Wiley, one of the oldest and largest global academic publishers has been in business for over 200 years serving both professionals and scholars, with content focused largely on topics in science, technology, medicine and law. With more than 800 partner organizations, representing 2 million members, Wiley operates an online library, among many other platforms, which is housed on custom technology. The Wiley Online Library provides access to more than 18 million documents, including 6 million articles from 2,000 journals, 13,000 books, and 200,000 other reference articles, all supported by 6 million bibliographic references.
In 2012, Wiley partnered with the American Geophysical Union (AGU), a nonprofit corporation dedicated to furthering geophysical sciences, to create a flagship academic resource in earth, space and environmental sciences that required integrating all of AGU’s data and functionality into the Wiley Online Library. This contract represented Wiley’s largest revenue generating society-owned partnership in its history and posed a number of challenges:
Aggressive timeline. According to the contract, project goals, including providing AGU customers access to all licensed content, needed to be completed in four months, with just six weeks for actual development. No revenue could be earned until the content was published.
Massive data volume. Wiley had to migrate existing content, comprised of 160,000 articles from 21 journals, 33 virtual journals based on AGU index terms and 743 special sections in addition to customer, user, product, license and alert data. And, Wiley had to accommodate new content at a rate of 400 articles per month, as well as adjust to changes in workflow.
Complex search requirements. The project required a search engine capable of working quickly and supporting content search across a range of index terms and special sections.
Multiple content formats. Because articles and journals were not standardized, many articles had no issue or page numbers, and journals came in an assortment of formats, including issues with multiple subsections or special editions.
I have a long history with MarkLogic, ever since they first came to us do a presentation on their company 10 years ago, and have been impressed with them ever since. I’m really pleased that I helped Wiley make the decision to use MarkLogic many years ago, and that decision continues to pay off.
From 2005, Wiley had been using MarkLogic as its content database, and as an XML store, search engine and for content modeling for its Online Library product since 2010. MarkLogic was a natural choice as the platform to power its partnership with AGU, enabling content developers to package and deliver their content in any desired format, on all types of devices. MarkLogic gave Wiley the capability to quickly package and deliver content in XML format, easily add new markup to support complicated queries, transfer content, and continue to accommodate new content as it arrived.
MarkLogic’s platform provided Wiley with a reliable foundation to successfully deliver on its project goals and earned the Wiley team Wiley’s President Award for Excellence, IT Project Team of the Year award at the UK IT Industry Awards and MarkLogic’s Customer Excellence Award. Benefits included:
Quick time to market and revenue. Wiley was able to publish AGU’s entire corpus of information (160,000 articles from nearly 800 data sources) in just 4 months—meeting its contractual obligations and delivering this content to its more than 60,000 customers and users. Revenue was recognized as soon as the new content was available on January 1, 2013.
Operational efficiencies. Both prior to and post-launch MarkLogic offered troubleshooting, auditing and reporting capabilities allowing Wiley to meet project milestones, recognize revenue more quickly, improve content quality, and identify bottlenecks that led to resource reallocation.
Rapid development. Leveraging its previous MarkLogic investment, Wiley enabled the 60+ enhancements that mirrored the AGU site functionality in just 6 weeks. Built in search with native indexing was a time saver as content was loaded. Reusing saved search and vocabulary services and out of the box faceting reduced developer effort.