Semantic technology company SciBite, an Elsevier company, has announced the launch of its next-generation scientific search and analytics platform, SciBiteSearch. The platform offers powerful interrogation and analysis capabilities across unstructured and structured data, from proprietary as well as public sources. Researchers are currently facing challenges around accessing and deriving meaningful insights from the ever-larger volumes of data, presented in an array of formats from multiple sources. SciBiteSearch offers scientists access to domain specific ontology and AI-powered search capabilities, allowing users to connect and build knowledge from their data.
Biopharmaceutical companies depend access to and understanding of data to advance R&D. Yet today, many data assets remain siloed, notes 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 harmonisation and comparison an uphill battle unless intelligent, purpose-built search tools are in place. SciBiteSearch is expertly tuned to address this and tackle the 'Find' aspect within the FAIR guiding principles for data management and stewardship.
SciBiteSearch 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.
Building on the easy-to-use search system in DOCstore, SciBiteSearch 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.
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