UCSF researchers often work closely with one another, across departments. We used data from UCSF Profiles to visualize how different departments work together, based on co-authorship patterns.
Visualization details: Data is drawn from UCSF Profiles, and includes all publications co-authored by current UCSF researchers from two more departments and listed on PubMed. The size of each department corresponds with the number of publications that members have published that include partnerships with other departments. The width of the lines connecting departments corresponds to the number of publications between two departments. Colors indicate clusters of departments that often publish collaboratively, based on network modularity. No scaling is done to account for varying sizes of different departments.
Click to view full-size image
CTSI at UCSF has invested in increasing the usage and usability of UCSF Profiles, our research networking system. Based on our presentation at the 2012 IKFC meeting, here are our top 5 technical tips on how to increase the impact of your institution’s investment in research networking platforms, based on our past three years of work.
You can’t understand how you’re doing without measuring usage.
- Install Google Analytics, then learn how to use this incredibly powerful tool (make sure to segment on-campus vs. off-campus traffic by setting up advanced segments based on service provider)
- Register your site on Google Webmaster Tools to understand how search engines see your data
2. Optimize for search engines
UCSF Profiles gets over 50,000 visits a month. 72% of that traffic comes from search engines, primarily Google. Here’s how to increase traffic from search engines:
- Implement a sitemap containing links to all your people profile pages, and make sure Google sees it using Google Webmaster Tools
- Add a readable meta description (e.g. “Jane Doe’s profile, publications, research topics, and co-authors”) to your profile pages so they look better in search engine results
- Add Schema.org data about your people on people profile pages
- Advanced: use rel=canonical to prevent different versions of the same content from being indexed
3. Build inbound links
Linking is a critical way to both increase site traffic, and to signal importance to search engines.
- Get websites large and small at your institution to link to your site (two years after launch, there are over 100 websites at UCSF that link to one or more pages on Profiles)
- Encourage heavy linking to individual profile pages, e.g. from the campus directory, news articles, departmental profiles
4. Reuse data
Your research profiling system comes with APIs. Encouraging campus-wide reuse of this data can increase the impact of your investment. See opendata.profiles.ucsf.edu to see how UCSF is marketing this data.
- Learn how to use your system’s APIs, so you can share that experience with others
- Publicly document how the APIs work, and include sample source code
- Reach out to campus technologists and webmasters to demonstrate how easy it is for them to reuse your data (e.g. the inclusion of Profiles data in UCSF’s mobile app was the result of technologist outreach)
- Reach out to campus leaders to show them what kind of efficiencies they can gain by reusing your data (e.g. the inclusion of links to researcher profiles on the UCSF Directory was the result of a strategic partnership)
5. Extend with ORNG (advanced)
- Install ORNG (OpenSocial) into your copy of Profiles or VIVO
- Add new apps from the ORNG library of free apps
Good luck! Feel free to leave comments and questions on this post—we’re happy to share what we know.
P.S. Thinking about how to make your campus equipment/services more discoverable? Try UCSF’s Plumage, the open source platform behind UCSF Cores Search.
Photo credit: digitonin via photopin cc
Here’s an article with an overview of online products out there for research social networking; the big gap in the article is that no institutional products are included such as Profiles, VIVO, etc. This is noted in one of the comments at the end, by Titus Schleyer.
That aside, there are interesting opinions in this piece, a few clipped below, and perhaps pointing to the current status of the space, where the sweet spot has not yet been found.
“After six years of running Zotero, it’s not clear that there is a whole lot of social value to academic social networks,” says Sean Takats, the site’s director, who is an assistant professor of history at George Mason University. “Everyone uses Twitter, which is an easy way to pop up on other people’s radar screens without having to formally join a network.”
Scholars aren’t interested in sharing original ideas on such sites, [Christopher Blanchard, an adjunct professor of community and regional planning at Boise State University] now believes, “because they’re afraid they’ll be ripped off” and because they simply don’t have the time.
“We have thousands of new discussions taking place every day—scientists helping scientists without getting anything for it,” [Dr. Madisch, of ResearchGate] says. “Three years ago, people were smiling at me and saying that scientists aren’t social. They won’t share information. They were wrong.”
Social Networks for Academics Proliferate, Despite Some Scholars Doubts – Technology – The Chronicle of Higher Education.
Here is an interesting new blog post by Heather Piwowar about the different ways research can impact the world and the importance of telling them apart. Good food for thought as we think about ways to help researchers analyze how people are reading, bookmarking, sharing, discussing, and citing research online.
I think Anirvan made a great point to think about ways how we can integrate “altmetrics” data with UCSF Profiles. Some of the metrics mentioned below may be a great starting point.
Here’s what Heather writes:
Figuring out the flavors of science impact. CC-BY-NC by maniacyak on flickr
We have clustered all PLoS ONE papers published before 2010 using five metrics that are fairly distinct from one another: HTML article page views, number of Mendeley reader bookmarks, Faculty of 1000 score, Web of Science citation counts as of 2011, and a combo count of twitter, Facebook, delicious, and blog discussion.
We normalized the metrics to account for differences due to publication date and service popularity, transformed them, and standardized to a common scale. We tried lots of cluster possibilities; it seems that five clusters fit this particular sample the best.
Here is a taste of the clusters we found. Bright blue in the figure below means that the metric has high values in that cluster, dark grey means the metric doesn’t have much activity. For example, papers in “flavour E” in the first column have fairly low scores on all five metrics, whereas papers in “flavour C” on the far right have a lot of HTML page views and Sharing (blog posts, tweeting, facebook clicking, etc) activity. View image and read on
Eric, Leslie, and I from CTSI at UCSF’s Virtual Home team spent the past three days at the AMIA 2012 Joint Summit in San Francisco.
Here’s some of what was happening on the researcher networking, social networking, knowledge representation fronts, and public search front, via Twitter:
Other tweets that caught my eye from the rest of the conference:
Three of us from the Virtual Home team at CTSI went to this year’s AMIA (American Medical Informatics Assoc) meeting in DC and presented on a panel with Griffin Weber of Harvard University. The panel was called “Four Steps to Using Research Networking Effectively at Your Institution”
Griffin spoke on cutting edge features of research networking tools, such as linked open data and social network analysis.
Eric Meeks of UCSF spoke on standard APIs, such as OpenSocial, to leverage a community of developers, I spoke about incentivize usage and understand your audience, and to round it out, Brian Turner spoke about using data, tools and strangers to improve user interfaces.
The panel presentation was a 90 minute break out session and we were happy to have a good turnout and an engaged audience. I think that the work that UCSF has put into the ‘social engineering’ of the tool has really paid off. Our usage and engagement numbers are on the rise and comparatively speaking, Griffin mentioned that our traffic is about 5-times that of what Harvard Profiles is currently getting.
In addition, Eric also had a poster session at the meeting!
The UCSF presentations will be up on Slideshare, available on the CTSI channel and via our individual UCSF profiles:
Unpublished or negative data rarely leave the lab books, even though they may help the scientific community at large avoid the repetition of unnecessary experiments. I recently came across the Academic Productivity blog and Mark Hahnel’s post about FigShare, an interesting initiative, released in March 2011, that tries to make it easy for researchers to share those types of research results. Since the data are categorized and tagged, I’m wondering whether – at some point – the database could turn into a data source for Profiles.
Mark Hahnel explains FigShare:
This is a new way of bringing scientific research online and to a new audience. By categorising and tagging the research, it becomes very searchable …there is also the ability to easily share figures, datasets and videos via a host of social media platforms through ‘share buttons’ on every page.
Read the original post
Also noteworthy, FigShare is collaborating with Digital Science which provides a suite of tools to make science more productive.