Posts Tagged ‘Taxonomies’
AI Still Needs a Map
Artificial intelligence (AI) has changed how we search for information. We can ask questions conversationally, explore unfamiliar topics and receive answers without knowing the exact keywords. But that convenience does not eliminate the need to organize information. It makes a strong foundation even more valuable. This important topic came to us from LinkedIn inn their…
Read MoreTrick, Treat, and Taxonomy: Order in the Candy Chaos
Dump a Halloween candy bucket onto the kitchen table and watch what happens. Someone sorts by chocolate versus everything else. Someone separates the gummies. Someone quietly relocates every peanut butter cup into a private collection. Congratulations. You have entered the world of taxonomy. The tiny pirate guarding the chocolate understands information architecture. This fun but…
Read MoreFindability in the Age of AI Starts with a Strong Taxonomy
Artificial intelligence (AI) can search vast collections of information in seconds, interpret natural language and surface connections people might otherwise miss. But even the smartest AI tools can struggle when an organization’s information is inconsistent, poorly described or difficult to access. This interesting topic came from Hedden Information Management in their article, “Generative AI and…
Read MoreMonsters, Metadata and the Magic of Findability
As a cinephile, I appreciate a horror mash-up: haunted houses, ancient curses and people who apparently cannot recognize that the basement is a terrible idea. Add taxonomy to the mix and suddenly my love of films meets my appreciation for organized information. Truly, a monster worth creating. This fun but important topic came to us…
Read MoreAI Didn’t Replace Taxonomies – It Made Them More Useful
Every few years, a new technology arrives and someone declares an older discipline dead. With artificial intelligence (AI), taxonomies have become a frequent target. Why spend time organizing information into agreed-upon categories when a model can read a document, identify its subject and answer a question in seconds? It is a reasonable question. AI can…
Read MoreThe More Technology Changes, the More Findability Matters
Over the past decade, emerging technologies have transformed nearly every aspect of how we create, manage and access information. Artificial intelligence (AI), machine learning, cloud computing, automation and natural language processing have shifted from futuristic concepts to everyday business tools. Entire industries have been rebuilt around predictive analytics, generative AI and massive-scale data processing. Information…
Read MoreBuilding a Data Culture People Will Actually Use
Let’s be honest. Most people do not wake up excited about data governance. No one is lighting candles around a beautifully organized spreadsheet whispering, “Ah yes, metadata.” But organizations that treat data seriously almost always function better, move faster and make smarter decisions. This important topic came to us from CIO in their article, “What…
Read MoreRecords Retention in the Age of AI: Why Taxonomy Still Reigns Supreme
In a world increasingly shaped by artificial intelligence (AI), records retention has moved from back-office obligation to strategic necessity. AI systems thrive on data, but not just any data—relevant, accurate, well-structured data. Without intentional retention policies, organizations risk feeding their AI outdated, redundant or even harmful information, leading to flawed outputs and questionable decisions. This…
Read MoreRetrieval Augmented Generation and the Role of Taxonomies in AI
Retrieval Augmented Generation (RAG), is becoming an important approach in the development of reliable artificial intelligence (AI) systems. While large language models are powerful tools for generating natural language responses, they are often limited by the information contained in their training data. RAG improves this process by connecting language models with external knowledge sources so…
Read MoreWhy Controlled Vocabularies and Taxonomies Matter for Automated Indexing
As organizations increasingly rely on machine assisted and fully automated indexing, the structure behind their information becomes just as important as the content itself. Automated systems are fast and scalable, but they are only as effective as the language frameworks guiding them. Without a controlled vocabulary or a full taxonomy in place, indexing efforts risk…
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