KNODE’s platform is designed to “help you better manage internal talent, promote your experts to the world, engage with outside collaborators, and manage and track your membership/faculty/staff,” according to its website. The company mines data “from millions of documents, including US Patents, PubMed Abstracts, NIH grants and clinicaltrials.gov records.” With the help of advance semantic mining and data processing algorithms, KNODE is able to create dynamic research signatures for millions of researchers, “describing their core areas of expertise, publication track record, authorship networks, and more.”

Wiley chose KNODE over other options because, as Sean Pidgeon, Wiley’s VP and director of research solutions, explains, “[B]y building a network that emphasizes the broad expertise of scientists rather than narrow measures based on the research literature, KNODE has created exciting opportunities to enhance the quality of collaborative research.”

Researcher Portals: A Growing Necessity

As recently as 2008, only a couple of researcher profiling systems were available to academe and the private sector. Many, such as Imperial College London’s Azeem Majeed, believe that for academic medicine, “[T]wo portals dominate—PubMed and Google Scholar. Physicians and medical academics tend to stick to these two portals, along with the websites of the main general medical and specialist medical journals.” As a recent article in Nature Biotechnology noted, “[R]ecent years have witnessed the development of several online services that enable not only the identification of key researchers in a certain field but also galvanize interactions among those researchers.”

Today there are tens of products in the marketplace and few major research organizations that haven’t adopted these products to enhance their productivity and visibility. Some systems have been developed by researchers or universities focused on meeting the needs of academe—and often these are available as either open source or collaborative ventures with other institutions. Others have developed from database vendors (such as Elsevier’s SciVal/Experts/Spotlight, ProQuest’s Pivot, and Thomson Reuters’ ResearcherID), and some linked to existing research portals (such as InfoEd Global’s GENIUS and ResearchGate). Google Scholar’s user profiles, LinkedIn, and other social networking systems are sometimes included in this category. In 2012, two U.K. searchers found that “use of LinkedIn and Academia.edu can help to raise the profile of peer-reviewed papers hosted in institutional repositories if links to the papers are provided in these popular services as this may enhance the Google ranking for the institutional repository.”

Canada’s Memorial University professor David Yetman has developed his own search system and sees the potential for these products to create a “Google of university research,” connecting researchers to each other as well as to governments, funding agencies, private sector partners, and others. However, today’s products are adding far more analytical capabilities than Google could ever freely supply. In a recent JISC Cetis report, Mark van Harmelen notes that “New forms of analytics are in development and use. These include research overlay maps, varying forms of altmetrics, semantic analysis and social network analysis. These offer to broaden the application of analytics by enabling new kinds of applications, for example understanding the relationship between areas of research or applying semantic knowledge management techniques.”

Although the risks of proper interpretation and forecasting still remain, sophisticated efforts are now underway to bring state-of-the-art technologies into this area—making the investment by research organizations all the more compelling. The Cyberinfrastructure for Network Science Center at Indiana University is working on five types of analyses: statistical analysis/profiling (leading to information on individuals or even countries, disciplines, and corporate giants); temporal analysis (allowing for a current snapshot or analysis over time for trends); geospatial analysis (mapping the careers/contributions by individual researchers, specific publications, or organizations or political/geographic area); topical analysis (studying the flow of information and new knowledge as it develops and grows); and network analysis (looking as core competencies and research contribution by individuals, groups, organizations, or other entities). Using visualization and other data mining techniques, research such as this promises even more advances in this area.