The Health division of Wolters Kluwer, a leading global provider of information and point of care solutions for the healthcare industry, has announced its participation in Copyright Clearance Center’s RightFind™ XML for Mining service that will make it euasier for biomedical researchers to conduct compliant text and data mining across the full text of its professional healthcare journals.
“We’re pleased to participate in this service so that our customers and their researchers can conduct the critical deep data mining for drug discovery and medical research,” said Andrew Richardson, Vice President, Business Development, Health Learning, Research & Practice at Wolters Kluwer.
With the exponential growth of biomedical research globally, RightFind XML for Mining service from Copyright Clearance Center (CCC) solves an industry challenge to provide compliant, controlled access to the literature for important text and data mining needs. Now researchers can conduct extensive data mining in a solution that normalizes full text in XML format across publishers for import into their preferred text mining software. CCC provides its publishing partners with usage reports to support decision-making related to text and data mining as part of content-development strategies.
“What customers find compelling about XML for Mining is that it’s a single source for the peer-reviewed scientific content they need, provided in machine-readable form,” said Babis Marmanis, CTO & Vice President, Engineering and Product Development, CCC. “With the addition of Wolters Kluwer, our customers gain access to important medical journals that further improve their ability to identify novel insights across a comprehensive, growing corpus – advancing the progress of scientific research.”
XML for Mining is built on the RightFind platform, CCC’s unique suite of cloud-based workflow solutions that offer immediate, easy access to a full range of Scientific, Technical, and Medical (STM) peer-reviewed journal content. Using RightFind XML for Mining, commercial biomedical researchers create sets of full-text XML articles from millions of articles from thousands of peer-reviewed journals produced by over 40 STM publishers, and import these sets into their preferred third-party text mining software. They can identify articles associated with their research from publications to which they subscribe and also discover articles that fall outside of company subscriptions, providing the most complete article collection for mining.
