DISQOVER for Research, developed by ONTOFORCE, is a software-as-a-service (SaaS) platform designed to accelerate research and development in the life sciences sector. It integrates and harmonizes both public and private data sources using an ontology-based knowledge graph, enabling advanced semantic search, filtering, and data visualization. The platform supports scientific researchers in accessing, analyzing, and comparing complex datasets, thereby streamlining the drug discovery process and facilitating data-driven decision-making.

Key Features

Integrated public and private data Combines diverse data sources into a unified, high-quality knowledge base.

• Links and structures siloed data from internal and external sources.
• Supports integration with electronic lab notebooks (ELNs) and other research systems.

Advanced filtering and semantic search Enables precise and efficient data discovery.

• Utilizes AI-based semantic search and natural language processing.
• Allows complex queries and advanced filtering for targeted results.

Automated alerts and result tracking Keeps researchers informed of new developments.

• Sends alerts when new results matching saved criteria appear.
• Enables following, saving, and rerunning data links.

Data export and comparison tools Facilitates downstream analysis and collaboration.

• Exports harmonized data for further analysis or AI/ML applications.
• Provides tools to compare datasets and research findings.

User-friendly interface and LLM-based assistant Empowers researchers with intuitive tools and AI support.

• Easy-to-use dashboards and visualization tools.
• LLM-based assistant for natural language search and summarization.

Benefits

Accelerated research timelines Reduces time spent on data integration and manual analysis.

• Streamlines access to relevant data and insights.
• Supports faster hypothesis generation and validation.

Improved data quality and accessibility Transforms fragmented data into a cohesive resource.

• Enhances data reliability and consistency.
• Makes complex data accessible to non-technical users.

Enhanced collaboration and innovation Facilitates cross-functional teamwork and knowledge sharing.

• Centralizes research data for collaborative analysis.
• Supports innovation by uncovering hidden connections and trends.