Rob Hanna and Lance Cummings: Information Typing in DITA – Episode 215
Rob Hanna and Lance Cummings Good communication has always been about understanding your audience — shaping your message to match how they think, what they need, and what they'll do with it. Information typing, the "IT" in the technical documentation standard DITA, codifies that practice into a design discipline that organizes content around its function rather than its form. Rob Hanna and Lance Cummings explore how information typing clarifies writing for human readers and have discovered in the process that those same structural principles help AI deliver better results. We talked about: their mutual interest in information typing, the "IT" in the DITA technical documentation standard the origins of information typing in textbook-building research at Stanford by Robert Horn in the 1960s how aligning information by function and to human capabilities reduces cognitive load how Lance's early work trying to teach structured thinking about content to his students led to his study of information typing information typing as a design discipline the origins of structured authoring well before DITA was created the rhetorical nature of an information typing system the three foundational info types in DITA - concept, task, and reference - and two extensions that Rob has developed — principle and process the importance of the process information type in agentic AI architectures the role of rhetoric, in particular the application of "machine rhetorics," in establishing context for AI agents the importance of being aware of the connections between how our brains work and what content is some examples of research they've done that shows how structured content improves results in AI systems like RAG (Retrieval Augmented Generation) Rob's advice to technical writers to become well-versed in structured authoring to adapt to the need to write for both humans and machines Lance's assertion that "information typing isn't just for technical writers" Rob's bio Rob Hanna is the CEO and co-founder of Precision Content. For more than 30 years, he's helped organizations turn complex documentation into structured, reusable knowledge that supports people, processes, and increasingly, AI. His passion is improving outcomes for companies embarking on structured authoring journeys—helping them avoid costly missteps, align teams around a practical content strategy, and build systems that make information easier to create, govern, find, and reuse. At Precision Content, he leads teams of writers, information architects, trainers, and developers to raise the standard of technical communication through DITA, CCMS implementations, metadata, microcontent, and information architecture. He's taught structured authoring, metadata, and taxonomies, and he's a Fellow of the Society for Technical Communication. What drives him most is seeing organizations move from fragmented content to reliable content supply chains that deliver better experiences for customers, employees, partners, and digital systems. Connect with Rob online LinkedIn Precision Content Lance's bio Lance Cummings is a professor of English in the Professional Writing program at the University of North Carolina Wilmington. Dr. Cummings explores content strategy and writing in technologically and culturally diverse contexts both in his research and teaching. His most recent work looks at how to leverage structured content with rhetorical strategies to improve the performance of generative AI technologies and shares his explorations in his newsletter, Cyborgs Writing . Connect with Lance online LinkedIn Cyborgs Writing What 17 Student Chatbots Showed Me About Structured Content article Video Here’s the video version of our conversation: https://youtu.be/Kn9roYzWS-g Podcast intro transcript This is the Content Strategy Insights podcast, episode number 215. When you're trying to communicate with either human beings or computers, it helps to align the kind of information you're imparting with the way the recipient expects to receive it. Technical writing experts call this "information typing," the practice of organizing content around its intent, not its format, which better aligns the information to human cognitive preferences. It turns out that this practice also helps AI systems deliver better results. Interview transcript Larry: Hi, everyone. Welcome to episode number 215 of the Content Strategy Insights podcast. I am really delighted today to welcome to the show Rob Hanna and Lance Cummings. Rob is the CEO and the founder at Precision Content, a technical content consulting company. And Lance is a professor of professional writing at University of North Carolina at Wilmington. He's also a well-known content creator. We'll talk a little bit more about that. So welcome to both of you, and maybe start with Rob. Rob, tell the folks a little bit more about what you're up to these days. Rob: Perfect. Thanks, Larry. Yes, we've been pioneering a writing methodology that we believe makes content easier for people to use. And as it turns out, easier for machines to use. So, there's continuous development and research in this field on how we bring these together and create better future-proof content. So, I've been embroiled in that for the last number of years. Larry: Nice. And Lance? Lance: Yeah, so I've been teaching and researching how we write and collaborate in diverse linguistic and technological environments. And I've been writing about AI since before ChatGPT in online, and kind of found my niche with technical writing. I was introduced to DITA probably back in 2017, '18, something like that at a conference and been trying to figure it out ever since. And really, ran into Rob's stuff at a conference, and the information typing clicked for me. Whereas I understand DITA and the use cases, but haven't necessarily had the time to really dig in and use it on my own, or to teach a class on it. But the information typing really got me thinking about structured writing in a different way, especially in concerns with AI, which I've been exploring on my blog, Cyborgs Writing on Substack. Been looking at structured approaches, how you take structured approaches, combine that with rhetoric to make AI work better. And I've really found information typing to be a pretty big part of that recently, and been working on developing approaches in AI writing systems and things like that. Larry: Nice. And you're reminding me of the reason this conversation came together. One of you, I think... I can't remember which of you posted it, but you had jointly created this document called DITA Information Types Aren't Templates, which I think is one of the key concepts behind DITA. I wonder maybe, Rob, maybe you can talk about that a little bit. What led to that article and a little bit about the difference between types and templates? Rob: Sure. Perfect. Thank you. Yeah, this has been a crusade of mine for a very, very long time: understanding what information typing is. I like to say it's at the heart of DITA. And D-I-T-A Information Typing, it's right there, but there's so little discussed or talked about what information typing actually is. In my work with the OASIS subcommittee, Business Documents Subcommittee, back in the aughts, we were looking at how we extend beyond product support and into the rest of the business. So, I studied a lot of different models that we could look to for extending DITA beyond simply concept, task, and reference, and landed upon information mapping. And so, that's where I discovered the genesis of information typing as defined by Robert Horn back in the late '60s at Stanford University, where he came up with these ideas around these information types based on patterns that he had found in textbooks. Rob: His task was to try to find a methodology that would help to build a better textbook. And so, through his analysis of a lot of text, he found these patterns in that content. And from there, a number of other folks in pedagogy and other areas started to look at why do these patterns emerge. And so, where we've landed with that is that that information types represent the function of information. In other words, how do our brains work with that information? How do we lower cognitive load for the reader by aligning information by function, and not mixing content together that have different purposes, different functions, different outcomes? Rob: So we can sort that apart, tease them apart, and signal to the reader what type of information it is that they're looking for. We can dramatically reduce the cognitive load and improve performance on that content. So, it's well beyond what a template was ever designed to do. This is more a template for your brain. This is how your brain works and how we template the information. Going here and actually do something with that information. Larry: Yeah. As you said that, it's a higher level than just WYSIWYG thinking. It's like, what are you doing here? What's the function versus the form that it takes in its expression? And one of the things that makes it so powerful, I think, is its alignment with how humans think. Maybe you can talk a little bit about this, Lance, is how the cognitive science that supports information typing and a lot of other DITA stuff as well. Lance: Yeah. So, I'll start by saying one of my hobbies has been to take the idea behind DITA and try to apply it to my education materials that I use with students, and also my own notes structures and things like that, because I see the value of reuse and modular thinking. And that's one of the things that I did in my blog when AI first came out, was to try to apply those. But a lot of times, trying to use the DITA labels, they didn't quite fit and I had a lot of trouble. And sometimes, you just make up your own labels and things like that,...

