SILVIA:Sovereign Information Learning Virtual Intelligent Architecture

This paper presents SILVIA (Sovereign Information Learning Virtual Intelligent Architecture), a federated Digital Twin framework designed for sovereign territorial data governance. Unlike conventional Digital Twin platforms that model constructed objects within institutional BIM workflows, SILVIA addresses living territories where the primary users are communities — including indigenous peoples, informal settlement residents, and conservation stakeholders — rather than technical professionals. The framework introduces four core contributions: (1) the Territorial Regeneration Index (TRI), a composite metric quantifying ecological, cultural, and socio-institutional regeneration grounded in Berkes (2008), Mang & Reed (2012), and Niemi & McDonald (2004); (2) a modular community-plugin architecture that allows the same core infrastructure to serve radically different territorial contexts through interchangeable knowledge bases; (3) an offline-first WhatsApp interface that enables data collection in environments without stable connectivity; and (4) a conceptualised inter-territorial semantic translation protocol that uses the TRI as a common measurement language between ecologically and culturally distinct territories. A proof-of-concept implementation demonstrates the framework across two case studies: Kanaimö (Pemón indigenous territory, Gran Sabana, Venezuela) and Caracas Metropolitan Area (informal urban settlements), with a third controlled case — a Munich residential building — under design for empirical validation of the Human Regeneration Index (HRI), a structural analogue of the TRI applied to the built environment. The system processes natural language observations via LLM, calculates TRI scores with community-specific weights, and generates an Obsidian-based knowledge graph whose density serves as a visual indicator of Digital Twin maturity. SILVIA operationalizes the CARE Principles for Indigenous Data Governance by embedding information sovereignty as a quantifiable variable (IIS) within the TRI formula itself, rather than treating data ethics as an external policy layer. This document includes an Executive Summary (page 0) followed by the full technical preprint. Proof of Concept Public release: https://youtu.be/ZgWuc1AAr_4?si=UBGSnHfwDQPViVlD GitHub Open Code: architect-josuemendes/SILVIA Keywords: Digital Twin, federated architecture, territorial governance, CARE Principles, indigenous data sovereignty, Territorial Regeneration Index, knowledge graph, informal settlements, WhatsApp, LLM, Pemón, Gran Sabana, inter-territorial semantic translation, Human Regeneration Index

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-04-16
DOI
https://doi.org/10.5281/zenodo.19616669
Primary Topic
Smart Cities and Technologies
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article
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article

SILVIA:Sovereign Information Learning Virtual Intelligent Architecture

Josue Fernando Mendes Vieras
Zenodo (CERN European Organization for Nuclear Research)
Smart Cities and Technologies
article

SILVIA:Sovereign Information Learning Virtual Intelligent Architecture

Josue Fernando Mendes Vieras
article en

Abstract

This paper presents SILVIA (Sovereign Information Learning Virtual Intelligent Architecture), a federated Digital Twin framework designed for sovereign territorial data governance. Unlike conventional Digital Twin platforms that model constructed objects within institutional BIM workflows, SILVIA addresses living territories where the primary users are communities — including indigenous peoples, informal settlement residents, and conservation stakeholders — rather than technical professionals. The framework introduces four core contributions: (1) the Territorial Regeneration Index (TRI), a composite metric quantifying ecological, cultural, and socio-institutional regeneration grounded in Berkes (2008), Mang & Reed (2012), and Niemi & McDonald (2004); (2) a modular community-plugin architecture that allows the same core infrastructure to serve radically different territorial contexts through interchangeable knowledge bases; (3) an offline-first WhatsApp interface that enables data collection in environments without stable connectivity; and (4) a conceptualised inter-territorial semantic translation protocol that uses the TRI as a common measurement language between ecologically and culturally distinct territories. A proof-of-concept implementation demonstrates the framework across two case studies: Kanaimö (Pemón indigenous territory, Gran Sabana, Venezuela) and Caracas Metropolitan Area (informal urban settlements), with a third controlled case — a Munich residential building — under design for empirical validation of the Human Regeneration Index (HRI), a structural analogue of the TRI applied to the built environment. The system processes natural language observations via LLM, calculates TRI scores with community-specific weights, and generates an Obsidian-based knowledge graph whose density serves as a visual indicator of Digital Twin maturity. SILVIA operationalizes the CARE Principles for Indigenous Data Governance by embedding information sovereignty as a quantifiable variable (IIS) within the TRI formula itself, rather than treating data ethics as an external policy layer. This document includes an Executive Summary (page 0) followed by the full technical preprint. Proof of Concept Public release: https://youtu.be/ZgWuc1AAr_4?si=UBGSnHfwDQPViVlD GitHub Open Code: architect-josuemendes/SILVIA Keywords: Digital Twin, federated architecture, territorial governance, CARE Principles, indigenous data sovereignty, Territorial Regeneration Index, knowledge graph, informal settlements, WhatsApp, LLM, Pemón, Gran Sabana, inter-territorial semantic translation, Human Regeneration Index

Zenodo (CERN European Organization for Nuclear Research)
Sustainable cities and communities
Openalex Percentile: Top 7%
Smart Cities and Technologies
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