The hunt for a recommendation, Stacey Donion, MD, provides a very different encounter. Like the Town of Boston site above, Dr. Donion’s profile on the Kaiser Permanente website is perfectly intelligible to a sighted human reader. However, because its markup is entirely presentational, its material is imperceptible to software agents.

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.

In 2012, content strategist Karen McGrane wrote that”you don’t get to determine which platform or device your customers use to get your content: they do.”
If we run Dr. Ruhlman’s Swedish Hospital profile page through Google’s Structured Data Testing Tool, we can observe that content about him is structured as small, different elements, each of which is marked up with descriptive types and attributes that communicate both the meaning of those traits’ values and the way they fit together as a whole–all in a machine-readable format.

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.

The Company case for content that is structured layout

Linked data and content aggregation

Software agent search and semantic HTML

In this instance, Dr. Ruhlman’s profile is marked up with microdata based on the vocabulary. is a collaborative effort backed by Google, Yahoo, Bing, and Yandex that intends to create a frequent language for electronic resources on the internet. This base that is content provides the base on. The Knowledge Graph information box, for example, includes Google testimonials, which aren’t part of Dr. Ruhlman’s profile, but that have been aggregated into this review.
To be able to tailor results to these questions that were especially formulated, software agents have started inferring intent and then using the data in their disposal. 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 displays this effect:

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

In this example, we can see that Google is able to find lots of connections to Dr. Donion in its own typical index results, but it is not able to”know” the data about those sources well enough to present an aggregated result. In this case, the Knowledge Graph knows Dr. Donion is a Kaiser Permanente doctor, but it pulls at the wrong place and the incorrect doctor’s title in its endeavor to build a Knowledge Graph screen.
Not one of the links supplied in this 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 am on the right track. (I didn’t inquire about asking a hearing.) This is because the content on the Town of Boston parking ticket page is styled to communicate content relationships visually to readers but isn’t structured semantically in a manner that also communicates those connections to inquisitive algorithms.

You’ll also notice that while Dr. Stacey Donion is an exact match in all of the listed search results–which can be a lot of enough to fill the first results page–we’re shown a”did you mean” connection for a different physician. Stacy Donlon, MD, is a neurologist who practices. Multicare does, nevertheless, provide semantic and related profiles that are data-rich to get their physicians.
In addition to the indexing purpose that search engines function, smart brokers and AI-powered search calculations are currently bringing of accessing information: aggregation and 34, two modes. As a result, design campaigns that focus on producing visually effective pages are sufficient to guarantee accuracy or the integrity of articles published on the net. Instead, by focusing on providing access to data in a structured, systematic way that is legible to both humans and machines, content publishers can ensure that their content is both accurate and accessible in these new contexts, whether they’re creating chatbots or tapping to AI directly. In this article, we’ll consider the forms and impact of content that is structured, and we’ll close with a set of resources which could help you to get started using a material that is structured approach to data design.

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.'

While this use of semantic HTML offers distinct advantages over the”page display” styling we saw on the City of Boston’s website, the Seattle page also shows a weakness that is typical of manual approaches to semantic HTML. You will notice that, in the Google Assistant results, the”Pay by Phone” option we saw on the web page was not listed. This irregularity in arrangement may be what is causing this option to be omitted by Google Assistant .
Layout practices which build bridges between technology needs and user requirements to meet business goals are critical to making this vision a reality. Expertise designers all, content strategists, programmers, and information architects have a role to play in providing and designing structured content options.

In addition to excerpting and locating information, such as parking ticket payment choices or recipe steps, software and search representative calculations also now aggregate content from several sources using linked data.

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.
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.
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.

There is not enough proof within this little sample to encourage a broad claim that algorithms have”cognitive” bias, but even when we allow for possibly confounding variables, we can observe the compounding issues we risk by ignoring structured content. No matter the Kaiser Permanente result we are given previously for Dr. Donion is to get the wrong doctor. Furthermore, from the Google Assistant voice search, the interaction format does not verify if we meant Dr. Donlon; it just provides us with her facility’s contact information. In such cases, providing clear content may only work to our advantage.
By communicating clearly in a digital context that now includes aggregation and inference, associations are more effectively able to consult with their customers where users actually are, make it on a website, a search engine results page, or even a voice-controlled digital assistant. They are also able to maintain greater control over their messages’ truth by ensuring that the proper content communicated and are available across contexts.
Because it’s composed of organized content that is marked up Regardless of the simplicity of the Town of Seattle parking ticket page, it ensures the integrity of its content across contexts. “Pay My Ticket” is a level-one heading (

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

), which signify that they are subordinate to the level-one element.
The rising prevalence of voice as a manner of access to information makes supplying structured, machine-intelligible content even more significant. Voice and software agents that are smart aren’t solely preventing users they are changing user behaviour. According to LSA Insider, there are numerous important differences between voice inquiries and typed queries. Voice queries often be:
This statement was meant to help designers, strategists, and businesses get ready for the imminent rise of cellular. With the prevalence of inquiries and supporters, the site of an organization is less likely to become a possible customer’s first experience with content that is abundant and less. Such as ratings, hours, telephone numbers, and finding location info — in many instances –this participation may be a user interaction with a data source.

Getting started: who and how

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.
A combined HTML code editor and preview window showing markup and results for heading, ordered list, and list item HTML tags.

Structured content is already a mainstay of many types of information on the internet. Recipe listings, for example, have been predicated on structured content for years. When I search, by Way of Example,”bouillabaisse recipe” on Google, I’m provided with a standard list of links to recipes, in Addition to an Summary of recipe measures, an image, and a set of tags describing one instance recipe:
HTML is both semantic and presentational because individuals understand what lists and headings look like and mean, and algorithms can recognize them as components with interpretable relationships.
Semantic HTML is about the connections between document elements, as opposed to just describing how they should look on display. Semantic elements such as heading tags and record tags, for instance, indicate that the text they enclose is a heading (

) for the set of list items (

  • ) in the ordered list (
      ) that follows.

      Google search results page for a bouillabaisse recipe including an image, numbered directions, and tags.
      A”featured snippet” to get on 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 same page seen in Google’s Structured Data Testing Tool. The values are shown by the pane on the right.
    1. Content Strategy for Mobile, Karen McGrane
    2. HTML markup that concentrates only on the presentational facets of a”webpage” may seem perfectly fine to a human reader however be completely illegible to an algorithm. If I Wish to find information about how to pay a parking ticket, a link in the home page takes me straight to the”How to Purchase a Parking Ticket” display (scrolled to reveal detail):

      While I inquire Google Assistant what time Dr. Donion’s office closes, the result is not only less helpful but actually points me in the incorrect direction. Instead of a selection of actions I’m presented .

        On creating content systems which work for algorithms and humans alike, practitioners from the design community have shared a wealth of tools in recent years. These articles and books are a Terrific place to begin to learn more about executing a content that is structured approach for your company:

      • Designing Connected Content, Carrie Hane and Mike Atherton
      • MultiCare Neuroscience Center, you’ll recall, is Dr. Donlon–the neuroscientist Google believes I may be looking for, not the orthopedic surgeon I am actually looking for–clinics. Dr. Donlon’s profile page, much like Dr. Ruhlman’s, is semantically structured and marked up with connected data.

        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.

        Remixed although these results aren’t just aggregated from disparate sources, but are interpreted to provide a customized response. Getting instructions, placing a phone call, and accessing Dr. Ruhlman’s profile site on are all at the tips of my hands.
        I readily understand what my choices are for paying as this page being read by a person : I will pay online, in person, over the phone, or by mail. But things get a little confusing, if I request Google Assistant how to pay a parking ticket in Boston:
        The Google Assistant hunt , however, offers a result that is more helpful than we see with Boston. In this case, the Google Assistant result links right to the”Pay My Ticket” page and also lists several ways I will pay my ticket: online, by email, and also in person.

        The City of Seattle website’s “Pay My Ticket” page, with the HTML heading elements outlined and labeled for illustration.

        These kinds of fast interactions, however, are only one piece of a much larger problem: linked data is key to preserving the integrity of articles online. The associations I have used as examples, like the hospitals, schools I’ve consulted with for years, and government agencies, do not measure the success of the communications efforts in ad clicks or page views. Success for them means linking patients, components, and community members with services and precise information regarding the business. This communication-based definition of success readily applies to practically any type of company working to further its business goals.

        Voice queries and content inference

        In a content that was structured design procedure, the connections between content chunks are explicitly defined and described. This makes the content chunks and the relationships between them legible into algorithms. Algorithms can then translate a content package as the”webpage” I am searching for–or remix and accommodate the exact same content to give me a list of instructions, the number of stars on a critique, the period of time left until an office closes, and any variety of additional succinct answers to specific questions.

        The model of constructing pages and anticipating users to detect and parse those pages to answer questionsfrom the era that is pre-voice, is becoming inadequate for communication. It precludes organizations from participating in emerging patterns of information discovery and seeking. Andas we found in the event of hunting for information about doctors –it might lead software representatives to make inferences based on information routing customers to competitors who communicate more effectively.
        Connected data expands the fundamental capabilities of semantic HTML by describing not only what sort of item a page component is (“Pay My Ticket” is a

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

        signifies a”pay activity,” which inherits the structural attributes of”trade actions” (the market of goods and services for cash ) and”actions” (actions carried out by a broker upon an object). Data creates a more nuanced description and it provides the structural and conceptual advice that algorithms need to bring data together.
        Say that I want to gather more information about two recommendations I have been awarded for orthopedic surgeons. A search for a first recommendation, Scott Ruhlman, MD, brings up a set of links in addition to a Knowledge Graph info box containing a photo, location, hours, telephone number, and testimonials from the net.

      An enormous difference is read by the machine interpreting it Though every one of these elements would look the same into a sighted human creating this webpage. While semantic HTML can be theoretically supported by WYSIWYG text entry fields, in training that they fall prey into the idiosyncrasies of even the most content authors. By making content structure that is meaningful a core element of a website’s content management system, organizations can produce semantically correct HTML for each component. This is also the base which makes it feasible to capitalize on the relationship descriptions afforded by data that is linked.
      In late 2016, Gartner predicted that 30 percent of web browsing sessions could be done without a display by 2020. Though there’s recent signs to suggest the 2020 picture might be more complex than these broad-strokes projections imply, we are already seeing the effect that voice search, artificial intelligence, and smart software agents like Alexa and Google Assistant are creating on the way information can be consumed and found on the internet.
      To be honest, subsequent trials of this search did produce the generic (and partially incorrect) practice place for Dr. Donion (“Kaiser Permanente Orthopedics: Morris Joseph MD”). The initial result, however, indicates that smart agents may be at least partially susceptible to the exact same accessibility heuristic which affects humans, wherein the information that is simplest to recall often seems the most appropriate.
      These elements, when designed convey relationships and information hierarchy visually to calculations, and into readers.
      The City of Seattle’s”Pay My Ticket” page, even though it lacks the polished visual design of Boston’s site, also communicates parking ticket payment options obviously to human visitors:
      This”featured snippet” view is possible since the content publisher,, has broken this recipe in the smallest meaningful chunks suitable for this subject matter and audience, and then expressed information about those chunks and the connections between them at a machine-readable way. In this instance, has used both semantic HTML and linked data to produce this content not only a webpage, but in addition legible, accessible data which may be accurately interpreted, adapted, and remixed by calculations and smart agents. Let’s look at each one of these components in turn to learn how they work across inference contexts, and indexing, aggregation.
      A structured content layout strategy frames content tools –like recipes, articles, product descriptions, how-tos, profiles, etc.–not as pages available and read, but as packages composed of small chunks of content information that relate to one another in meaningful ways.

      The Use of structured content