> [!Note] Note > In this page, I'm trying to work out how to speak about IA in terms that most people will understand. I'm trying to tease out the fundamental things that are true of the IA approach to problem solving and systems thinking. Some of this is my own writing, and I've tried to indicate where I've quoted from others. --- I organize large-scale information systems in order to make information findable by end users. Kind of like a digital librarian. In the course of my work, I have accidentally become a product manager, because I found it was the best way for me to translate a strategic vision into something tangible. --- In order to be effective at arranging information, IAs need to be good at a number of things. First and foremost, we need to be good at learning new things. Information environments are complex, and the diversity of subjects one might encounter is vast. But by asking the right questions and considering multiple points of view, an IA can suss out the important things to know about any topic area. As Sarah Barrett says, IAs are experts at *becoming* experts. IAs think through things. We have the skills and tools to understand complex spaces and help others organize information and make decisions. In the process of learning, we will reflect back what we've discovered to partners and stakeholders. These can sometimes be difficult conversations, because we are often peeling back layers of assumptions and uncovering ideas that have been ignored or not thought about. To get clarity around a subject requires making decisions, and sometimes making those decisions may shift power structures or call for work to be done. As a result, IAs learn to use empathy and patience, and develop communication skills to help urge teams towards consensus. And in going through this process, IAs are both examining details of a system at multiple levels, as well as building up a picture of the system as a whole. In doing this, we are able to work holistically to address information problems at the data level and at the user interaction level, and at many layers in between. --- Alright, think of information architecture as the blueprint or structure behind how information is organized, presented, and navigated in digital spaces like websites, apps, or databases.  Imagine you're designing a website for a company. Information architecture involves determining what content will be included, how it will be categorized, and how users will navigate through it to find what they need. It's about creating a logical and intuitive framework that makes it easy for users to access information quickly and efficiently. Information architecture considers things like menu structures, navigation paths, search functionalities, and content organization. The goal is to create a user-friendly experience where people can easily find the information they're looking for without feeling overwhelmed or lost. So, essentially, information architecture is about designing the backbone of digital platforms to ensure that information is structured in a way that makes sense and is easy to access for users. --- I typically work in the context of making business content findable and useful to customers and internal users, but my skill set can be applied to a wide variety of problem spaces. With a vision in place, I create the space for teams to execute on the solutions using soft skills and a finely-honed sense of how to communicate complex information to diverse audiences. My special sauce is my knowledge of a variety of techniques and practices from the science of information management and user experience design, which helps me both develop and execute solutions. How I work - Understand the current state of play - I start any endeavor by understanding the themes and boundaries of the space. Who are the major and minor players? What is the stated goal? What are the unstated goals? How do things work (or not work) now? - Understand context - Where does this project fit into the efforts of the larger team, organization, industry, and society? What forces are affecting this effort in positive and negative ways? - Learn the business - What are the business goals? What are the needs and wishes of leaders at every level of the organization? - Learn the players - I want to understand not just the people directly involved, but the people who are tangentially involved, the ones who will be impacted by the product, and those who are producing similar work. Comparing and contrasting these different roles helps enlighten my team's work and creates a network of allies and partners. - Model the space - I draw models of everything not only for my own understanding but so that I can communicate my understanding to others and tease out where I'm on target and where I'm off base. - Envision what's next - From the established baseline of how things work today, I identify a series of steps to move from the current state to the optimum end result. --- Data / information hygiene Knowledge management --- From https://jarango.com/2024/04/14/information-architects-must-embrace-ai/ >Information architects are well-positioned to help steer these conversations in positive directions. After all, we are the language systems people — i.e., the team members who look after conceptual integrity across contexts. >We should do more of this: engage with the technology to help define principles and processes for its productive use --- [[2024-04-11 07 Achievable Automation, Soon! Play-Testing Your Team’s AI-iest Ambitions for Proof and Profit Through Pre-Personalization]] >IAs should own product discovery. **Your seat at the AI table is labeled “data quality”.** > Also: IA can reduce friction in the UX and keep site content to a manageable level. --- [[2024-04-11 11 How to Dive into a New Domain and Get Oriented Quickly]] >IAs work with wide ranging groups to create cohesion. Our systematic design brings in information from all corners of an organization. There’s a lot of work around getting familiar with each domain and making sense of it. --- [[2024-04-11 09 IA Fast Track to Search-Focused AI Solutions]] [[The value of metadata]] --- [[2024-04-12 03 Structured Content in the Age of AI- The Ticket to the Promised Land]] >“It will take people with a 'content science' background to make the content intelligent.” Michael Iantosca Senior Director of Content Platforms and Knowledge Engineering, Avalara > >“The fundamental nature of information and its relationship to human cognition, experience, and society” -ChatGPT in response to 'What do IAs care about?" --- [[2024-04-12 09 Data Design – a New Paradigm for Building Holistic Personalization Experiences]] >Data design = UX design for the data users depend on. > >Personalization requires well-designed data. > >What are data designers designing? >- data collection, storage and display >- Data solutions and systems >- Shared taxonomy data for diverse use cases >Data design expertise is multi-disciplinary. Includes information science, product management, UX design, data engineering, data analytics. --- [[2024-04-13 04 Bridging the Gap - IA as an Essential Part of Domain Driven Design]] >Effectively, we are experts in _becoming_ experts. >We’re good at asking questions >We elicit mental models and assumptions. > >You need IA wherever complexity is being lost. > >We take things up and down the ladder of abstraction. > >We’re great at exploratory domain-driven design. --- [Reinventing the Wheel: On Generative AI for \[Poor\] Search and Knowledge Management](https://www.linkedin.com/pulse/reinventing-wheel-generative-ai-poor-search-knowledge-bob-kasenchak-9vxec/?trackingId=7ak50TNFiJT3MTbvHr3bcA%3D%3D) >It is hard work to reduce loss, in the context of understanding what is relevant information, if you do not provide complete documents; distillation of facts, limitations of interfaces, and the variable context of users are among the issues to navigate. > >This work is done, every day, by information architects. --- [Fractional Information Architecture — Seneb Consulting](https://www.seneb.com/fractional-information-architect) ---