Results for: ontology

Suggested Categories:

Scientific Data Management System (SDMS) Software
Scientific data management systems (SDMS) are systems that manage all data related to a scientific lab, and include components such as data storage, data cataloging, document management, and more. Scientific data management systems can integrate with laboratory information management systems (LIMS) and electronic lab notebooks (ELN).
Data Management Software
Data management software systems are software platforms that help organize, store and analyze information. They provide a secure platform for data sharing and analysis with features such as reporting, automation, visualizations, and collaboration. Data management software can be customized to fit the needs of any organization by providing numerous user options to easily access or modify data. These systems enable organizations to keep track of their data more efficiently while reducing the risk of data loss or breaches for improved business security.
Data Modeling Tools
Data modeling tools are software tools that help organizations design, visualize, and manage data structures, relationships, and flows within databases and data systems. These tools enable data architects and engineers to create conceptual, logical, and physical data models that ensure data is organized in a way that is efficient, scalable, and aligned with business needs. Data modeling tools also provide features for defining data attributes, establishing relationships between entities, and ensuring data integrity through constraints. By automating aspects of the design and validation process, these tools help prevent errors and inconsistencies in database structures. They are essential for businesses that need to manage complex datasets and maintain data consistency across multiple platforms.
Data Integration Tools
Data integration tools help organizations combine data from multiple sources into a unified, coherent system for analysis and decision-making. These tools streamline the process of gathering, transforming, and loading data (ETL) from various databases, applications, and cloud services, ensuring consistent data across platforms. They provide features like data cleansing, mapping, and real-time synchronization, ensuring data accuracy and reliability. With automated workflows and connectors, data integration tools reduce manual effort and eliminate data silos, improving operational efficiency. Ultimately, they enable businesses to make better, data-driven decisions by providing a comprehensive view of their information landscape.
Semantic Layer Tools
Semantic layer tools provide a unified, business-friendly view of data across multiple sources, translating complex data models into easily understandable concepts and metrics. They allow business users to query, explore, and analyze data using consistent definitions without needing deep technical knowledge of databases or query languages. These tools sit between data storage and analytics platforms, ensuring alignment and accuracy in reporting. By standardizing key metrics like revenue, customer churn, or retention, they eliminate inconsistencies across dashboards and reports. Semantic layers empower organizations to democratize data access while maintaining governance, transparency, and trust.
  • 1
    Timbr.ai

    Timbr.ai

    Timbr.ai

    Timbr is the ontology-based semantic layer used by leading enterprises to make faster, better decisions with ontologies that transform structured data into AI-ready knowledge. By unifying enterprise data into a SQL-queryable knowledge graph, Timbr makes relationships, metrics, and context explicit, enabling both humans and AI to reason over data with accuracy and speed.
    Starting Price: $599/month
  • 2
    Sapio Scientific Data Cloud
    Sapio Scientific Data Cloud is a science-aware scientific data management system that unifies and contextualizes all your laboratory data, assay results, instrument outputs, archives, and third-party ELN/LIMS records into a single, searchable platform without any coding. It supports automated data capture and parsing from over 200 instrument adaptors, semantic search powered by ontologies, built-in charting, and advanced neural-network analytics (ANOVA, best-response curves, 4/5 PL curves, flow-cytometry gating), and AI-driven insights. Secure, role-based access and data archiving keep sensitive information safe, while protein, molecule, plasmid, and system-wide viewers let scientists explore results interactively. ...
  • Previous
  • You're on page 1
  • Next