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I'm Anna, the owner of the boutique.

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I specialise in maternity clothing for people who

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struggle to find the right fit.

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But my marketing spend reaches plenty of people whose

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needs don't fit what I sell.

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Anna wants a better starting point: help people discover

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what her boutique can actually supply, when it matters to

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them.

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In this proposed model, the boutique authenticates before

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publishing a discovery reference.

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Anna first checks the living shared dictionary for an

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existing category.

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A namespace provides hierarchical naming.

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Within it, a category, such as maternity clothing, brings

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related attribute definitions together.

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If a definition is missing, I can suggest it.

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I don't just create another name for the same thing.

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Suggestions go through governance and validation.

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The customer-owned cooperative maintains these shared

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definitions and discovery references.

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An attribute definition explains what a field means:

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garment type, the sizing system and measurements, fabric

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composition, price currency, or delivery options.

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Anna supplies the values for her particular product.

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The definition says what to describe; the value says what

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this boutique offers.

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For this dress, I'd publish the measurements, fabric

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details, available sizes, price, delivery area and return

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terms.

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Then I'd keep them current.

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Keep three things distinct.

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The dictionary defines the fields.

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The directory records the endpoint reference.

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Anna's own server holds the products, stock, prices and

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descriptions.

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The registry points to that authoritative source; it

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doesn't store her full catalogue.

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Validation helps establish usable information and

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admitted participation.

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It doesn't prove product quality.

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Think briefly of DNS: a root delegates to top-level

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domains, which delegate to domain authorities.

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Shared names lead you to the responsible source across

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distributed servers.

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Here, that's an analogy for lookup and delegation, not

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literal product search.

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Shared governance doesn't require one physical server, or

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a central database containing everybody's offerings.

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I'm petite and pregnant.

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I'm looking for maternity clothes with shorter

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proportions, soft fabric, and seams that hold up to

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washing.

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I need home delivery, and clear return terms.

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Maya's agent would map her words to the relevant category

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and defined attributes, then follow references to

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merchant sources.

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The intended privacy model withholds Maya's identity

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during discovery.

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Today's protected retrieval authenticates a customer to

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the provider, so that promise still needs a distinct

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privacy design.

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The comparison separates a potential fit, a mismatch and

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an unknown.

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Measurements support a fit question; missing measurements

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leave uncertainty.

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Relevant experiences of washing, fit and returns can add

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context.

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One comment isn't conclusive.

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Merchant claims, published details and user experiences

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remain different kinds of information.

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I want customers to understand what they're choosing.

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A sale that comes straight back isn't the outcome I'm

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after.

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I'd start with one product I can describe properly.

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If Maya chooses an introduction, she controls what to

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share in the intended experience.

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Any automated response is the boutique's agent, not Anna

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speaking personally.

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Anna can test useful purchases, returns and total

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acquisition cost.

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Better results have to be demonstrated.

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Which offering would you start with?
