This site is remarkable in many ways. It brings together all the people, lifelong learning, and resources for the Life Sciences across Harvard and its affiliates.
In the People area, you'll find social networking for the research community called Profiles. . It not only shows traditional directory information, but also illustrates how each person is connected to others in the broad research community.
When you view a person's profile, three types of information are displayed:
1. Managed Descriptions
This is the typical information listed in a research profile, including name, titles, affiliation, phone number and email address. Faculty can edit their own profiles, adding publications, awards, narrative, and a photo.
2. Passive Networks
Passive networks are formed automatically when faculty share common traits such as being in the same department, working in the same building, co-authoring the same paper, or researching the same topics (as defined by the "MeSH" keywords assigned to their publications). The passive networks a person belongs to are shown on the right side of the page when viewing a profile.
3. Active Networks
Active networks are the ones that users define by choosing collaborators, advisors, or advisees. Currently, users can manage their own networks. In the future they will be able to share these lists with others.
The website is open to the general public. However, people with a Harvard Medical School login can access additional features, such as "active networking", described above.
All data shown by default on the website is currently available on other public websites, but Profiles integrates the data in novel ways. Directory information was obtained from the Harvard Whitepages, and publications and keywords were copied from PubMed. If faculty had previously entered awards and narratives in the Faculty Affairs CV/Promotion management application called FIRST, then that information can be displayed on this website, but only if those faculty approve it. Default photos are from Harvard IDs, but faculty must also approve the use of those before they are shown on this website. Lists of co-authors and similar people are derived automatically from publications, and the "department" and "neighbor" lists are determined automatically from directory information.
Keywords, co-authors, and list of similar people are derived automatically from the PubMed articles. Keyword rankings and similar people lists are based on complex algorithms that weigh multiple factors, such as how many publications users have in a subject area compared to the total number of faculty who have published in that area.
Breaking down silos in the research community at Harvard via social networking is a great first step toward catalyzing research acceleration. You'll see many new features and functions on this new website over the next year, so stay tuned!