Factor

“What do you want to be when you grow up?” It’s funny how many of us have no hesitation at asking kids that question when I’m sure a large number of us adults probably don’t have an answer as good as the kids have. I’ve been thinking about this field of Information Architecture that I work in and my personal journey to where I am now. I asked myself "How do I know that this work is right for me?” After a little bit of pondering, I think I have my answer: when I encounter something new in Information Architecture, I immediately want to know more about it. It feels like my interest builds or expands on itself. Some examples: I forget when and where I learned about the concepts of the Semantic Web and Linked Open Data, but when I heard about them I thought it was a fascinating idea and wanted to know more about it. Ontologies: I gotta check this out! Generative AI: I need to find out more about how they work. Don’t get me wrong, the day-to-day work can sometimes be arduous and dull. I spend a lot of time staring into spreadsheets, opening request tickets, and replying to emails. But at its best, the day-to-day work is also doing detective work, trying to create something for others that will last after you, and helping people. If you’re feeling a bit burnt out or overwhelmed, it might be a refreshing little break to take a minute and ponder over what it is that you enjoy about the field you’re in and/or the work you do. I’d love to see your responses if you want to share them. I hope all of you have a great day today. #Taxonomy #InformationGovernance #FactorFriday

AI is great at processing data, but ontologies and taxonomies are what shape its understanding of relationships. Factor's Erik Lee is back on Talk Tech to explore how these frameworks drive AI’s reasoning, decision-making, and real-world applications. A must-listen for anyone navigating enterprise #datastrategy. ????

One of the best things about conferences is getting to learn in person from people I normally only see on the other side of a webcam. Connor Cantrell and Factor continue to show how innovative they can be when it comes to taxonomies.

"Digitization does not equal access… but digitization, combined with carefully crafted metadata, can significantly enhance end-user access." —Murtha Baca, Introduction to Metadata #HumanFactor #Metadata #Digitization #UX

If teams don’t speak the same language, their data won’t either. Every department has its own way of talking about the business. Finance, sales, operations, and marketing might all use different terms for the same concept. Over time, these inconsistencies get baked into systems, reports, and dashboards, creating a fragmented data environment that no one fully trusts. This is exactly how data silos form. When terminology isn’t aligned, neither are insights. One team’s “customer” might exclude certain segments another team considers critical. A “completed order” in one system might not match another’s definition. This means confusion, redundant work, and, at worst, missed opportunities and lost revenue. Standardizing business language is one of the most effective ways to prevent data silos before they start. A shared taxonomy (a structured, agreed-upon set of terms) ensures data is truly interoperable so you can use that information to make better decisions. Does your organization have a shared business language? If not, your data strategy might be missing a foundational piece. ?? Read more about data silos and decision-making: https://lnkd.in/d_sjq73P #DataSilos #Taxonomy101 #EnterpriseTaxonomy #InformationStrategy

Knowledge graphs are often wrapped in layers of technical jargon. But you don’t need to be a data scientist to understand and apply KGs in your work! That’s why Factor’s Bob Kasenchak and John Tulinsky are leading Introduction to Knowledge Graphs for IA Practitioners at #IAC25. This workshop was designed specifically for IAs who want to cut through the hype, grasp the fundamentals, and explore how KGs can enhance their practice. What you’ll gain: ?? A clear understanding of what Knowledge Graphs are and how they connect to taxonomies and ontologies ?? Practical insights into how KGs support AI, analytics, and discovery ?? A framework to think about KGs in your own work (without needing to code!) ?? A chance to move beyond theory with interactive activities that make concepts click If you're looking for a dense four-hour lecture, this workshop isn't for you. We've combined engaging presentations with hands-on exercises designed to make the material really stick. The session will focus on real-world applications, helping IAs see past tech buzzwords and understand how solid information foundations make everything—yes, even AI—work better. If you've been curious about KGs but weren't sure where to start, this is your chance! Join Bob and John at IAC and leave with the knowledge and confidence to bring KGs into your IA practice. Register here: https://lnkd.in/gqQ9H2qk #InformationArchitecture #KnowledgeGraphs #DataStrategy

AI isn't magic, it's math. And if your employees can't make sense of your data, AI won't be able to either. This video from Chris Walker is a great reminder of how enterprises need to be thinking about #AIEnablement in 2025.

Information chaos is a growth killer. Without structured, reliable data, decision-making slows, customers receive inconsistent experiences, and employees waste time searching for what they need. A strong information foundation turns raw data into a strategic asset. Here’s what that looks like: ???Taxonomies – Organize information in a way that makes sense to users, so they can find what they need faster. ????Metadata – Give data context to improve search, reporting, and analytics. ???User Understanding – Build systems that people can (and want to) use. ???Data Governance – Define ownership, maintenance, and compliance to keep information reliable. ???Organizational Alignment – Make information management a business-wide priority, not just an IT task. Without these elements, growth leads to inefficiency instead of progress. Get them right, and your business moves with clarity, speed, and confidence. What’s been your biggest challenge in structuring information for scale? Tell us in the comments. #InformationArchitecture #EnterpriseData #DataStrategy #DataGovernance #EnterpriseIA

AI can’t fix messy, unstructured, or inaccessible information. If anything, it just makes the problem worse. Join Factor’s Gary Carlson as he breaks down what it really takes to make AI work for your business. No hype, just expert insights on building AI-ready information foundations. #AIEnablement #EnterpriseAI #InformationFoundations #Webinar

Is your organization stuck in the ‘wild west’ of taxonomy? Where everyone creates their own terms, and structure is an afterthought? Moving to a governed model doesn’t mean enforcing rigid rules or red tape overnight. The key is gradual buy-in, not brute force. Here’s how to make the shift without resistance: ? Start with small wins. Quick improvements, like automated tagging, AI-driven metadata recommendations, or reducing redundant content searches, show immediate value. ? Make governance the solution, not the obstacle. Many resist governance because they see it as restrictive. Flip the narrative: A governed model eliminates friction, making workflows smoother and content more discoverable. ? Build momentum through socialization. People support what they help create. Engage teams early, highlight their wins, and frame governance as a competitive advantage, not a compliance burden. ? Showcase ROI in real terms. Strong taxonomy governance reduces rework, increases AI accuracy, and cuts down on wasted effort. The less time spent searching, fixing, and reinventing, the more time teams have for strategic work. Governance isn't about control. It's about creating a structure that scales. The shift from chaos to governance doesn’t happen overnight, but with the right approach, it can happen without a fight. Learn more about creating a governance strategy that's built to last in our latest webinar replay: https://lnkd.in/gRSATjbj #Taxonomy #InformationGovernance #EnterpriseData