Science Live Pipeline

Science Live Pipeline#

Breaking Down Silos to Accelerate Knowledge Transfer#

Science Live Pipeline is a semantic knowledge exploration platform designed to address one of the most pressing challenges in modern research: knowledge silos that prevent effective collaboration and discovery across disciplines, institutions, and research domains.

Note

The Silo Problem: Valuable scientific insights often remain trapped within individual research groups, institutions, or disciplines, limiting the potential for breakthrough discoveries and collaborative innovation.

What You Can Do With Science Live#

Ask questions in natural language and get structured scientific insights:

  • “What papers cite the original transformer paper?” → Get citation networks

  • “Who are the key researchers in CRISPR gene editing?” → Discover expert networks

  • “What measurements exist for graphene conductivity?” → Find experimental data

  • “How do climate models connect to biodiversity research?” → Explore cross-domain links

Quick Start#

Get Science Live running in 2 steps:

  1. Installation

git clone https://github.com/ScienceLiveHub/science-live-pipeline

pip install -e ".[dev]"

  1. Basic Usage

# Quick setup for experimentation
import asyncio
from science_live.pipeline.pipeline import quick_process

async def quick_explore():
    # This creates a test environment automatically
    result = await quick_process(
        "What papers cite AlexNet?",
        endpoint_manager=None  # Uses petapico endpoint automatically
    )
    print(result.summary)
    return result

# Run in script
result = asyncio.run(quick_explore())

# Or in Jupyter notebook, use:
# result = await quick_explore()

The Science Live Approach#

Breaking down research silos requires a systematic approach to knowledge transformation:

        graph TD
    A[Research Silos] --> B[Semantic Integration]
    B --> C[Knowledge Graphs]
    C --> D[Collaborative Discovery]

    E[FAIR Principles] --> B
    F[Nanopublications] --> B
    E --> C
    F --> C

    style A fill:#ffcccc
    style D fill:#ccffcc

Science Live addresses the silo problem by:

  1. Leveraging proven standards (FAIR Principles, Nanopublications) to structure scientific knowledge

  2. Enabling semantic integration that makes research outputs machine-readable and interconnectable

  3. Building knowledge graphs that reveal hidden connections across research domains

  4. Facilitating collaborative discovery through natural language exploration of the scientific record

Built on Proven Standards#

  • Nanopublications: Structured scientific claims with provenance

  • SPARQL: Industry-standard semantic web queries

  • FAIR Principles: Ensuring data findability and reusability

  • Rosetta Statements: Standardized scientific claim representation

AI-Powered Processing Pipeline#

Science Live transforms natural language questions into structured scientific insights through a 7-step AI pipeline:

Question → Intent → Entities → Statements → Queries → Results → Answers

Each step applies domain-specific AI to ensure accurate, contextual scientific knowledge discovery.

Learn the complete pipeline →

Community & Support#

Science Live Pipeline is developed as an open-source project with contributions from researchers and developers worldwide.

Citation#

If you use Science Live Pipeline in your research, please cite:

@software{science_live_pipeline,
  title = {Science Live Pipeline: Breaking Down Silos to Accelerate Knowledge Transfer},
  author = {Science Live Team},
  year = {2025},
  url = {https://github.com/ScienceLiveHub/science-live-pipeline},
  version = {0.0.1}
}
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