We’ve completed our NSF Grant! UCSF Profiles and its use by external partners

INTRODUCTION

UCSF Profiles is an example of a Research networking system (RNS). These systems provide automated aggregation and mining of information to create profiles and networks of the people that make up an academic institution. RNS’s have in effect, become a new kind of ‘front door’ for the university, providing access to the university’s intellectual capital in a manner previously unattainable — i.e. one focused on expertise rather than schools or departments, thus intermingling experts regardless of where they’re officially housed. Against this backdrop, we wanted to understand how such a tool might enhance access to academic expertise by external partners, specifically industry, and improve UCSF’s response to industry interest.

METHODS & RESULTS

To this end, we assessed the usage of UCSF Profiles by commercial entities in the biotech, medical device and pharmaceutical industries to understand both how the tool might be used to enable industry-academic interactions in general, and then get a snapshot for UCSF of the nature of industry interest in our faculty.

We systematically derived a list of 111 unique biomedical-related companies with identifiable IP addresses who viewed individual faculty profiles. In one year, biomedical companies viewed 2,618 UCSF profiles (between July 1, 2013 and June 30, 2014). Profiles were viewed one or more times by one or more users by one or more companies on that list. By Sept 2014, 2318 individuals were still at UCSF representing roughly 35% of all profiles on UCSF Profiles as of September 2014.

We found that researchers were viewed across the spectrum of seniority, with slight increases by seniority from postdocs and residents to assistant professors, associate and full professors. Professors accounted for 53% of the pageviews from companies, and 64% (790 of 1244) Professors were viewed at least once by at least one company during the year. Although Professors were most viewed, a significant number of more junior assistant professors (39%, 381 of 972) and postdocs (31%, 326 of 1055) were viewed. Again, in terms of depth of interest, clearly individual professors got more pageviews on average than junior researchers (professors averaged 6.34 pageviews, associate professors 4.17, assistant professors 3.38 and postdocs 1.39)

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We then sent a short email survey to all those that were viewed by industry as defined above in the past year. The survey assessed the following:

  • whether the individual viewed had a prior relationship to the company or not, to establish whether the tool was being used to view potential new collaborators for industry.
  • why they thought they might have been viewed by industry partners, to get an initial sense of areas of potential interest for industry viewing academic profiles online.

Of 2,304 faculty and trainees who actually received the email survey (no bounces), 718 responded, a 31% response rate. Of those who responded, 237 (33%) had a prior relationship with the company who contacted them. Thus, the majority of views (481 of 718, or 67%) were for researchers that had no prior relationship with the company.

We also asked if the researcher was contacted by the company that viewed them. We found that 230 (33%, the similarity in numbers is a coincidence) were contacted by 1 or more companies. Professors who were viewed had a higher chance of being contacted (27% of viewed professors were contacted) than those more junior (24, 17 and 11% respectively of Associate, Assistant and Postdocs, respectively).

Since our goal was to enable support of faculty to prepare them for industry interest and/or to enhance the chance that a meaningful relationship develop, we were most interested in those without prior relationships. Of the 481 that had no prior relationship, 83 (17%) of these were contacted. Though we do not know how the contacts went, we are working on a process for the industry alliances office to get reports based on these data on a regular basis so they can follow up individually.

ANALYSIS, DISCUSSION & PRACTICAL APPLICATIONS

Finally we analyzed user reports describing their sense of why industry would have been interested in viewing their profile and contacting them. This information provides guidance on elements of user profiles that can be enhanced in the future to improve engagement with industry partners as well as provides insights for follow-up from the relevant institutional office. We categorized responses under one of six buckets:

  1. interest in research collaboration
  2. interest in specific technology
  3. recruiting
  4. sales or other commercial interest
  5. don’t know
  6. other

Not surprisingly most faculty thought the industry interest was based on their research (308 out of 716, 43%), and mostly, they thought, via a publication. Some but only a few thought it arose from their own prior collaboration with industry (63 out of 716, 8%) and a few specifically suggested a specialized technology from their lab could be of interest (22 out of 716, 3%). Many did not know why industry had been interested in their profile (128 out of 716, 17%) providing a key group to help and support in understanding the commercial implications and potential health impact of their work.

A key goal for this project was to enable UCSF to improve how we support the formation of industry-academic collaborations. We worked closely with the institutional offices that manage these relations and want to improve how they identify those that may need targeted help. We discussed tools & approaches and we are working to establish a regular process for reporting to enable this improvement.

Examples include:

  • Providing input on emerging scientists with research of value to industry. The junior faculty that did not have prior industry relations are an especially key subgroup that would otherwise not rise to the attention of industry alliances offices.
  • An overlay of those viewed by industry with length of time at UCSF could provide a shortlist of those who may have activities of interest for industry collaboration and be less likely to have information about efforts at the university that can facilitate those interactions
  • The companies found viewing faculty profiles can be compared to those who are establishing contracts to understand and potentially engage companies that show interest but haven’t converted into specific alliances.
  • Programs such as the Early Translational Research program can use regular reports based on the analyses we modeled to send targeted solicitation of research proposals that may require support to advance (often when the faculty member themselves may not be aware of this).
  • Programs can use identified faculty who are of interest to industry for focus groups or other forums to further customize programs.
  • Detailed company-specific data can be generated to enable the industry alliances office to build more effective partnerships.

Want more details?  Let us know!  We have lots more data that we can share if your interest is piqued. Send inquiries to profiles@ucsf.edu

SEO for Research Networking: How to boost Profiles/VIVO traffic by an order of magnitude

"Redwoods" by Michael Balint (cc-by)

The UCSF Profiles team has increased site usage by over an order of magnitude since the site’s big campus-wide launch in 2010. This “growth hacking” cheat sheet distills the key lessons learned during that period, and can be applied to almost any research networking platform, including VIVO, Profiles, and home-grown solutions.

1. Measure Everything

  • Install Google Analytics
    • Set it up on every page of the site
  • Learn how to use it
  • Segment on-campus vs. off-campus use
    • Find your “service provider” name(s) at Audience > Technology > Network
    • Create an advanced segment that includes only your service provider(s), and one that excludes it/them
    • Use these two segments to analyze everything (internal and external visitors are totally different, and need to always be analyzed separately)
  • Register with Google Webmaster Tools
    • Go to google.com/webmasters/tools
    • Follow the directions to register your site
    • See how your site’s indexed on Google, and check for issues
  • Check the Recommendations for RNS Usage Tracking

2. Ignore Your Homepage, Focus on Profile Pages

  • On a mature search-optimized RNS like UCSF Profiles, only 2.6% of visits start on the homepage
  • If you’re successful with steps 3-4, traffic directly to profile pages will skyrocket, and dominate traffic. That means you need to focus most of your attention on the care, feeding, and design of profile pages, vs. the home page.

3. Search Engine Optimization (SEO)

  • Make sure search engines can see your pages
    • Tweak your robots.txt so search engines can see all your pages (robotstxt.org)
    • Create a dynamically-generated sitemap of all your profile pages (sitemaps.org)
    • Mention your sitemap in your robots.txt file, and then register it with Google Webmaster Tools
    • Wait a day, use Google Webmaster Tools to validate that your sitemap works
  • Improve the copy on your profile page titles and descriptions
    • Make the page <title> on profile pages short and globally unique
    • Make <meta name=”description”> on profile pages readable and descriptive
      (e.g. “Jane Doe’s profile, publications, research topics, and co-authors”)

4. Add extra professional metadata

  • Follow the directions at schema.org and schema.org/Person to add people-oriented HTML metadata to your profile pages
  • Use google.com/webmasters/tools/richsnippets to test your syntax
  • OPTIONAL: Use “pretty” URLs — and include names if possible (e.g. http://www.yoursite.edu/firstname.lastname)
    • Pretty URLs should be the “real” final URL, not just a redirect
    • All old or alternative profile URLs should do a 301 redirect to the pretty URL
  • OPTIONAL: Prevent indexing of multiple versions of your page
    • If you have multiple versions of your page getting indexed (e.g. /url/ vs. /url/?a=b), tell search engines which version is the main one by using the rel=canonical canonical link element

5. Get Inbound Links

  • Get webmasters to link to your homepage from campus resource guides, etc.
  • Get webmasters to link to individual profiles from departmental faculty profiles, news stories, campus directory, etc.
  • Encourage reuse of your data via APIs, and ask for a link back as attribution (downstream users save time and money; you get links back in return)
  • All these new links may not send traffic, but will help SEO.

Have questions? Suggestions? Leave a comment below, or contact Anirvan Chatterjee directly.

Photo credit: Michael Balint, used under Creative Commons attribution license

UCSF Profiles coauthorship networks, by degree

We’re using UCSF Profiles data to explore whether co-authorship networks are a good way to show the connections between researchers at UCSF.

We can start off by looking at immediate co-authorship connections. I was surprised at how few current UCSF co-authors most users have. The flip side of co-authoring widely outside of one’s institution is that there are fewer internal co-authors:

Avg # contacts, 1 degree away

The numbers jump when you go one degree further out, though the relative proportions are similar:

1 and 2 degree

The numbers grow further when we count first, second, and third degree coauthors.

1-3 degree contacts

My big takeaways are unsurprising:

  • The number of UCSF co-authorships generally grow with seniority — which may correlate with both the length of one’s career, as well as one’s tenure at UCSF
  • Even in the case of professors’ 1st-3rd degree, connections, we’re maxing out at 180 people, out of about 6,500 people in UCSF Profiles. This number may correlate to the size of one’s department/field at UCSF.
  • If we showed logged-in UCSF Profiles users a visualization showing “here’s how you know this person” when looking at another random user’s profile, it would kick in pretty infrequently — thought that might be different for folks in the same field/department

UCSF dentistry co-authorships, internal vs. external (by institutions)

What does a typical UCSF publication look like, in terms of the number of internal co-authors vs. the number of external co-authoring institutions? Here’s a breakdown among dentistry-related publications by UCSF researchers published in 2013. (This is the same analysis as yesterday, but looking at the number of external institutions, vs. the number of external people.)

Again, I was surprised to see so many co-authorships between a single UCSF researcher and one or researchers from one or more external institutions (the very top row of results), which accounts for 52% of the papers we looked at.

UCSF vs External Co-Authoring InstitutionsView as PDF

Method: I searched Web of Science for dentistry-related articles published between January 1-December 5, 2013. I began by running a search for any articles published in 2013 matching a number of dentistry-related keywords (dental, dentistry, electrogalvanism, endodontics, jaw relation record, mouth rehabilitation, odontometry, oral, orthodontics, periodontics, prosthodontics, teeth, tooth), then filtered only those that matched the “DENTISTRY ORAL SURGERY MEDICINE” Web of Science category. Web of Science automatically attempts to normalize institution names; in addition, I lumped all institution labels with names that start with “UCSF”, “UC San Francisco”, or “UCSF Sch ” to “Univ Calif San Francisco” as part of the main UCSF grouping.

UCSF dentistry co-authorships, internal vs. external

What does a typical UCSF publication look like, in terms of internal vs. external co-authors? Here’s a breakdown of each type of co-author, among dentistry-related publications by UCSF researchers published in 2013.

Three immediate take-aways:

  • I was surprised to see so many co-authorships between a single UCSF researcher and one or more external researchers — the very top row of results. By volume, this accounts for 52% of the papers we looked at.
  • When every author is internal to UCSF, there’s an average of 3.5 UCSF co-authors
  • When there’s an external collaboration, there’s an average of 2.0 UCSF co-authors

UCSF vs External Co-AuthorsView as PDF

Method: I searched Web of Science for dentistry-related articles published between January 1-December 5, 2013. I began by running a search for any articles published in 2013 matching a number of dentistry-related keywords (dental, dentistry, electrogalvanism, endodontics, jaw relation record, mouth rehabilitation, odontometry, oral, orthodontics, periodontics, prosthodontics, teeth, tooth), then filtered only those that matched the “DENTISTRY ORAL SURGERY MEDICINE” Web of Science category. Web of Science automatically attempts to normalize institution names; in addition, I lumped all institution labels with names that start with “UCSF”, “UC San Francisco”, or “UCSF Sch ” to “Univ Calif San Francisco” as part of the main UCSF grouping.

UCSF dentistry collaborations, mapped

Social network graphs are pretty, but they’re not the only way we can try to visualized cross-institutional research collaborations. Here’s a geographic view of some of the institutions that UCSF dentistry researchers have co-authored with over the course of 2013.

UCSF Dentistry Collaborations, Jan 1 - Dec 5, 2013 (World)

UCSF Dentistry Collaborations, Jan 1 - Dec 5, 2013 (USA)

UCSF Dentistry Collaborations, Jan 1 - Dec 5, 2013 (Europe)

Method: I searched Web of Science for dentistry-related articles published in 2013 (i.e. from January 1-December 5, 2013). I began by running a search for any articles published in 2013 matching a number of dentistry-related keywords (dental, dentistry, electrogalvanism, endodontics, jaw relation record, mouth rehabilitation, odontometry, oral, orthodontics, periodontics, prosthodontics, teeth, tooth), then filtered only those that matched the “DENTISTRY ORAL SURGERY MEDICINE” Web of Science category. I pulled out institution names, tried to geolocate them using the OpenStreetMap Nominatim service, and used Google Fusion Maps to put them on a map. This map is by no means authoritative, given that a significant number of institutions could not be trivially geolocated.

UCSF dentistry collaborations, visualized

Looking at cross-institutional co-authorship networks is a useful way of seeing not only who we work with, but also where there may be gaps of interest.

I first looked at dentistry-related publications by UCSF researchers published in 2013, breaking out the institutions we co-authored with. And there we are, sitting pretty in the center of our universe, collaborating with major institutions in the US, Korea, Australia, Italy, Denmark, and more.

(Details: Institution node sizes indicate the total volume of dentistry-related articles published. Connecting line widths indicate the number of articles co-authored between two institutions. Distance between nodes indicates the tightness of co-authorship networks, and different sets of node colors help distinguish groups of institutions whose researchers frequently co-author together. Of 462 institutions that collaborated with UCSF researchers, we’re showing only 91 that had 10 or more cross-institutional articles in that time.)

View full-size visualization (PDF)

UCSF dentistry research co-authorships, Jan 1 - Dec 5 2013

Then I looked at the total universe of dentistry-related publications published in 2013 (see below). Notice a difference? I have to admit that it took me a while to find UCSF in the mess of dots. (If you look at the full-size view, we’re in the medium blue section, next to the pinks.) Of course this says more about the sheer volume of research being published by universities all over the world, than about any lack of cross-institutionally collaborative spirit on our part; in fact I hid over 80% of the institutions in the first image to keep it readable, which accounts for a a good chunk of the difference. But the sheer weight of institutions from Europe, East Asia, and Latin America in this second image that aren’t there in the first is intriguing, and something I’m going to try digging into.

(Details: Institution node sizes indicate the total volume of dentistry-related articles published. Connecting line widths indicate the number of articles co-authored between two institutions. Distance between nodes indicates the tightness of co-authorship networks, and different sets of node colors help distinguish groups of institutions whose researchers frequently co-author together. Of 2,575 institutions that we found, we’re showing only 374 that had 10 or more cross-institutional articles in that time.)

View full-size visualization (PDF)

Dentistry research co-authorships, Jan 1-Dec 5 2013

(And yes, I realize fully well that I’m probably looking at the wrong things here, privileging increasing the count of cross-institutional collaborations as an end in itself, avoiding any consideration of research quality, and giving greater visual weight to institutions that publish more, regardless of the size of the institution or the quality of work. Pretty pictures lie can hide lots of flaws. I hope you’ll bear with me as I publicly iterate through these topics, step by step, hopefully getting just a little bit less dumb every time.)

Additional uninteresting details: I searched Web of Science for dentistry-related articles published in 2013 (i.e. from January 1-December 5, 2013). I began by running a search for any articles published in 2013 matching a number of dentistry-related keywords (dental, dentistry, electrogalvanism, endodontics, jaw relation record, mouth rehabilitation, odontometry, oral, orthodontics, periodontics, prosthodontics, teeth, tooth), then filtered only those that matched the “DENTISTRY ORAL SURGERY MEDICINE” Web of Science category.

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