Structured Data SEO
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Structured Data is sheet-music for search engines.


Structured Data SEO

Semantic Web (Web 3.0)

RDF image example extended
Image by, Denny [CC0], via Wikimedia Commons

Also known as structured data, the Semantic Web is centered around the Wikipedia project and Google's Freebase (2007-2016). Semantic Web markup languages have been developed to assist machine learning.

Instead of manual data-entry, datum is collected from "decorated" web-content (mark-up), stategically encoded with name / value pairs. I like to use the word "decorated" because the scripting is similar to making a word or phrase bold in a document. The rules for semantic parent and child nesting of name / value pairs is somewhat complicated and is an art called Library science.

An early example that many may be familiar with is the Virtual Business Card (vCard), which encodes contact information into a structured format. The Wikipedia uses a closed system called WikiData (2012). Google's Knowledge Graph (2012), and Facebook's Open Graph (2010), are substantially more open than Wikipedia.

Structured data allows us to do on-page search engine optimization that describes your content. Search engines store these topics and relationships and suggest links to persons who are already known to be interested in similar content. As such, we are leveraging the search engine's relevance algorithm to organically reach receptive individuals.

Imagine how many times a professional musician has heard the words, "I would have attended the show, if I had only known you were in town."


Linked Data

Video courtesey of Manu Sporny

With the emergence of location aware hand-held computers, we can tap into commonalities between the consumer and provider. For instance, a group breaks from their business meeting for lunch and someone is craving meatloaf. A quick search for meatloaf, combined with the known location of the device and the search engine yeilds results for nearby resturants that serve meatloaf.

Resturant menu/delivery/reservation services and event ticket sales are two areas where Structured Data has been widely adopted.

Alternately, a service business may target their preferred service area, generating more local business leads, reducing considerable driving hours and vehicle expenses over the course of the year. The street address is a highly ranked relavence indication in Google Knowledge Graph. There are other factors that improve top search results for the LocalBusiness schema type.

More specific LocalBusiness Types
AnimalShelter AutomotiveBusiness ChildCare Dentist
DryCleaningOrLaundry EmergencyService EmploymentAgency EntertainmentBusiness
FinancialService FoodEstablishment GovernmentOffice HealthAndBeautyBusiness
HomeAndConstructionBusiness InternetCafe LegalService Library
LodgingBusiness ProfessionalService RadioStation RealEstateAgent
RecyclingCenter SelfStorage ShoppingCenter SportsActivityLocation
Store TelevisionStation TouristInformationCenter TravelAgency

Google / Privacy

Privacy eye image

In the late 1990's, DoubleClick was the largest and most intrusive Internet advertising presence of the era. I was developing an add-on that hardened Microsoft's Internet Explorer against privacy intrusion and browser-hijacking at that time. With the announcement of Google's plans to partner/purchase DoubleClick, I shut down my project, as both companies boasted a 50% (plus) market-share -- I knew we had lost the privacy war. DoubleClick had developed tracking routines embedded in their advertisements and Google already had the database expertise to organize and pair the advertising data with their search result data. The Internet's anonimity protocol had been forever broken.

Several years later, Facebook came along with a free version of Classmates. When you are interested in contacting old friends, it is only logical that you disclose your real identity to the provider. Facebook's "Like" and "Share" buttons, now embedded on most websites, allow them to know what website you visited last.

Google, Yahoo (Bing), and Yandex are all involved in structured data development, due to marketshare consideration and the available software tools, I am specializing in the Google platform. This does not come without cost, Google's mostly free products are subject to change and sparsely documented. In addition to following a subset of Google's products, I actively follow the development of the structured data ontology (schema.org), Wikimedia (Wikipedia / WikiData) platform.

Wikipedia

Google Knowledge Graph for Michael Crichton
Google Knowledge Graph for Michael Crichton
Consensus is the refuge of scoundrels...
—Michael Crichton

Wikipedia (and WikiData) plays an important role in the identification of subjects (official website) and disambiguation of similarly named subjects. Unfortunately, the Wikipedia has become an obstacle in the credentialing process for organizations and products. The official website, defined on Wikipedia/WikiData is the primary resource for Google's Knowledge Graph cards (pictured right or above on hand-helds). Once Google has the official domain name, disambiguation is achieved and they scan the official website for additional information about the subject -- social media sites, events and news about the subject.

In the guise of "saving the encyclopedia" a small band of the most active users have made the Wikipedia unfriendly and unproductive place for anyone suspected of having a conflict of interest, or engaging in paid editing. In my four years of editing, I found that learning the cryptic nomenclature, policies, guidelines, essays and the wiki-markup was about the equivelent to earning a paralegal's certificate (7 hours week, for 11 months at UCLA). Gone are the days when you could submit a weakly referenced stub-article that could be expanded as the subject flourished.


Some background:
On 3 March 2007 Metaweb announced Freebase, describing it as "an open shared database of the world's knowledge", and "a massive, collaboratively edited database of cross-linked data". Often understood as a database model using Wikipedia-turned-database or entity-relationship model, Freebase provided an interface that allowed non-programmers to fill in structured data, or metadata, of general information and to categorize or connect data items in meaningful, semantic ways.
—Wikipedia

Producers.wiki is a MediaWiki installation to incubate Wikipedia articles for later submission and perhaps eventually to become a credentialing resource for the search engines.

Ranking or Relevance?

statistical chart for rank vs relevance page
Image by, Public Domain Dedication (CC0) via pixbay.com

Ranking:

Is ranking an important metric? If you are measuring improvement over time, or progress against a competitor, the answer is probably yes. We can’t presume much about Internet rankings, the various components, weight and algorithm are usually proprietary.

In a body of data that numbers in the billions, it is important to remember that rankings can have ties; meaning, if your website is ranked 1,294,221st there could conceivably be thousands of other websites tied at that same position. The position above, 1,294,220 may also be in a tie with many websites. In lower ranked websites, a little bit of TLC can go a long way. Of course, advancing in rank gets exponentially more difficult as your ranking improves.

Relevance:

The relevance based technique leverages the search engine’s AI to match our content with the reader’s interests (search engines maintain profiles on readers). This is a more organic approach where ranking has little relevance and some SEO techniques, geared toward ranking, may be detrimental to a relevance campaign.