Collaboration Tools

UCSF’s most internally collaborative departments, 2017

/ Anirvan Chatterjee

Some UCSF departments consistently reach out out to collaborate with other members of the UCSF community. Here are the top UCSF departments whose researchers have the highest proportion of publications co-authored with people at other UCSF departments.

This ranking is based on data is drawn from UCSF Profiles, and only includes departments whose researchers had 100+ publications in 2017. We counted departmental affiliations based on someone’s primary department in UCSF Profiles in April 2018. So if someone subsequently left UCSF or changed primary departments, we wouldn’t count them as part of the primary department they were affiliated with at the time of publication. Or if they published something while at another institution in 2017, but subsequently moved to UCSF by April 2018, that paper would be chalked up their current UCSF department.

  1. Epidemiology & Biostatistics: 54.2%
    260 of 480 publications were co-authored with other UCSF departments
  2. Pathology: 49.5%
    93 of 188 publications were co-authored with other UCSF departments
  3. Radiology: 38.1%
    159 of 417 publications were co-authored with other UCSF departments
  4. Ob/Gyn, Reproductive Sciences: 37.1%
    101 of 272 publications were co-authored with other UCSF departments
  5. Pediatrics: 35.2%
    153 of 435 publications were co-authored with other UCSF departments
  6. Neurological Surgery: 34.9%
    112 of 321 publications were co-authored with other UCSF departments
  7. Bioengineering: 33.1%
    47 of 142 publications were co-authored with other UCSF departments
  8. Pharmaceutical Chemistry: 32.1%
    42 of 131 publications were co-authored with other UCSF departments
  9. Laboratory Medicine: 31.9%
    52 of 163 publications were co-authored with other UCSF departments
  10. Neurology: 30.7%
    149 of 485 publications were co-authored with other UCSF departments
  11. Anesthesia: 29.7%
    43 of 145 publications were co-authored with other UCSF departments
  12. Medicine: 29.0%
    584 of 2011 publications were co-authored with other UCSF departments
  13. Psychiatry: 28.1%
    125 of 445 publications were co-authored with other UCSF departments
  14. Surgery: 27.9%
    99 of 355 publications were co-authored with other UCSF departments
  15. Radiation Oncology: 27.6%
    34 of 123 publications were co-authored with other UCSF departments
  16. Dermatology: 25.6%
    41 of 160 publications were co-authored with other UCSF departments
  17. Orthopaedic Surgery: 24.8%
    39 of 157 publications were co-authored with other UCSF departments
  18. Urology: 24.0%
    31 of 129 publications were co-authored with other UCSF departments
  19. Ophthalmology: 19.5%
    26 of 133 publications were co-authored with other UCSF departments

How to get started with Git for biomedical researchers

/ Anirvan Chatterjee

Learning basic Git is a pretty essential skill for biomedical researchers sharing code—and increasingly, data—with others.

Thankfully, there’s a wealth of helpful guides out there on how to get started. Here are 4 resources we recommend:

  1. Why use Git? Skim “Git can facilitate greater reproducibility and increased transparency in science” by Karthik Ram
  2. Are you a visual learner? Watch Data School’s Git and GitHub videos for beginners
  3. Want to learn by doing, and already have Git on your command line? Begin with Software Carpentry’s self-guided lesson on how to get started with Git
  4. Want to work with others? You’ll probably want to set up a free account on Github (the most commonly used Git hosting/collaboration site) — and if you want to upgrade, you can take advantage of their education discounts

 

Balancing the benefits and risks in using Cloud Technology for Research

/ Melissa Telli

Contributed by Jamie Lam, Data Security Compliance Manager, UCSF School of Medicine

Cloud technology offers many benefits to researchers, such as:

  • ease of use,
  • rapid deployment, and
  • reduced costs.

At the same time, there are also some hidden implications to using a cloud service provider, including security obligations that may not be well understood.

While a well-designed cloud computing system can be safer than traditional client-server systems, when you are considering a cloud service, you must understand the benefits and risks, as well as your responsibilities in keeping sensitive data secure.

A couple of important points:

1) UC has standard contracts used with providers that protect our institutions’ security and assets. You should always work with procurement so they can ensure that the appropriate agreement is in place.

2) If disruption to services will negatively impact your research or operations, you should negotiate a Service Level Agreement (SLA) based on your needs.

However, don’t just rely on the signed contracts – you should always vet the vendors to confirm that they really are protecting our patients and our reputation.

UCSF has many resources to help you select the right vendor and ensure that your application and sensitive data are secure:

Interested in understanding more about Cloud Services and their benefits and risks? Take a look at this presentation by the School of Medicine Data Security Compliance Program: Securing Data in the Cloud

The 7 Keys to Maximizing Email Survey Response Rates

/ Nooshin Navidi Latour / 1 Comment

Lessons learned after achieving a high email survey response rate for a recent NSF Grant Study on UCSF Profiles.  Brought to you by Anirvan Chatterjee & Nooshin Latour

Your recipients don’t care about your email

The average office worker may get over 100 emails per day. Swiftly deleting or ignoring unwanted email can be the only way to stay afloat. These seven best practices will help ensure your email gets opened, read, and acted on — and not ignored or deleted.

We believe that our email marketing tactics and using customized data to drive up survey responses is widely applicable across research studies that can utilize targeted user data to increase study participation. Continue reading →

UCSF Profiles Team Invited to Geneva, Switzerland

/ Brian@CTSI

The UCSF Profiles Team got more international attention for its enhancements to the Profiles product and the level of engaged users last year. Over the past several months, the Special Program for Research and Training in Tropical Diseases (TDR) has been in talks with UCSF Profiles to gain insight and plan an approach to create a system that will show and track their researchers’ work around the globe. TDR is a global collaborative program sponsored by the United Nations Children’s Fund (UNICEF), the United Nations Development Program (UNDP), the World Bank and World Health Organization (WHO). Continue reading →

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

/ leslieyuan / 1 Comment

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. Continue reading →

UCSF collaborations, visualized

/ Anirvan Chatterjee

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

UCSF internal collaborations, by department, based on publication co-authorship

Study: The Science Behind Twitter ‘Tribes’

/ Nooshin Navidi Latour

The article ‘You Are What You Tweet’ from MediaBistro alluded to a recent study by EPJ Science finding that ‘word usage mirrors community structure in the online social network Twitter.’

It made me think about how we communicate with people interested in accelerating biomedical research – do we employ a unique language pattern? On the flip side: How should our language change when trying to reach a wider audience (outside our social network), engage new communities and partners?

Image

EPJ Abstract
Background: Language has functions that transcend the transmission of information and varies with social context. To find out how language and social network structure interlink, we studied communication on Twitter, a broadly-used online messaging service.

Results: We show that the network emerging from user communication can be structured into a hierarchy of communities, and that the frequencies of words used within those communities closely replicate this pattern. Consequently, communities can be characterised by their most significantly used words. The words used by an individual user, in turn, can be used to predict the community of which that user is a member.

Conclusions: This indicates a relationship between human language and social networks, and suggests that the study of online communication offers vast potential for understanding the fabric of human society. Our approach can be used for enriching community detection with word analysis, which provides the ability to automate the classification of communities in social networks and identify emerging social groups.

 

Making Science Greater

/ John Daigre

A new laboratory in ViCOSrginia, the Center for Open Science, is (according to its website) “dedicated to improving the alignment between scientific values and scientific practices to improve the accumulation and application of knowledge. Operating with a technology start-up atmosphere and mindset, the COS team moves quickly, identifies problems and creates solutions, encourages risk-taking, blends science and technology, and is collaborative, high energy, and dedicated to openness.”

The Center has already launched a signature project—the Open Science Framework, allowing scientists to store and share all aspects of their work.

A news story at NationalGeographic.com notes: “failed experiments, the minutiae of methods, the genesis of ideas… these are often omitted from published papers or left to languish in personal file drawers. That creates strong biases in the literature, and makes it harder for people to check and reproduce each other’s work.”

It adds that the Center is “less about doing great science than about making science greater. It will try to foster a new approach to research that will produce more reliable results.”