KNOWLEDGE GRAPH LAB

SOURCE ZERO Deployments

From laboratory work to real-world deployment

SOURCE ZERO was not developed as a theory detached from practice. The methodology grew out of real deployments, server-log analysis, crawler-access problems, entity reconciliation, structured data and observation of responses produced by generative systems.

Knowledge Graph Laboratory develops the research, methodological and control layers of SOURCE ZERO. Commercial deployments may be delivered in cooperation with zrobione4U.online.

What can be deployed

The scope is defined through an audit of the existing state. We do not deploy a Schema.org type merely because it exists in the vocabulary; we use it when it describes a real entity, role or relationship and a source can be identified.

  • audit of the machine identity of a person or organisation
  • Entity Home and stable @id identifiers
  • Organization, Person, ScholarlyArticle and WebPage
  • sameAs relationships, ORCID, DOI, Wikidata and other identifiers
  • a knowledge graph in JSON-LD
  • data consistency between the website and external sources
  • authorship, roles, sources and claim provenance
  • robots.txt, sitemap.xml and crawler accessibility
  • WAF, ModSecurity and HTTP responses
  • log analysis and confirmation that a document was retrieved
  • measurement of answer-system behaviour
  • observation of changes over time

We do not build a “Knowledge Panel”

A Knowledge Panel is not a product that can be ordered or an outcome that KGL can guarantee. Google generates entity representations automatically from multiple sources and its own systems.

A SOURCE ZERO deployment serves a different purpose: to prepare a coherent, verifiable and machine-readable description of a person, organisation or publication, and to check whether the infrastructure actually allows systems to reach it.

We do not guarantee a panel, position, visibility, AI citation or ranking.

How a deployment works

  1. Audit

    We examine existing entities, identifiers, entity homes, JSON-LD, registers, profiles, inconsistencies and sources.

  2. Entity model

    We define people, organisations, publications, roles, competencies, relationships and identifiers.

  3. Implementation

    We deploy HTML, JSON-LD, @id, sameAs, canonical, WebSite, Organization, Person, WebPage, ScholarlyArticle and the required relationships.

  4. Open gate

    We check robots.txt, the sitemap, HTTP responses, WAF, ModSecurity, crawler access and logs.

  5. Measurement

    We examine actual crawler visits, 403, 406 and 429 errors, entity reconstruction, observable visibility, generative-system responses, referral traffic and changes over time.

What the client receives

  • an audit of the current state
  • an entity model
  • a relationship and identifier plan
  • corrected or new JSON-LD
  • technical implementation
  • crawler-access verification
  • log analysis
  • a post-deployment report
  • a list of confirmed elements
  • a list of elements requiring further observation

We do not report what we cannot observe.

Research and deployments

Knowledge Graph Laboratory conducts research, develops the SOURCE ZERO methodology and is responsible for the research and methodological layer.

Technical and commercial implementation may be carried out in cooperation with zrobione4U.online.

This preserves the separation between the research methodology and commercial project delivery. Both entities are connected through the author of the methodology; we do not present them as independent sources that validate their own authority.

Deployments conducted within KGL were also a source of observations described in SOURCE ZERO 2.0 — The Open Gate. The publication documents crawler access, HTTP 403/406/429 responses, server logs, entity reconciliation, source selection by generative systems and the limitations of such observations.

Knowledge Graph Laboratory

Research, methodology, control model, definition of criteria and interpretation of observations.

zrobione4U.online

Possible technical and commercial delivery within the agreed scope.

SOURCE ZERO 1.0 — DOI ↗ SOURCE ZERO 2.0 — DOI ↗

Do you want to see how machines interpret your organisation?

We can start with an audit: examine entity identity, structured data, sources, crawler access and the points at which a system currently has to infer missing information.

Ask about a SOURCE ZERO audit