Data Flow

Understand the transformation layers that turn raw web data into structured intelligence.

The Information Pipeline

Information in Lens is never just "scraped." It moves through a series of high-integrity transformation layers to ensure accuracy and relevance.

Ingestion

Collectors fetch raw bytes from source APIs (JSON, XML, or binary PDFs). This data is immediately stored in the local cache if enabled.

Normalization

Raw data is mapped to the internal ResearchItem schema. Fields like "pub_date" or "repo_url" are standardized to ISO-8601 and absolute URLs.

Refinement

The ResearchGraph is analyzed for duplicates. Cross-source items representing the same entity (e.g., a paper on both arXiv and Crossref) are merged into a single node.

Synthesis

The synthesis engine traverses the DAG to identify key clusters and generates the final summary report with full citations.

Data Integrity

Lens uses a cryptographic hash of the content to detect identical items across collectors, even when metadata (like titles) slightly differs.

python

# Pseudo-code for duplicate detection
def calculate_content_hash(item):
    # Normalize and hash the core technical content
    clean_text = normalize_whitespace(item.content.lower())
    return sha256(clean_text).hexdigest()

Architecture Complete

You've explored the entire technical foundation of the Lens engine.

Start Building Become a Contributor

Engine

Tutorials