Researchers around the world and across the chemical sciences rely on the articles published in top-tier journals to make vital advances. The volume of valuable information available grows hourly – and any part of it might be crucial to the next breakthrough.
This is why more and more organisations are tapping in to the opportunities offered by machine analysis to extract, pinpoint and apply insights from vast numbers of articles to their ongoing research. Machine-ready articles are feeding a future of greater knowledge and faster R&D.
To support this move towards digitisation, companies can now access the research in our journals in formats suitable for TDM and machine learning.
Increasing interaction between chemistry … other sciences, [and] fields such as … computer and materials sciences [has been] identified as the single most important theme for the chemical sciences over the next ten to twenty years.
How are industrial researchers using TDM?
Text and data mining has already been adopted by a number of large companies, and their projects are being used effectively to drive targeted, evidence-based R&D.
Discovery
Pinpointing the right content across the breadth of internal & external data sources
Data integration
Creating a master view of all accessible data, enhanced to add context and links
Project support
Accessing the right research and knowledge to address project needs
Modelling
Extracting data from documents to build new models
New knowledge
Inferring new knowledge from integrated and enhanced data resources
Depending on their local legal framework, researchers in academia may be permitted to carry out TDM on articles accessed via our article pages for non-commercial uses, and should check with their institution’s librarian.
Please contact us beforehand if you are planning a text mining project, as we will need to make sure the machine access doesn’t affect other users, or contradict our terms and conditions.
What can we provide?
We have made our full journals catalogue available for use with TDM and machine learning applications, supplied as XML with tables and accompanying images. Bulk delivery of archive material can be supplemented by secure delivery of new publications.
We have practical licensing options, and a dedicated data support team on hand to help with queries.
Industry sectors supported by the research we publish include:
| Agrochemicals and food chemistry | Battery and electrochemistry | Chemical analysis |
| Dyes, printing and inks | Emerging technologies | Energy, fuels and renewables |
| Glass, metals, ceramics and pigments | Green chemistry | Insulating materials |
| Petrochemicals and engineering | Pharmaceuticals | Polymers |
| Semiconductors and optical materials | Synthesis and speciality chemicals | Water treatment technologies |
Explore our research
Our infographic below shows the areas our publications covered throughout 2022.
Preparing for an integrated future
We are working towards a future in which science can be easily interrogated by machine applications as soon as it is published, to support the growth of chemical science knowledge.
Making our publications available as XML to our industry customers is the first step to achieving this.
Start a conversation with us
To learn more about accessing our full-text XML content for commercial TDM or machine learning, or to talk through any other data-related questions you might have, complete this form and we will be in touch soon.