Fran Alexander: Democratizing Taxonomy Practice – Episode 202

Content Strategy Insights

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Fran Alexander There is always more taxonomy work to be done than there are practitioners to do it. Fran Alexander's solution to this imbalance is to democratize taxonomy practice. Fran's work actually spans the full range of semantic practices, from simple term lists to taxonomies, thesauruses, and ontologies and knowledge graphs. Wherever she's working in this span of activities, she's always happy to bring other practitioners along with her. We talked about: the transition in the taxonomy world from building taxonomies to help machines understand humans to building taxonomies to help humans understand machines he the rise of AI and LLMs has highlighted the importance of well-structured knowledge and good semantic layers the hierarchical progression of knowledge organization from simple lists to full-blown ontologies how her efforts to democratize taxonomy and semantic practice are jump-started by humans' innate organizing schemes how the fact that there is always more semantic work to be done than there are taxonomists drives the need to democratize the craft how to evaluate the effectiveness of a taxonomy fascinating taxonomic edge cases like boundary objects that highlight the artistic aspects of taxonomy science how an ontology "is a map of important ideas" two main types of taxonomies - descriptive taxonomies and operational taxonomies how to assess whether a taxonomy is doing the work you need it to typical uses cases for a taxonomy: tagging, indexing, discovery, retrieval, recommendation systems, personalization, etc. some advanced taxonomy practices that enterprises could benefit from the connections between taxonomies, ontologies, and knowledge graphs the Taxonomy Bootcamp London Bite-sized Taxonomy Boot Camp series Fran's bio Fran started her career as a writer and editor of dictionaries and thesauruses in the UK, and, as technology evolved, she specialised in information architecture, search systems, and digital archives, and more recently, the use of semantics in knowledge graphs and LLM applications. Having worked on reference publications including the Collins English Dictionary, and as Taxonomy Manager for the BBC Archive, she now lives in Montreal, Canada, and is the Senior Taxonomist for Expedia Group. She was Taxonomy Bootcamp London's Taxonomy Practitioner of the Year 2023. Connect with Fran online LinkedIn Resource mentioned in this interview Bite-sized Taxonomy Boot Camp Video Here’s the video version of our conversation: https://youtu.be/SoxApp_myeg Podcast intro transcript This is the Content Strategy Insights podcast, episode number 202. As we write our shopping lists and organize our thoughts, we all practice taxonomy and think semantically every day. Some of us get to do these practices professionally. Fran Alexander is a taxonomist based in Montreal. She's also the reigning Taxonomy Bootcamp Practitioner of the Year. As she's realized that there will always be more semantic work to be done than there are trained practitioners, she added "democratizing taxonomy" to her to-do list. Interview transcript Larry: Hi, everyone. Welcome to episode number 202 of the Content Strategy Insights podcast. I am really delighted today to welcome to the show Fran Alexander. Fran is a taxonomist based in Montreal, in Canada. She's also the reigning Taxonomy Boot Camp Practitioner of the Year, so she's a rock star in the taxonomy world. Welcome, Fran. Tell the folks a little bit more about what you're up to these days. Fran: Well, thanks, Larry. It's a pleasure to be here. It's a pleasure to talk to you about taxonomies and democratizing taxonomies. One thing that's top of mind for me, and it gives a bit of context, I think to the work that I've done and the changes that I've seen over, well, the last couple of decades really, is that we used to build taxonomies to help machines understand humans. Now we're building taxonomies to help humans understand machines. We've done a lot of foundational work to set up intelligent systems and organize our concepts and our context to create knowledge basis, knowledge graphs and so on. Now AI is coming in and is so elaborate and sophisticated. We, as humans, are having to step back and try and understand and explain and work with the complexities of that world. There's really been a huge shift and it's fascinating. It makes it a really great field to be working in. Larry: The way you just said that, is business booming these days for the taxonomy folks? Has AI been- Fran: Absolutely. Larry: Yeah, I would assume so. Fran: Absolutely. There's a lot of excitement obviously over the last few years with the rise of AI and LLMs, but that's also brought into focus the importance of knowledge and the importance of well-structured knowledge and the importance of really good semantic layers is what people are talking about now to support those AI applications and to support those LLMs. If you've got really good, well-described knowledge in a way that machines can process and understand, then that artificial intelligence, those applications that sit over the top are so much more effective and accurate and explainable and so on. I really feel that taxonomy and semantics are going to go in and out of the spotlight, but there's huge, huge interest at the moment. It really is a boom time for taxonomy and taxonomists. Larry: I was at the semantics conference a couple of weeks ago in Amsterdam and there was palpable excitement and even giddiness about the need for semantic help. A lot of it goes to what you were just saying about AI and the need to go and that progression you described of well, from AI and LLMs and then that illustrating the importance for well-structured knowledge. That's almost like not the, when you look at a maturity model or a, I don't know what you call it, but that evolution of ways to manage descriptions of categorizations and descriptions of things. Can you talk a little bit about like we talked before, we went on the air a little bit about everything from folksonomies to a full-blown ontology, but there's lots of stuff in between too. Fran: Sure, absolutely. Well, it's interesting because actually, some of the earliest forms of writing known to history are lists and catalogs. That's like Hittite tablets and Sumerian King List and so on, and they're kind of inventories, stock lists. Those were the first things that people, at least as far as we know, those were the first things that people were writing down. That really is the first point of knowledge organization is that you make a list, and we're all very, very familiar with lists and how useful they are, but a list is your first step. As you get more and more information, once your list starts to get bigger, you need to divide your list up to make it usable and manageable into categories and subcategories. At that point, you're starting to build a taxonomy. Fran: Then you need to go one step further as you get more and more content that you want to understand and manage. You want to move away from a simple monohierarchical taxonomy to start building graphs and have concepts that can belong in more than one subcategory on your list and at that point, you're starting to build a graph. Taxonomy is obviously focused on the hierarchy, broader and narrow it, to allow you to zoom in and out and find things through that kind of browse mechanism. It's the fundamentals of taxonomy. Then you start to want to add in synonyms and related concepts, so you start to build up a thesaurus, and thesauruses are where you have all the different words for the same concept. Fran: That's a very fundamental point in semantics, it's why we need semantics because we have so many different words for the same thing and we need to organize that. Then ontologies come in as you start to define those relationships. How do your lists taxonomies relate to each other? You start to put in some logical rules and your ontology then starts to build up your whole worldview and your perspective. At that point, when you've got your ontology and you start to have the actual data that you're working with, the actual information, you've got a knowledge graph. That is something that you then need to support your LLMs and work with your LLMs to get really good results. That's how you evolve from starting off with lists and tags and labels and build up through to the sophisticated knowledge ecosystems that we're working with now. Larry: As you set out that escalation of organizations schemes, I realize that I'm reminded of something else we talked about earlier, this notion that we're all already doing a lot of this stuff already. You just happen to do it professionally and have very precise and ISO standards and stuff that you're working to, but everybody does shopping lists and then goes, "Well, I need to organize it by aisle," or whatever. Can you talk a little bit about, because the whole theme of this conversation is the democratization and that's like pre-democratization. People are already poised for this. Assuming we have a slam dunk here in terms of democratizing this. Fran: Yeah, absolutely. We are all taxonomists kind of all the time. One example that I like to use is supermarkets, mentioning shopping lists, the way that a supermarket is organized, that's effectively a taxonomy. You've got the dairy section and then within the dairy section you've got the milk and you've got the different types of milk and cheese and so on. Well, that's really, that's a taxonomy. Whenever you organize your folders on your desktop or you go into your email inbox and you start tagging your emails and organizing those into a folder structure, you are doing taxonomy work. In the digital age, we put hashtags on our Instagram posts, all that kind of work is effectively taxonomy work.

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