{"id":5087,"date":"2016-12-13T09:15:50","date_gmt":"2016-12-13T09:15:50","guid":{"rendered":"https:\/\/clarivate.com\/?p=5087"},"modified":"2025-08-07T15:29:38","modified_gmt":"2025-08-07T15:29:38","slug":"web-of-science-big-data-blooms-in-bloomington","status":"publish","type":"post","link":"https:\/\/clarivate.com\/academia-government\/blog\/web-of-science-big-data-blooms-in-bloomington\/","title":{"rendered":"Web of Science Big Data Blooms in Bloomington"},"content":{"rendered":"

This November, we had the opportunity to partner with the KnowledgeLab at the University of Chicago<\/strong><\/a>\u00a0and the\u00a0I-School of Indiana University<\/strong><\/a> to host a workshop with over 40 of our colleagues and customers to discuss research approaches to using our data. More than\u00a08,500 scholarly\u00a0articles based on Web of Science data have been published in the\u00a0past 15 years by researchers in myriad fields; and with the recent explosion in big data technologies, this trend is sure to continue. Working with these researchers on\u00a0ways to improve both our data services and their research was the inspiration for the\u00a0event.<\/p>\n

Attendees joined us from all over North America and as far away as Switzerland and Poland for two days of discussion, presentations, networking, and hacking with Web of Science data. The attendees included representatives from top university big data research labs, Key Opinion Leaders, development partners, and our expert colleagues. Check out our ‘lighting talks’<\/a> covering in-depth look at the history of, and technology powering, Web of Science.<\/p>\n

The second day was really the highlight with the\u00a0Hackathon<\/strong>. We provided everyone with a custom Web of Science dataset<\/a> for the event and split up into small teams to focus on digging into the data. The teams dove in and brought all kinds of tools to bear on the dataset including data analytics and compute power using both the KnowledgeLab Data Enclave and the IU secure data desktop as well as visualizations in commercial tools like\u00a0Tableau<\/a>. In the collaborative spirit of the event, folks were sharing their own custom code from\u00a0GitHub<\/a>\u00a0and immediately realized how much time they could save each other by sharing tools and approaches to things like disambiguation, recommendations,\u00a0similarity metrics,\u00a0SQL schemas,\u00a0XML parsers,\u00a0matching IDs,\u00a0gender identification, and\u00a0data format conversions.<\/p>\n

We had wide-ranging discussions on many topics throughout the workshop, but the following stand out as perhaps the top takeaways and most interesting food for thought:<\/p>\n