Navigator:
- Media Concept
- Data Sources for Media
- Data Schema: Human and Machine Processing Breakdown
- Guidelines for Automated Services in the Schema
MEDIA CONCEPT
Design tables with glass tops held up by ceramic animal figures. The media focuses on the fact that the figure supports the glass, but this is a metaphor: the ceramic not only supports the tabletop but also the contained space—a defined place. The media illustrates how an authored object is born from handcrafted labor, non-standard color, and character, and how it subsequently lives within a home.

DATA SOURCES FOR MEDIA
Source 1: WorkshopPhotographs and videography of the process, specifically molding, firing, glazing, and assembly. Drafts, sketches, records of firing temperatures, and notes on cracks and their causes.
Source 2: Ready-made objectsParameters for each shape and composition: title, color, dimensions, pose, role in the composition, creation date, series number. Glass parameters: thickness, shape, mounting.
Source 3: Buyers and Clients
Correspondence in Telegram and Instagram*, customer reviews, order histories, and customization requests. With permission—quotes and stories.
(*social media network banned in the Russian Federation)
Source 4: Professional CommunityInterior designers, curators, platforms, galleries. Interviews, comments, and feedback.
Source 5: Interiors
Photography of tables at client sites and in showrooms. Space description: style, colors, lighting, and how the table interacts with the interior design.
Source 6: Channel Analytics
Telegram and Instagram statistics: reach, saves, reposts, incoming inquiries. This is less about the content itself and more about structuring the thematic plan and understanding which topics resonate with the audience.
Source 7: Professional literature and media.Publications on collectible design, ceramics, and functional sculpture.
DATA SCHEMA WITH HUMAN AND MACHINE PROCESSING SEPARATION
Stage: CollectionData: photos, videos, sketches, workshop recordingsHuman Processing: The artist films and records themselves—choosing angles, capturing details, and providing voice commentaryMachine Processing: Automatic cloud upload, sorting by date, and facial/object recognition for tagging
Stage: CollectionData: figure and composition parametersHuman Processing: The author manually fills out the card: name, color, pose, roleMachine Processing: A spreadsheet template with field validation, automatic population of date and series number
Phase: CollectionData: correspondence with buyersHuman Processing: the author reads, replies, and highlights quotesMachine Processing: automatic database export, tagging based on request type (order, question, review)
Stage: ProcessingData: Draft postsHuman Processing: The author writes the text in the first personMachine Processing: Spell check, post length suggestions, automatic paragraph splitting
Stage: ProcessingData: Photos and VideosManual Processing: The author selects shots and decides what to show.Machine Processing: Basic color correction, framing to fit formats, compression, thumbnail creation.
Stage: processingData: customer quotes and storiesHuman Processing: the author edits while preserving the human voiceMachine Processing: spellcheck and punctuation review
Stage: ProcessingData: TerminologyHuman Processing: The author formulates the explanation in plain language.Machine Processing: Compliance check and suggestions for simplifying phrasing.
Stage: PublicationData: Text and MediaHuman Processing: Author approves final versionMachine Processing: Automatic scheduled posting, cross-posting to Telegram and Instagram, site preview generation
Stage: PublicationData: object cards on the websiteHuman Processing: the author verifies the description matches the objectMachine Processing: automatic generation of the card from the table, image insertion, updates upon data change
Phase: AnalysisData: Channel metricsHuman processing: The author interprets which topics resonate and what questions are being askedMachine processing: Automatic statistics collection, overview of reach, saves, and inbound inquiries
Stage: AnalysisData: Incoming requestsHuman processing: The author responds personally and logs the resultMachine processing: Automatic sorting of requests by type, reminders for unanswered requests, conversion tracking
GUIDELINES FOR AUTOMATED SERVICES IN THE SCHEME
Guideline 1The machine does not write in the author’s voice. Any automated service—whether it is text generation, suggestions, or auto-replies—must not publish text in the first person without the author’s approval. The machine may offer a draft, structure, or review, but the final wording remains the human’s responsibility.




