Schema: unitText

An in-depth JSON-LD example for JobPosting markup, wired into the Xoo universe as Xoo Code Inc. hiring a Senior Structured Data Engineer for the XooStructured team at Dunmore. Learn the Google for Jobs rich result requirements: the tricky baseSalary composition, employmentType enum, remote-work properties, and the requirements soup that trips up most authors.

PropertyValue JSON-LD example for product specifications: material, weight, color, fit, print method, and care instructions. The key-value structure that Product and Place use for additional properties beyond the core fields.

Dataset JSON-LD example for Jane Xoo's 1945-1955 pediatric outcome data. Covers distribution with DataDownload for file formats, temporalCoverage and spatialCoverage, variableMeasured, license, measurementTechnique, and how Dataset markup feeds Google Dataset Search.

QuantitativeValue JSON-LD example for a product weight. Reference page covering all 7 QuantitativeValue properties: value, minValue, maxValue, unitCode, unitText, additionalProperty, valueReference. The standard schema.org structured value for measurements.

Demand JSON-LD example, the mirror-image of Offer for buyer-side (wanted-to-buy) signals. Direct Intangible, 30+ properties shared with Offer (availability, eligibleRegion, priceSpecification, itemOffered).

UnitPriceSpecification JSON-LD example for per-unit and subscription pricing. PriceSpecification subtype adding unitCode, unitText, referenceQuantity, billingDuration, billingIncrement, priceType.

TypeAndQuantityNode JSON-LD example for bundle components and order line items: a reusable (product, quantity, business-function, unit) tuple. StructuredValue subtype from the GoodRelations vocabulary.

HowToSupply JSON-LD example for a material consumed in a HowTo (ingredient, paint, lumber). HowToItem subtype with estimatedCost.

HowToTool JSON-LD example for a tool used (but not consumed) in a HowTo. HowToItem subtype with no unique properties.

RealEstateListing JSON-LD example for a property-listing page (sale or rent). WebPage subtype with datePosted and leaseLength.

DataFeed JSON-LD example for a feed of dataset items (a streaming / batch data feed). Dataset subtype with dataFeedElement for the feed's items.

DataFeedItem JSON-LD example for a single element inside a DataFeed. Intangible with dateCreated, dateModified, dateDeleted, item.

Observation JSON-LD example for a single statistical observation at a specific time/place. Intangible + QuantitativeValue dual inheritance. Properties: measuredProperty, observationAbout, observationDate, value, variableMeasured, marginOfError.

QuantitativeValueDistribution JSON-LD example for statistical distributions (median + percentiles 10/25/75/90 over a duration). StructuredValue parent of MonetaryAmountDistribution.

OfferForLease JSON-LD example for a lease-out offer (rental, leasing, subscription rental). Direct Offer subtype with no unique properties; businessFunction is implicitly LeaseOut.

PriceSpecification JSON-LD example for the root of the schema.org pricing tree. StructuredValue subtype carrying price, priceCurrency, validFrom / validThrough, eligibleQuantity, eligibleTransactionVolume, minPrice / maxPrice, and VAT flagging.

OrderItem JSON-LD example for a line item inside an Order. Structured-value subtype carrying orderItemNumber, orderQuantity, orderedItem, orderItemStatus, and orderDelivery for per-line fulfillment tracking.

FinancialProduct JSON-LD example for the parent of all published banking / credit / insurance offerings. Service subtype adding interestRate, annualPercentageRate, and feesAndCommissionsSpecification.

BankAccount JSON-LD example for checking, savings, and money-market accounts. FinancialProduct subtype adding bankAccountType, accountMinimumInflow, and accountOverdraftLimit.

LoanOrCredit JSON-LD example for mortgages, auto loans, student loans, lines of credit. FinancialProduct subtype adding amount, loanTerm, loanType, gracePeriod, requiredCollateral, recourseLoan, renegotiableLoan.

BusinessAudience JSON-LD example for targeting B2B products at companies by revenue, employee count, or age. Audience subtype carrying yearsInOperation, yearlyRevenue, numberOfEmployees as QuantitativeValue ranges.