Research
From historical documents to computational research
The project moves beyond digitization, cataloging, and transcription to build a scientific and computational infrastructure for studying colonial-era society in San Luis Potosí. It enables researchers to study thousands of sources at once, reconstruct PER–LOC–ORG networks, and identify historical structures that are difficult to see through exclusively manual procedures.
From documentary heritage to relational knowledge
The project brings together physical conservation and computational analysis to study historical newspaper collections and documentary heritage. Historical materials are stabilized, documented, and digitized before reproducible computational pipelines extract entities, normalize information, and connect actors, events, sources, and territories. These structured data are then modeled as relational and knowledge networks to reveal historical patterns, communities, and emerging narratives that are difficult to identify through individual document analysis.
From historical newspapers to a replicable digital methodology
The project develops a systematic workflow for preserving, digitizing, and facilitating the assisted reading of historical newspapers, using Estandarte as the starting collection. Controlled photographic capture and image preprocessing produce standardized digital pages prepared for GLIMPSE-assisted analysis, enabling the extraction of entities, editorial patterns, and temporal relationships. The resulting workflow is designed to be reusable across similar collections while also supporting conservation diagnosis and recommendations for preserving the original documents and their reproductions.
From dispersed artistic records to connected cultural knowledge
The project builds a digital information system that brings together information about artists, works, exhibitions, institutions, spaces, and territorial relationships connected to San Luis Potosí. Using structured metadata, controlled vocabularies, and specialized taxonomies, dispersed sources are normalized and validated within a shared repository. The resulting information supports the exploration of artistic trajectories, collaborations, places, and historical connections through public records, visualizations, narratives, and research-oriented data access.
From historical sources to patterns, connections, and new questions
An interdisciplinary research project that applies data science methods—including graph theory, natural language processing, and network analysis—to historical sources and documentary corpora. Combined with conceptual history (Begriffsgeschichte), these computational approaches help reconstruct the social, discursive, and relational structures that shaped the past, revealing patterns, connections, and transformations that can be difficult to identify through traditional methods alone. Rather than replacing critical interpretation, computational models extend it by generating new evidence and questions for historical research.