Metadata Processing

The Posters.science platform uses advanced AI-powered processing to automatically extract, validate, and enrich metadata from scientific posters. This ensures FAIR compliance and optimal discoverability.

AI-Powered Extraction

Content Analysis Pipeline

Features

High-Accuracy Text Recognition: Advanced OCR for poster text extraction
Multi-language Support: Recognition of various languages and scripts
Layout Preservation: Maintains document structure and formatting
Image Processing: Handles charts, graphs, and visual elements

Natural Language Processing

Entity Recognition: Automatic identification of authors, institutions, and dates
Topic Classification: AI-powered subject categorization
Keyword Extraction: Automatic keyword and phrase identification
Abstract Summarization: Content summarization and enhancement

Processing Workflow

1. Initial Extraction

File Analysis: PDF structure and content analysis
Text Recognition: OCR processing and text extraction
Layout Detection: Section and element identification
Quality Assessment: Content completeness evaluation

2. Entity Recognition

Author Extraction: Name and affiliation identification
Institution Detection: Organization and department recognition
Date Parsing: Publication and event date extraction
Location Identification: Geographic and venue information

3. Content Analysis

Topic Classification: Subject area determination
Keyword Generation: Automatic keyword extraction
Abstract Enhancement: Content summarization and improvement
Reference Parsing: Citation and bibliography analysis

4. Validation and Enrichment

Data Validation: Format and completeness checking
External Lookup: ORCID, DOI, and database integration
Standardization: Controlled vocabulary mapping
Quality Scoring: Metadata completeness assessment