES Combining Data-User Feedback with User-Support Expertise for Successful Data Tools And Pivoting when Technology Changes! Digital Data Products: Two Key Questions ➊ What problem(s) need to be solved? ➋ How do users want to solve those problems? Unlocking the potential of data tools requires: understanding user needs (talking directly with data users); leveraging existing user support expertise; the pivoting unapologetically if user demands and tech developments shift. Why This Matters to You Elevate your potential to gather effective user feedback when developing digital data products and data-related services: • When resources or time are in short supply • That goes beyond “textbook” or “Google-search” research approaches used in ideal conditions • To see some cool, recently launched products produced by ICPSR that your patrons may have interest in using Before Starting Definitions User Testing: the process of collecting research data from real users while they are using a digital product whether a prototype or fully launched User: an individual that uses or has the propensity to use a digital product; includes the individuals who actually interact with the product as well as those directing/training users to interact with the product User Support: individuals who assist hundreds of users annually who are interacting with a product whether support is for general questions or to solve problems User Research: The Practicalities Purpose: Observe, log, and analyze user interactions with a product, noting successes, challenges, and failures in order to improve user experience on the front-end and content received in the back-office Challenges: • Finding & recruiting “real” users • Expense $$ and time intensive • Live user research is a lab experience; users often act differently in the wild! • Users represent one experience — their own! Is their experience unique or common — that is the question! Process: At-A-Glance 1st Step Define the problem What is the (user) problem(s) to solve? How will it help the producer of the product (it’s okay to help yourself!)? Hint: Key to success — include user support staff in all phases starting with problem definition. 2nd Step Define the user Who is the primary user? Secondary? Hint: Define demographically, experience levels (substantive, technological, methodological) 3rd Step Test, Research, Build, and, if needed, Pivot • Recruit for testing and reward ($) • Conduct research again and again and again • Invite user support to help interpret research Hint: Digital Products — Be prepared to pivot when new technology arrives (AI changes everything!) Real-life Examples from ICPSR Digital Data Product Releases Product Research Data Ecosystem TurboCurator Problem Depositors not often knowledgeable on creating Findable metadata efficiently Solution ICPSR’s TurboCurator — designed to semi-automate the process Pivot Technology-inspired: AI - ChatGPT Identified three key metadata areas (Title, Description, Key Words) • Depositor inputs general information about the study, dataset, or file • TurboCurator, powered in part by AI, outputs accepted formats for title, description, and controlled key words that depositor can cut/paste to describe the data deposit https://myumi.ch/AZwPe Product Research Data Ecosystem Explore Data Problem A need to “look into” the data to learn more about “what’s in there” before downloading it or analyzing it; make data more Accessible Solution ICPSR’s Explore Data Pivot User-inspired: Users advised against another statistical analysis tool; keep it simple https://myumi.ch/G4Gz1 Product Research Data Ecosystem Researcher Passport Authentication & Authorization System Problem A need for an updated authentication and authorization system to exit ICPSR from password management (increase security) and make access to restricted-use data less cumbersome Solution ICPSR’s Researcher Passport — launching in two phases: • Basic Passport — basic acco