Get there faster
Artificial intelligence is driving R&D’s digital transformation and data is what fuels it. Better data, better outcomes — faster to market, faster ROI, lower risk.
As your R&D data, technology and services partner, Elsevier offers flexible options to:
Support the digital transformation of your processes and workflow
Structure and enrich your
Amplify your data with a vast pool of rich scientific data
Integrate your data with Elsevier
and third-party data
Empower teams with fit-for-purpose
platforms and tools
FAIR data packages
New datasets to boost R&D capabilities are on the horizon. Applying the power of SciBite semantic analysis, Elsevier will license FAIR data packages, starting with FAIR Journal Literature. Additional flexible options for licensing other solutions content will follow.
These unique data opportunities result from Elsevier's acquisition of SciBite in August 2020, which combined SciBite's expertise in semantic AI with Elsevier's deep data in STEM domains.Learn more about FAIR data
Transform your data, unlock potential
Your data shouldn't limit how you innovate and achieve your goals.
Managing data at scale is in our DNA. As the largest global provider of scientific, technical and medical information, Elsevier has been transforming content into usable data for decades. Now with the power of the SciBite suite of semantic solutions, we can work with you to build your data infrastructure and unlock your data potential. This includes applying FAIR data principles, which we helped to co-author and promote.
When unstructured scientific text is transformed into clean, contextualized data, you can feed a range of artificial intelligence applications.
Work with a partner who can help you develop, manage and apply:
- Machine learning and deep learning models
- Text analysis and extraction
- Ontologies, vocabularies and thesauri
- Knowledge graphs
- Semantic enrichment and annotation
Learn more about digital transformation, data and services within your industry:
Great data powers success
What data are you missing? Draw from the largest corpus of trusted scientific data in the world, extracted from a variety of sources, including peer-reviewed, full-text literature. This data is used as vital inputs in training algorithms, knowledge graphs and other applied analytics.
Data pools and sources include:
Biological entities and relationships
Chemical structures, properties and reactions, experimental data, bioactivity data and patents
Drug safety, pharmacokinetic and metabolizing enzyme and transporter data, and efficacy data
Conference abstracts and proceedings
Multidisciplinary engineering content, including property and materials data
Geospatial maps and geoscience data
Full-text literature and book content, images and citations
Opinion leader and affiliation profiles
R&D productivity soars
Your team members need best-in-class tools to help find the right information at the point of need. When this process is fast and accurate, they are empowered to make timely decisions that increase ROI. Discover platforms and tools that combine high-quality data, optimal user experience and AI-enabled features.
- CENtree — enterprise-ready ontology management
- TERMite — named entity recognition and extraction engine
- SciBiteSearch — scientific search and analytics platform
- SciBiteAI — prepare, train and deploy deep learning models
- ScienceDirect — world’s premiere STEM knowledgebase
- Scopus — expertly curated abstract and citation database
Chemical and biomedical
- Reaxys — a chemical database and cheminformatics solution
- Embase — the comprehensive biomedical research database
- PharmaPendium — drug safety and risk assessment resource
- Biology Knowledge Graph — biological entities and relationships
Engineering and geosciences
- Knovel — engineering references, data and interactive tools
- Geofacets — geoscience data and maps from scientific publications
- Engineering Village — 14 engineering literature and patent databases
Deep domain knowledge and expertise
Our team of highly credentialed domain and data experts have backgrounds that span:
- Biology and bioinformatics
- Chemistry and cheminformatics
- DMPK and safety/toxicology
- Energy and natural resources
- Data science and analysis
- Knowledge management
Elsevier’s parent company, RELX, makes significant investments to enable its businesses to help customers make better decisions, get better results and be more productive.
data scientists and data analysts
annual technology spend
Elsevier domain experts work on product innovation and customer initiatives. People like:
Matt Clark, Senior Director, Scientific Services
Matt has a PhD in chemistry and spent his early career working in translational medicine and bioinformatics at AstraZeneca, Pharmatrope and BioFortis. As a consultant in Elsevier’s Professional Services team, he has collaborated on projects to help pharma companies accelerate discovery via data integration and applied analytics.
John Skero, Director of Product Management, Engineering
John has a degree in Geological and Earth Sciences/Geosciences and was a top 10% performer at the ExxonMobil Upstream Research Center. He worked for 12 years in exploration and development before joining Elsevier where where he helped companies such as ExxonMobil, Woodside Energy, and Ecopetrol transform their business models with data.
Maria Shkrob, Life Sciences Consultant, Professional Services
Maria has a PhD in molecular biology and worked in biomedical research with Evrogen on new applications of fluorescent proteins and at Ariadne Genomics. At Elsevier, she has worked on bioinformatics and text mining tools, and now applies her rich background to helping to solve customer research challenges.
Partnering with the R&D community for greater impact
Is your company ready for Industry 4.0?
The process of transitioning to Industry 4.0 involves getting connected, maximizing data and implementing standards and best practices. See how chemical companies are transforming.
Unlocking the value of geoscience data
Elsevier is working with BHP to create a geoscience portal that will make their proprietary data discoverable alongside other relevant research and data, enabling a rapid response to new opportunities.
A collaboration with pharma to predict DDIs
Collaborating with Boehringer Ingelheim, Eli Lilly and Company, Pierre Fabre, Sanofi, Servier and others, Elsevier enhanced its drug-drug interaction risk calculator within PharmaPendium.