Google search results page for Scott Ruhlman, MD, showing a list of standard links and an info box with an image, a map, ratings, an address, and reviews information.

There is not enough evidence in this little sample to support a wide claim that calculations have”cognitive” prejudice, but even if we allow for potentially confounding variables, we can see the compounding issues we risk by ignoring structured content. Regardless, the Kaiser Permanente outcome we’re given above for Dr. Donion is to get the wrong doctor. Furthermore, in the Google Assistant voice hunt, the interaction format does not confirm whether we meant Dr. Donlon; it only provides us with her facility’s contact information. In these scenarios, providing clear, machine-readable content can work to our advantage.

In late 2016, Gartner called that 30 percent of internet browsing sessions could be done with no display by 2020. Even though there’s recent signs to suggest that the 2020 picture may be more complicated than these broad-strokes projections imply, we’re already seeing the effect that voice hunt, artificial intelligence, and smart software agents like Alexa and Google Assistant are making about the way information can be found and consumed on the internet.

The City of Boston website's “How to Pay a Parking Ticket” page, showing a tabbed view of ways to pay and instructions for the first of those ways, paying online.

The Company case for structured content layout

The City of Seattle website‘s “Pay My Ticket” page, showing four methods to pay a parking ticket in a simple, all-text layout.

None of the links provided in the Google Assistant results take me directly to the”How to Pay a Parking Ticket” page, nor do the descriptions clearly allow me to know I’m on the ideal track. (I didn’t ask about asking a hearing.) This is due to the fact that the content on the Town of Boston parking ticket page is styled to convey content connections visually to human readers but isn’t structured in a manner which conveys those relationships to inquisitive algorithms.
HTML is both semantic and presentational because people understand what headings and lists look like and mean, and algorithms can recognize them as components with defined relationships.
In this example, Dr. Ruhlman’s profile is marked up using microdata based on the schema.org language. This base that is content provides the foundation on which further content connections could be constructed. The Knowledge Graph info box, for instance, comprises Google reviews, which are not part of Dr. Ruhlman’s profile, but that have been aggregated to this review.

MultiCare Neuroscience Center, you’ll remember, is where Dr. Donlon–the neuroscientist Google thinks I may be looking for, not the surgeon I am actually looking for–clinics.

The role of structured articles

As a human reading this page, I understand for paying what my choices are : I will pay online, in person, by mail, or over the phone. But things get a little confusing, if I request Google Assistant how to pay a parking ticket in Boston:

Program broker search and semantic HTML

Though each of these elements would look the exact same into a human producing this page, a difference is read by the machine. That they fall prey into the idiosyncrasies of the very well-intentioned content writers Even though semantic HTML can be theoretically supported by WYSIWYG text entry fields, in training. By making content structure that a core part of a site’s content management system, organizations can produce correct HTML every moment, for each element. This is also the base which makes it possible to capitalize on the rich relationship descriptions given by data.

In a layout procedure, the relationships between content chunks are specifically defined and described. This creates the relationships between them and both the material chunks legible to algorithms. Algorithms can then interpret a content bundle as the”page” I’m searching for–or remix and adapt that same content to give me a list of instructions, the number of celebrities on a review, the amount of time left before an office shuts, and some variety of additional succinct answers to certain questions.

HTML markup that concentrates just on the presentational aspects of a”page” may look perfectly fine to a human reader however be completely illegible into an algorithm. If I Wish to find information about how to pay a parking ticket, then a connection from the home page takes me directly to the”How to Purchase a Parking Ticket” display (scrolled to reveal detail):

To be able to tailor results to such specifically formulated queries, software agents have begun then and inferring purpose using the linked data at their disposal to assemble a targeted, succinct response. If I request Google Assistant what time Dr. Ruhlman’s office closes, for instance, it reacts,”Dr. Ruhlman’s office closes in 5 p.m.,” and exhibits this effect:

The City of Seattle website’s 'Pay My Ticket' page, with two HTML heading elements outlined and labeled for illustration, and an open inspector panel, where we can see that the headings look the same to viewers but are marked up differently in the code.

Semantic HTML is markup which communicates information about the relationships between document components, instead of simply describing how they should look on display. Semantic elements like heading tags and list tags, for example, indicate that the text they enclose is a heading (

) for the collection of list items (

  • ) from the ordered list (
      ) that follows.

    1. Content Strategy for Mobile, Karen McGrane
    2. These elements, when designed well, convey data hierarchy and relationships visually to viewers, and to algorithms.
      Despite the visual simplicity of the Town of Seattle parking ticket page, it ensures the integrity of its material across contexts as it’s composed of organized content that’s marked up semantically. “Pay My Ticket” is a level-one heading (

      ), and also every one of the choices below it’s level-two key words (

      ), which indicate that they are inferior to the level-one component.

      Getting started: who and how

      In this instance, we could see that Google is able to find lots of connections to Dr. Donion in its own typical index results, but it isn’t able to”know” the information about these sources well enough to demonstrate an aggregated result. In this case, that the Knowledge Graph knows Dr. Donion is a Kaiser Permanente physician, but it pulls at the wrong place and the incorrect physician’s title in its attempt to construct a Knowledge Graph screen.
      When I inquire Google Assistant what time Dr. Donion’s office closes, the outcome is not just less useful but actually points me in the incorrect direction. Rather than a concentrated selection of actions to follow up on my query, I am presented to MultiCare Neuroscience Center.
      Although this use of semantic HTML offers distinct advantages over the”page display” styling we found on the Town of Boston’s site, the Seattle page also reveals a weakness that is typical of guide approaches to semantic HTML. You will notice that, in the Google Assistant results, the”Pay by Phone” option we found on the webpage was not recorded. If we look at the markup of this page, we can see that while the 3 choices found by Google Assistant are wrapped in both and

      tags,”Pay by Phone” is only marked up with an

      . This irregularity in structure may be what is causing Google Assistant to omit this option from its own results.
      In addition to the indexing purpose that search engines perform, smart agents and AI-powered search algorithms are now bringing two additional modes of obtaining information. As a result, design campaigns that are devoted to producing effective pages are enough to guarantee accuracy or the integrity of content published on the web. Instead, by focusing on providing access to data within a structured, systematic manner that is legible to both machines and humans, content publishers may ensure that their content is both accessible and accurate in these new contexts, whether or not they’re creating chatbots or tapping to AI directly. In this guide, we will look at the forms and impact of content, and we are going to close with a set of tools that could help you get started with a material approach to information design.
      A structured content design approach frames content resources–like recipes, articles, product descriptions, how-tos, profiles, etc.–maybe not as pages available and read, but as bundles composed of small chunks of content information that all relate to one another in meaningful ways.

      Google search results page for Dr. Donion, showing a list of standard links for Dr. Donion, and a 'Did you mean: Dr Stacy Donlon MD' link at the top. There is a Google info box, as with the previous search results page example. But in this case the box does not display information about the doctor we searched for, Dr. Donion, but rather for 'Kaiser Permanente Orthopedics: Morris Joseph MD.'

      These outcomes aren’t just aggregated from sources, but are interpreted and remixed to supply a customized response to my particular question. Getting instructions, placing a phone call, and accessing Dr. Ruhlman’s profile page on swedish.org are all at the ends of my hands.
      Design practices which build bridges between user requirements and technology requirements to meet with company goals are critical to making this vision a reality. Content strategists information architects, programmers, and experience designers all have a part to play in designing and delivering content options that are successful structured.

      The City of Seattle website’s “Pay My Ticket” page, with the HTML heading elements outlined and labeled for illustration.
      Google Assistant app on iPhone with the results of a “how do I pay a parking ticket in Seattle” query, showing nearly the same results as on the desktop web page referenced above.
      Google search results page for a bouillabaisse recipe including an image, numbered directions, and tags.
      A”featured snippet” for allrecipes.com about the Google results page.
      Google Structured Data Testing tool showing the markup for a bouillabaisse recipe website on the left half of the screen and the structured data attributes and values for structured content on the right half of the screen.
      The exact same allrecipes.com page viewed in Google’s Structured Data Testing Tool. The pane on the right shows the values that are machine-readable.

      In its simplest form, linked data is”a set of best practices for connecting structured data on the web.” Connected data extends the fundamental capacities of semantic HTML by describing not just what kind of item a page element is (“Pay My Ticket” is an

      ), but also the real world concept that item represents: this

      signifies a”pay activity,” which inherits the structural attributes of”trade activities” (the exchange of goods and services for money) and”activities” (actions carried out by a broker upon an item ). Linked data generates a richer, more nuanced description of the association between page elements, and it provides the structural and technical information that calculations need to bring data together from disparate sources.

        The search for a second recommendation, Stacey Donion, MD, provides a very different encounter. Like the City of Boston site above, Dr. Donion’s profile on the Kaiser Permanente website is perfectly intelligible to some sighted human reader. But since its markup is presentational, its content is almost invisible to software agents.

        Google search results info box for Dr. Ruhlman, showing an photo; a map; ratings; an address; reviews; buttons to ask a question, leave a review, and add a photo; and other people searched for.

        The model of then expecting users parse and to discover these pages to answer questions and constructing pages in the era that is pre-voice, is becoming insufficient for successful communication. Organizations are precluded by it from participating in emerging patterns of information discovery and hunting. And–as we found in the event of searching for information about doctors –it may lead software representatives to make inferences based on incorrect or insufficient information , possibly routing clients to rivals who communicate more efficiently.

        Linked content and data aggregation

        The increasing prevalence of voice as a mode of access to data makes providing structured, machine-intelligible content all the more significant. Software agents and voice are not freeing users from their keyboards, they’re changing user behaviour. Based on LSA Insider, there are many important differences between voice inquiries and typed questions. Voice questions tend to be:

        When we conduct Dr. Ruhlman’s Swedish Hospital profile site through Google’s Structured Data Testing Tool, we can see that articles about him is structured as small, different elements, each of which can be marked up using descriptive types and attributes that communicate the significance of these traits’ values and the way they fit together as a whole–all in a machine-readable format.
        Search and software agent algorithms now aggregate content from several sources by using linked data.

      • Content Modelling: An Expert Skill,” Rachel Lovinger
      • These kinds of interactions, but are only one part of a larger issue: connected data is key to preserving the integrity of articles online. Like the hospitals, colleges I’ve consulted for decades, and government agencies, don’t measure the success of their communications efforts in ad clicks or page views. Success for them means linking constituents, patients, and community members with solutions and precise information regarding the organization that information may be found. This definition of success applies to any type of organization working to further its business goals.

        Google Assistant app on iPhone with the results of a “what time does dr. ruhlman office close” query. The results displayed include a card with “8:30AM–5:00PM” and the label, “Dr. Ruhlman Scott MD, Tuesday hours,” as well as links to call the office, search on Google, get directions, and visit a website. Additionally, there are four buttons labeled with the words “directions,” “phone number,” and “address,” and a thumbs-up emoji.
        Google Structured Data Testing tool, showing the markup for Dr. Ruhlman's profile page on the left half of the screen, and the structured data attributes and values for the structured content on that page on the right half of the screen.

        You will also notice that while Dr. Stacey Donion is an exact match in all the listed search results–which can be a lot of enough to meet with the first results page–we are revealed a”did you mean” link for a different physician. Stacy Donlon, MD, is a neurologist who practices at MultiCare Neuroscience Center, which is not affiliated with Kaiser Permanente. Multicare does provide semantic and related profiles that are data-rich for their doctors.

      • Designing Connected Content, Carrie Hane and Mike Atherton
      • A combined HTML code editor and preview window showing markup and results for heading, ordered list, and list item HTML tags.
        Google Assistant app on iPhone with the results of a “how do I pay a parking ticket in Boston” query, showing results only weakly related to the intended content.

        Content is already a mainstay of various kinds of information on the web. Recipe listings, for instance, have been predicated on structured articles for years. When I search, by Way of Example,”bouillabaisse recipe” on Google, I’m provided with a standard list of links to recipes, as well as an Summary of recipe measures, a picture, and a pair of tags describing one example recipe:

        • Longer;
        • more likely to inquire who, what, and where;
        • more conversational;
        • and more specific.

        On creating material systems that work for algorithms and humans alike practitioners from throughout the design community have shared a wealth of tools lately. To learn more about executing a content that is structured strategy for your organization, articles and these books are a great place to start:
        The City of Seattle’s”Pay My Site” page, even though it lacks the polished visual design of Boston’s website, also communicates parking ticket payment options clearly to human visitors:
        The Google Assistant hunt , however, offers a result that is far more helpful than we see Boston. In cases like this, the Google Assistant result links right to the”Pay My Ticket” page and lists several ways I can pay my ticket: on line, by email, and also in person.

        Google Assistant app on iPhone with the results of a “what time does Doc Dr Stacey donion office close” query. The results displayed include a card with “8AM–5PM” and the label “MulitCare Neuroscience Center, Monday hours,” as well as links to call the office, search on Google, get directions, or visit a website.

        Say, as an instance, that I would like to gather info about two recommendations I have been given for orthopedic surgeons.
        This announcement was meant to help designers, strategists, and companies prepare for the imminent rise of mobile. With the growing prevalence of clever supporters and queries, the website of an organization is less inclined to become a customer’s first encounter with content that is rich and less. In many cases — such as ratings, hours, telephone numbers, and finding location info –this pre-visit participation might be a user interaction with a data resource.
        This”featured snippet” view is possible because the content publisher, allrecipes.com, has broken this recipe into the smallest meaningful chunks suitable with this subject matter and audience, and then expressed information about these chunks as well as the relationships between them in a machine-readable manner. In this example, allrecipes.com has used both semantic HTML and connected data to make this content not merely a page, but also legible, accessible data that can be accurately interpreted, accommodated, and remixed by calculations and smart agents. Let us look at each one of these components in turn to learn how they work across indexing, aggregation, and inference contexts.
        To be honest, following trials of this search did produce the generic (and partially incorrect) practice location for Dr. Donion (“Kaiser Permanente Orthopedics: Morris Joseph MD”). The initial result, nevertheless, indicates that smart agents may be at least partly susceptible to the exact same availability heuristic which affects humans, wherein the advice that’s simplest to remember frequently seems the most appropriate.
        By conveying clearly in a digital context that now includes inference and aggregation, associations are more effectively able to speak to their users where users are, be it on an internet search engine results page, a web site, or even even a voice-controlled digital helper. They are also able to keep control over their messages’ truth by ensuring the proper content are available and hauled across contexts.

        Voice queries and articles inference