When Vivian Chan was studying for her PhD in Biochemistry, she encountered a problem that most scientists have confronted: how can you keep yourself updated with the enormous amount of new research that is being published every day? In fact, for scientists, it is getting increasingly difficult to remain updated with the latest developments in their own field of expertise. Generally, nowadays it has become the norm to read journal articles, RSS feeds, and email updates every morning, thus missing updates on a single day can make it very overwhelming for an individual researcher.
To overcome this issue, Chan built her own unique solution, Sparrho, which is a science recommendation engine that looks like a familiar social networking or news aggregation site. Sparrho combines the power of machine and human intelligence to find recommendations and aims to make the process of finding new, relevant research within your field of interest easy as possible. Sparrho’s database includes updates on journal articles, grant announcements, patents, to conference proceedings and so on, which helps researchers see everything they require in one place.
Channels and Pinboards
Sparrho’s clean look and user interface has been inspired by popular social networking platforms. While using Sparrho, a user can search for keywords or journal titles, the results of which can be saved as personal channels. In this manner, users can have access to a number of personal channels and Sparrho updates these channels hourly such that the newest content is present at the top. Sparrho also allows users to save and share useful articles using pinboards, which can be private and used to collect articles for personal use, or can be shared with colleagues or interest groups such that users can collaborate, run virtual journal clubs, or simply share interesting studies.
The Discovery Engine
Sparrho used a discovery engine that uses natural language processing to develop a semantic understanding of each user and their requirements such that channels and news feeds are truly relevant and offer useful results. This engine can search and categorize over 45,000 journals every hour. Sparrho personalises channels and feeds even further by tracking the interaction of users, as well as identifying what they share, read, and save. This allows the discovery engine to identify overlapping interests and show results that may be useful based on these interactions. Sparrho also offers users to rate individual results as relevant or not relevant, so with increase in usage, it is able to give better and relevant suggestions to its users.
Sparrho aims to create a revolution by democratising science and disrupting traditional disciplinary boundaries. Unlike Scizzle and PubChase, which are platforms similar to Sparrho but focus on life science, Sparrho includes suggestions from multiple disciplines and data forms. Thus, Sparrho allows researchers to easily find novel and important research as well as offer a brand new, user-friendly, and exciting way to do better science.
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