SciBite Search: Next-generation scientific search & analytics platform

Cambridge, UK March 31, 2021 – SciBite, an Elsevier company and award-winning semantic technology company, today announced the launch of SciBite Search. The next-generation scientific search and analytics platform offers powerful interrogation and analysis capabilities across unstructured and structured data, from public and proprietary sources. Researchers today face increasing challenges around accessing and deriving meaningful insights from the ever-larger volumes of data, presented in an array of formats from multiple sources. SciBite Search provides scientists with access to domain specific ontology and AI-powered search capabilities, allowing users to connect and build knowledge from their data.

“Biopharmaceutical companies depend upon access to and understanding of data to advance R&D. Yet today, many data assets remain siloed,” commented Phil Verdemato, Head of Software Engineering, SciBite. “Compounding this issue, is unlike other industries where it is simply the amount of data that is the problem, it is also the variety of data streams in life sciences that presents a barrier. This makes harmonization and comparison an uphill battle unless intelligent, purpose-built search tools are in place. The expertly tuned scientific search engine, SciBite Search, helps organizations address this and tackle the ‘Find’ aspect within the FAIR guiding principles for data management and stewardship.”

SciBite Search goes beyond traditional search methods, using knowledge graphs to augment searches and deliver not only items relevant to the query but the structure and relationship between them. The addition of AI further enhances the search experience enabling natural language understanding. SciBite Search can integrate data across a range of use cases including:

• Unify multiple data sources into a single solution, designed for departments wanting their own tailored search tool. For example, combining public biomedical literature, clinical trials, and grants with proprietary data to facilitate smarter searching.
• Incorporate full-text biomedical literature from publishers to better address researchers’ discovery needs. For example, users can load subscribed licensed data from partner publishers or content brokers.
• Enable users to get accurate search results without the need to understand the complexities of Named Entity Recognition (NER), its underlying data structures, or the functions required to surface.

Building on the easy-to-use search system in DOCstore, SciBite Search offers an intuitive user interface, and sophisticated query and assertion indices created using SciBite’s tools and ontologies. A streaming load API, connectors, and parsers for different sources and content types make it simple to load and process content to make it searchable.

Learn more about SciBite Search

About SciBite

SciBite’s data-first, semantic analytics software is for those who want to innovate and get more from their data. Leading the way by pioneering the combination of the latest in machine learning with an ontology-led approach, SciBite’s semantic infrastructure answers business critical questions in real time by releasing the value and full potential of unstructured data.

Supporting the world’s leading scientific organizations with use-cases from discovery through to development, SciBite’s suite of fast, flexible, deployable API technologies empower customers, making it a critical component in scientific, data-led strategies.

About Elsevier

As a global leader in information and analytics, Elsevier helps researchers and healthcare professionals advance science and improve health outcomes for the benefit of society. We do this by facilitating insights and critical decision-making for customers across the global research and health ecosystems.

Elsevier is part of RELX, a global provider of information-based analytics and decision tools for professional and business customers. www.elsevier.com