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Data Science

Moodle Class Announcement: Big Data in Healthcare: Exploring Emerging Roles

SEA Data Science - Wed, 2018-01-03 14:46

The National Network of Librarians of Medicine (NNLM) invites you to participate in Big Data in Healthcare: Exploring Emerging Roles. This course will be primarily held via the Moodle platform with optional WebEx discussions. This course is designed to help health sciences librarians understand the issues of big data in clinical outcomes and what roles health sciences librarians can take on in this service area.

DatesFebruary 5 – March 30, 2018

Register: To register for this class, please visit:

The class size for this course is limited to 60 students. We will begin a waitlist if there are more interested in participating.

Course instructors for the winter session are Ann Glusker, Pacific Northwest RegionDerek Johnson, Greater Midwest RegionAlicia Lillich, MidContinental Region, Ann Madhavan, Pacific Northwest Region, Tony Nguyen, Southeastern/Atlantic Region, and Elaina Vitale, Mid-Atlantic Region.

Please contact Tony Nguyen with questions.

Description: The Big Data in Healthcare:  Exploring Emerging Roles course will help health sciences librarians better understand the issues of big data in clinical outcomes and what roles health sciences librarians can take on in this service area. Course content comes from information shared by the presenters at the March 7, 2016 NNLM Using Data to Improve Clinical Patient Outcomes Forum, top selections from the NNLM MCR Data Curation/Management Journal Club and NNLM PSR Data Curation/Management Journal Club’s articles, NINR’s Nursing Research Boot Camp, recommended readings from previous cohorts, and Big Data University’s Big Data Fundamentals online course.

Participants will have the opportunity to share what they learned with the instructor from each section of the course content either through WebEx discussions or Moodle Discussions within each Module. These submissions can be used to help support the student’s views expressed in the final essay assignment.

Objectives: Students who successfully complete the course will:

  • Explain the role big data plays in clinical patient outcomes.
  • Explain current/potential roles in which librarians are supporting big data initiatives
  • Illustrate the fundamentals of big data from a systems perspective
  • Articulate their views/options on the role health sciences sector librarians is in supporting big data initiatives

NOTE: Participants will articulate their views on why health sciences librarians should or should not become involved in supporting big data initiatives by sharing a 500-800 word essay. Students are encouraged to be brave and bold in their views so as to elicit discussions about the roles librarians should play in this emerging field. Participants are encouraged to allow their views to be published on a NNLM online blog/newsletter as part of a dialog with the wider health sciences librarian community engaging in this topic. Your course instructors will reach out to you following the completion of the course.

On top of information gained, being a part of the big data in clinical care dialog, and earning 9 continuing education credits from the Medical Library Association, students may earn an IBM Open Badge program from the Big Data University.

This is a semi-self-paced course (“semi” meaning there are completion deadlines). While offered primarily asynchronously, your course instructors plan to offer opportunities in which participants can join a WebEx discussion to discuss some of the content.

Course Expectations: To complete this course for nine hours of MLA contact hours, participants are expected to:

  • Spend 1-2 hours completed the work within each module.
  • Commit to complete all activities and articulate your views within each module.
  • Complete course requirements by the deadline established in each module.
  • Coordinate with a course instructor to publish your observations/final assignments on a NNLM blog/newsletter
  • Provide course feedback on the Online Course Evaluation Form

Grading: Grades for this course is simply a pass/fail grading system. When your submission meets the assignment’s expectations, you will receive full credit for the contact hours for that Module. For submissions that are unclear or incomplete, you may be requested for more information until your instructor approves.

  • For discussion posts, your activity will be marked as complete after you’ve submitted a discussion AND your instructor assigns a point to mark as complete
  • If you participate in WebEx Journal Club Discussions (when available), your instructor will assign points in the Discussions for that module.
  • Students have the option to accept fewer contact hours. However, you will need to inform your course instructors ahead of time.
Categories: Data Science

The OHSU Library Data Science Institute Introduces Data Science Techniques to Librarians and Researchers

PNR Data Science - Thu, 2017-12-14 21:47

Today’s Dragonfly post comes to us from Nicole Vasilevsky, Letisha Wyatt, Robin Champieux, Laura Zeigen and Jackie Wirz

The Oregon Health & Science University Library in Portland, Oregon hosted the “OHSU Library Data Science Institute” (ODSI) from November 6-8, 2017 in downtown, Portland. The event was targeted towards researchers, librarians and information specialists with an interest in gaining beginner level skills in data science. The goal was to provide face-to-face, interactive instruction over a three-day workshop. The learning objectives for the training were:

  • Increase awareness of key skills in data science and how these can be applied to the participants own daily practices, such as research or serving patrons
  • Increase confidence with using data science techniques
  • Increase the ability of participants to use or apply data science techniques in problems outlined in the course

Over 75 participants attended this event, which was held over the 3 days. Participants came from within and outside Portland, Washington, Idaho, California, British Columbia and Kansas. The topics for the workshop included topics such as an introduction to version control and GitHub, exploratory data analysis and statistics, biomedical data standards; data description, sharing and reuse; quantitative and qualitative analysis, analyzing textual data, web scraping, data visualization and mapping and geospatial visualization. All of the materials are shared and openly available via our website.

The goals of the ODSI were to:

1) to increase skills of students and information professionals (e.g., librarians and research staff) so that they may be better equipped to work with data or meet the needs of the research communities that they work with

2) provide a venue for networking and relationship-building between local research community, libraries, and active information professionals.

As an outcome of this course, the majority of our participants that identified as librarians or information professionals reported they are more aware of, can actively teach or use key skills in data science and are more aware of how these can be applied to researchers. In addition, the respondents that identified as researchers reported that they have increased awareness of and confidence using data science knowledge; that they anticipate integrating skills derived from the Institute into their workflow (experimental design, data cleaning, analysis) and that they bring this information back to their laboratory, department, and peers.

Our full webpage, which includes links to session syllabi and instructional materials.

Some lessons learned include:

  • Development of curricula for a diverse audience is a daunting challenge! To address this in the future we would consider tracks or ensuring that the content is focused and targeted to a specific career field/discipline.
  • A Train-the-Trainer event would help present a uniform approach towards pedagogy, hands-on-learning, and delivery. In addition, it might be helpful to host a demo day where instructors can test their content with either other instructors or a test audience.
  • More coffee and tea! Data Science is fueled by warm beverages, so we need to add more.
Categories: Data Science

NIH All of Us Research Program Traveling Exhibit Visits the University of Arizona in Tucson!

PSR Data Science - Wed, 2017-12-13 18:48
salam ahleh and yamila el-khayatAhlam Saleh and Yamila El-Khayat

by Yamila El-Khayat
Outreach Services Librarian
Health Sciences Library
University of Arizona
Tucson, AZ

The NIH All of Us Research Program traveling exhibit came to the University of Arizona’s Banner Health Hospital Campus on December 7, 2017. It provided an excellent opportunity to visit and learn more about the All of Us Program. At the entry, there was an introductory video that clearly and simply introduced the All of Us project. The video focused on two individuals of differing ethnicities and lifestyles, but with the same diagnosis. It focused on the importance of molding medicine to each individual because of their differences. It was a very creative way of simply defining the concept of precision medicine.

Next in the exhibit was an area to answer a couple of questions on a tablet computer. Then your picture was taken and you received a color identification from the spectrum of options. The picture was then shown framed in the identity color. No definitions were supplied regarding the colors, but I ended up being red, which according to the person giving us the tour was rare, and her first experience seeing that color. It was a further illustration of the differences in each of us. Finally, we were shown other activities and noises and had to identify what we thought they were and then shown what they really were. This was a way to learn about differing perceptions, again emphasizing the importance of uniqueness in individuals. All in all, the exhibit was an informative and entertaining way to learn more about the All of Us Research Program.

bus with all of us advertisementAll of Us Traveling Exhibit
Categories: Data Science

Coming soon—Survey results about DATA!

PNR Data Science - Wed, 2017-12-13 18:08

You may remember the email and picture below, which was sent out to various groups and promoted in various ways this past spring.  In it, we were asking you all to participate in the NNLM-PNR data needs assessment survey.  By doing the survey, Annie Madhavan and I (Ann Glusker) were hoping to get feedback on the directions you want us to go with teaching about and providing resources related to data.

Well, we had 60 people respond, which we are thrilled about, and we ended up sending out 14 fabulous prizes (the NLM tape measures shown in the photo–woo hoo!).  More importantly, we’ve completed the data analysis, got some VERY helpful information, and are putting the final touches on the report we promised! (a little later than we’d hoped, but better late than never?)

So, we just wanted to let you know that the report will be sent out to the HLIB-NW list in early January, as well as to all the people whose emails we have and/or who ask for a copy, with our best wishes for a very happy New Year.  See you online again soon!

Categories: Data Science

An NNLM RD3 Update

PNR Data Science - Mon, 2017-12-04 04:00

It’s been almost 6 months since the launch of the National Network of Libraries of Medicine’s new data website, NNLM RD3: Resources for Data-Driven Discovery, and since May, several new features have been added. When the site first launched at MLA 2017, it had only recently transitioned from the New England Region’s eScience Portal for Librarians. Since then, with the very generous assistance of both old and new volunteer content editors, we have updated many of the original physical science and engineering subject primers, and have also added a number of health sciences topics. The subject primers now provide a brief overview of each field followed by data related information, including pertinent articles on big data and data management, metadata, data repositories, and data standards and policies specific to each field.

We have also added a Twitter feed on the NNLM RD3 homepage that links to @NNLM_RD3’s Twitter page and highlights a wide range of data science and data management retweets. Also on the homepage, is a Data Science around the Regions blog feed that links to data related articles from across the NNLM’s eight regions.

In the coming months we are planning to feature information on innovative data librarians and data management initiatives across the country, update and add additional subject guides, reveal the Data Thesaurus, and report on the first cohort of NNLM Training Office’s Biomedical & Health RDM Training for Librarians course. We invite you to continue to explore NNLM RD3 and post your comments and suggests below or on website. RD3 continues to be a work in progress and one that could not exist without the support and expertise of many of our members. We are always on the lookout for content editors, so if you would like to contribute to a new or existing subject primer, or simply suggest a new feature or update, we would love to hear from you.

Categories: Data Science

Seeing the Forest and the Trees: Why Librarians Can Make Valuable Contributions Working with Big Data

GMR Data Science - Fri, 2017-12-01 09:33

In the NNLM Big Data in Healthcare: Exploring Emerging Roles course, we asked participants, as they progressed through the course to consider the following questions: Do you think health sciences librarians should get involved with big data in healthcare? Where should librarians get involved, if you think they should? If you think they should not, explain why. You may also combine a “should/should not” approach if you would like to argue both sides. NNLM will feature responses from different participants over the coming weeks.

Written by: Heidi Beke-Harrigan, MLS, Health Sciences Librarian, Member Services Coordinator, OhioNET

There has been an explosion of conversation around the topic of big data. The potential for mining large sets of data in endless, customized combinations could revolutionize healthcare, patient outcomes and evidence-based medicine. At the same time, as with systematic reviews, effective data projects benefit from a collaborative environment and a team approach. One individual is not likely to possess the skills to formulate the right questions, write queries, extract the data, provide analysis and manage data storage/retrieval. Data without context is lifeless. Misused it can be exploited, misinterpreted and manipulated. Deriving meaning from data depends on someone’s ability to mine what’s there and make real connections to people’s lives. That’s where librarians excel. Our work has always been about cultivating connections, enabling access to raw information so that new ideas can ferment, providing access to those ideas and end products, and storing the results. Formats have come and gone, but it’s all data and librarians can play a key role in making data useful. Where individuals with specific expertise may focus on a very narrow aspect of data work (trees), librarians tend to see patterns, connections and possibilities (forest). Librarians like to create spaces where nuanced details and creativity can coexist and mingle in a place of infinite possibility.

What skills can librarians specifically bring to the table? Researchers have identified the need to recode data elements and challenges maintaining consistency of data over time as two barriers to big data work. Librarians with cataloging and metadata experience can work with teams to help bring about harmonizing of terminologies and standardize metadata descriptions. They are also able to ask important questions about storage and retrieval. Where will the coding that extracted the data live? Do the resulting data sets need to be stored? How can reproducibility or access points to the data be supported? What story does the data tell and who else might want to discover it?

Imagine further, a world where librarians are part of a new framework of front-line clinical teams and integral to using big data to improve patient outcomes. If we assist with research topic formulation, provide input regarding user experience design, help develop consult management tools, and support the creation of effective query forms and output displays, can we free up clinicians and partner with other colleagues to more fully explore the role of data in Practice Based Evidence (PBE)?

Librarians’ expertise in providing programming, informal learning opportunities and formal classroom instruction can serve us well to assist in citizen data scientist training and to prepare our students with critical skills for work in a data rich landscape. Part of that skill-set should also include an awareness for and appreciation for data literacy, data sharing, and transparency. As Dr. Brennan pointed out, there are certainly opportunities for data scientists and programmers in this information-rich world, but to give that data meaning, requires that we all bring the unique strengths and core values of our diverse professions to the table. In that realm, librarians have much to share.

Categories: Data Science

NIH’s All of Us Research Program Partners with NNLM to Reach Target Communities Through Local Public Libraries

PSR Data Science - Wed, 2017-11-29 11:45
diverse group of people with the All of Us Research Program logo and tagline, “The future of health begins with you.

The NIH All of Us Research Program and the National Library of Medicine (NLM) have teamed up to raise awareness about the program, a landmark effort to advance precision medicine. Through this collaboration, the National Network of Libraries of Medicine (NNLM) has received a $4.5 million award to support community engagement efforts by public libraries across the United States and to improve participant access. According to Eric Dishman, director of the All of Us Research Program: “We want to reach participants where they are. For many people in the country, including those with limited internet access, one of those places is the local library. We’re excited to work with the National Library of Medicine to make more people aware of All of Us and the opportunity to take part.”

The partnership is a three-year pilot program, running through April, 2020. Program objectives include:

  • To increase the capacity of public library staff to improve health literacy.
  • To equip public libraries with information about the All of Us Research Program to share with their local communities.
  • To assess the potential impact of libraries on participant enrollment and retention.
  • To highlight public libraries as a technology resource that participants can use to engage with the program, particularly those in underserved communities affected by the digital divide.
  • To establish an online platform for education and training about All of Us and precision medicine, with resources for members of the public, health professionals, librarians and researchers.
  • To help identify best practices in messaging and outreach that lead to increased public interest and engagement in the program.

The All of Us Research Program aims to build one of the largest, most diverse datasets of its kind for health research, with one million or more volunteers nationwide who will sign up to share their information over time. Researchers will be able to access participants’ de-identified information for a variety of studies to learn more about the biological, behavioral and environmental factors that influence health and disease. Their findings may lead to more individualized health care approaches in the future.

Amanda J. Wilson, head of NLM’s National Network Coordinating Office (NNCO), and Dara Richardson-Heron, M.D., chief engagement officer of the All of Us Research Program, will lead the new partnership. Each NNLM region’s funding includes one FTE for an All of Us Point of Contact. Kelli Ham, formerly NNLM PSR Consumer Health Librarian, will fill the role in the Pacific Southwest Region. Her new title will be Community Engagement Librarian. Over the course of the pilot program, Kelli will focus her outreach efforts on various designated target geographic areas in the region, beginning with Sacramento, CA.

The All of Us Research Program is currently in beta testing. To learn more, sign up to receive updates. Precision Medicine Initiative, All of Usthe All of Us logo, and “The Future of Health Begins with You” are service marks of the U.S. Department of Health and Human Services.

Categories: Data Science