“As partnership manager, I have the pleasure of working collaboratively with our growing network of partners and customers. Together we are building innovative solutions that extend our partners’ existing capabilities, deliver real value to our mutual customers and are chipping away at major data challenges within the life sciences.”
SciBite is a trusted industry leader in semantics and the application of ontologies to create clean, machine-readable data. Our tooling is already widely adopted within many top biotech and pharmaceutical companies. Our software infrastructure is specifically designed to integrate with ease into other applications, allowing us to work with some of the best names in the industry to provide an ever-extensive array of workflows and services.
Augmenting your application with SciBite’s semantic platform unlocks a wealth of opportunities for your customers to do more with that data and to support FAIR data principles. Partner with SciBite to deliver more value, whether it is by enabling full semantic search, FAIR data capture, advanced analytics and dashboards or new opportunities to mine the data more effectively with AI and machine learning applications.
A pioneer in voluntary collective licensing, CCC (Copyright Clearance Center) helps organizations integrate, access, and share information through licensing, content, software, and professional services. With expertise in copyright and information management, CCC and its subsidiary RightsDirect design and deliver innovative information solutions that power decision-making by helping clients integrate and navigate data sources and content assets.
Through our partnership with SciBite, CCC integrates SciBite’s award-winning semantic platform, hand-curated VOCabs, and Named Entity Recognition (NER) engine TERMite in our RightFind Insight and RightFind Navigate products. These integrations improve discovery and enhance the reading experience for customers. Also, through the combination of SciBite DOCStore and RightFind XML for Mining, clients can easily access, enrich and index full-texted XML articles from a wide range of scientific publishers.
“Our partnership with SciBite gives customers an unparalleled opportunity to experience the power of semantic enrichment and make published content more discoverable. Together we continue to make a great impact on important work in drug discovery, life sciences, and many other areas.”
Lauren Tulloch, Vice President and Managing Director, Corporate Markets at Copyright Clearance Center
The basis of the partnership between IDBS and SciBite is a common goal of maximising the utility of Electronic Laboratory Notebook (ELN) data. IDBS specialise in the capture and management of R&D data during biologics and drug discovery and development.
The partnership supports ontology backed data capture through the import of ontologies managed in CENtree into E-workbook, prospectively capturing data with a defined structure. Semantic enrichment of unstructured text and attached documents is also possible through a connection between E-workbook and SciBite Search. This enables full semantic search and analytics over legacy and other unstructured data, embracing FAIR and improving the search and usability of ELN data stored in E-workbook and Polar applications.
Managing data during the development and manufacture of precision medicines or crops is challenging. Data is generated at multiple stages of the process, and this flows between different tools, groups, and even organisations.
Through their Enterprise Science Platform (L7|ESP), L7 provides a platform to drive data intelligence and support data management, combining ELN, LIMS, Sample Management, Inventory, Electronic Batch Record (EBR), and dashboarding functionality into a single tool.
To support this complex data capture and management process, L7 builds and maintains data models using CENtree (SciBite's enterprise ontology management platform), leveraging public ontologies where possible and embracing FAIR. These data models in the form of ontologies are supplied to customers, and L7 customers use CENtree functionality through L7|ESP. Customers can modify and extend these models to fit the specific data and use cases, facilitating robust search and analytics.
“CENtree has a highly intuitive interface, was developed by scientists for scientists, and is based on the premise of collaboration and driving insight. This makes CENtree an ideal fit for ontology management within L7|ESP for delivering the industry-leading data plus intelligence platform in life sciences.”
Vasu Rangadass, CEO of L7 Informatics
Modak is a solutions company that enables enterprises to manage and utilize their data landscape effectively and provide technology, and cloud-agnostic software and services to accelerate data migration initiatives.
Modak uses machine learning (ML) techniques to transform how structured and unstructured data is prepared, consumed, and shared. Modak Nabu™ converges data discovery, ingestion, preparation, cataloging, unification, quality, and profiling into a single data engineering platform to provide Google-like metadata search across data repositories.
By automating mundane and laborious data preparation tasks, Modak Nabu™ significantly reduces the time taken to develop and deploy data pipelines across thousands of on-premise, cloud, and external data sources.
The integration of Modak Nabu™ with SciBite’s TERMite empowers customers with the ability to simplify TERMite annotations by possessing ready access through Modak Nabu™ to the data and integrate TERMite ontologies into standardized and harmonized data pipelines. Thus streamlining and accelerating the preparation of machine-readable and FAIR data.
“The Modak and SciBite collaboration will empower customers with a modern data platform to easily find, manage, and share data. SciBite’s ontology led approach and Modak Nabu’s data orchestration will fuel the scientific discovery with trusted data for life sciences organizations,”
Milind Chitgupakar, Chief Analytics Officer, and Co-founder, Modak.
Data overwhelms most life science organizations. It’s spread across siloed systems and is difficult to turn into usable information and insights. This friction slows processes, such as the development time for new drugs or devices.
Sinequa Intelligent Search platform helps Healthcare and Life Sciences organizations connect employees to the data, knowledge, and expertise in their work. Sinequa provides the unique ability to access content in all formats, securely and at scale across all sources. Scibite and Sinequa work in concert to enrich this data semantically and extract its meaning, allowing employees to surface relevant information and remove ambiguity.
“Relevant knowledge at the right time is priceless for our joint customers. SciBite's semantic expertise focuses our technology and enhances relevance to tame content chaos in the life sciences. Sinequa and SciBite team up for unbeatable relevance by combining intelligent search with domain-specific ontologies to surface insights from the vast ocean of scientific content to drive success for the top life science organizations."
Jeff Evernham, VP of Product Strategy
Knowledge Graphs are increasingly being used as a tool to navigate and extract insight from the huge volumes of scientific data being collected. Major challenges in the production of knowledge graphs are the scale of data being served and having machine readable and clean data to feed into the graph.
SciBite and Stardog are addressing these challenges together through partnership. SciBite provides the tooling to build an underlying data model based on ontologies and generates machine readable input for the graph, through the extraction and tagging of scientific entities and their relationships. Stardog provides a robust and highly scalable graph technology, allowing machine readable data to be queried and new and novel scientific insight extracted.
"SciBite’s relentless focus and expertise in semantic technologies enables our joint customers to move from concept to production in short order. Their solutions elegantly address the challenges of modelling domain specific information, integrating and harmonising vast amounts of unstructured data and helping deliver on the promise of FAIR data. The net result in every case is a fast-track to value."
Simon Gregory, VP, Global Alliances and Partnerships, Stardog
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