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News for Network Members in Alabama, District of Columbia, Florida, Georgia, Maryland, Mississippi, North Carolina, Puerto Rico, South Carolina, Tennessee, U.S. Virgin Islands, Virginia and West Virginia
Updated: 5 hours 28 min ago

Upcoming Webinar: Proposed Provisions for a Draft NIH Data Management and Sharing Policy

Tue, 2018-11-06 14:37

Date: Wednesday, November 7, 2018

Time: 11:30 AM – 1 PM ET

Registration: Details about the webinar, including how to register can be found by clicking here.

Description: On October 10, 2018, the National Institutes of Health (NIH) issued a Request for Information (RFI) in the NIH Guide to Grants and Contracts to solicit public input on proposed key provisions that could serve as the foundation for a future NIH policy for data management and sharing. The feedback obtained will help to inform the development of a draft NIH policy for data management and sharing, which is expected to be released for an additional public comment period upon its development.  To further engage stakeholders, NIH will be hosting a webinar on the proposed key provisions on November 7, 2018, from 11:30 a.m. – 1:00 p.m. ET.

Comments on the proposed key provisions will be accepted through December 10, 2018, and can be made electronically by visiting the National Institutes of Health, Office of Science Policy.

For a perspective on the importance of obtaining robust stakeholder feedback on this topic, please see the latest Under the Poliscope by Dr. Carrie D. Wolinetz.

Categories: Data Science

NIH Seeks Public Comment on Proposed Provisions for a Future Draft Data Management and Sharing Policy

Fri, 2018-10-12 15:45

On October 10, 2018, the National Institutes of Health (NIH) issued a Request for Information (RFI) in the NIH Guide to Grants and Contracts to solicit public input on proposed key provisions that could serve as the foundation for a future NIH policy for data management and sharing.  The feedback we obtain will help to inform the development of a draft NIH policy for data management and sharing, which is expected to be released for an additional public comment period upon its development.

Comments on the proposed key provisions will be accepted through December 10, 2018, and can be made electronically by visiting here.

To further engage stakeholders, NIH will also be hosting a webinar on the proposed key provisions on November 7, 2018, from 11:30 a.m. – 1:00 p.m. ET. Details about the webinar, including how to register can be found by clicking here.

For a perspective on the importance of obtaining robust stakeholder feedback on this topic, please see the latest Under the Poliscope by Dr. Carrie D. Wolinetz.

Questions about the proposed provisions may be sent to the NIH Office of Science Policy at SciencePolicy@od.nih.gov

Categories: Data Science

Upcoming Webinar: Planning, Developing, and Evaluating R Curriculum at the NIH Library – October 12 2 PM ET

Thu, 2018-09-27 12:11

Join NNLM for the next iteration of the Research Data Management webinar series: Planning, Developing, and Evaluating R Curriculum at the NIH Library October 12, from 2-3 pm ET. To register for this free webinar, visit: https://nnlm.gov/class/Rtraining. Can’t make it on the 12th? Don’t worry, the webinar will be recorded!

This webinar will describe a pilot project to evaluate current R training at the NIH Library, and based on an evaluation of the data, revise the library’s R training curriculum. This will include a discussion of the development of a training plan, weekly R check-in sessions, managing documents using Open Science Framework (OSF), and an evaluation of the pilot.

Learning Objectives:

By the end of this webinar participants should have a better understanding of:

  1. R curriculum before the pilot project
  2. Our evaluation of data-related training before the pilot project
  3. The components of the pilot project
  4. The development of our training plan
  5. How OSF was used for project management
  6. Format and frequency of classes during the pilot project
  7. Post-pilot evaluation

Instructor Bios:

Doug Joubert joined the National Institutes of Health (NIH) Library in 2004. He is a customer-oriented practitioner with extensive experience in providing comprehensive research and information services support to researchers working in the areas of public health and health care policy. In this role, Doug provides his clients with services that support of the missions of the NIH and select HHS staff divisions. As part of his duties at the NIH Library, he identifies and provides guidance on the effective use of emerging technologies and recommends strategies to capitalize on them. Practice areas include data analytics, data visualization, GIS, and teaching.

Candace Norton joined the National Institutes of Health (NIH) Library as a National Library of Medicine (NLM) second year Associate Fellow in 2017. Prior to joining the NLM Associate Fellowship Program, Candace managed a small corporate library for a pharmaceutical and life sciences consulting company in Bethesda, MD. During her fellowship appointment, she has pursued projects and training in areas related to pharmacovigilance monitoring, systematic reviews, bibliometric analysis, and data visualization.

Categories: Data Science

Big Data Science: What Librarians Offer

Tue, 2018-09-25 12:17

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: Margaret Ansell, Nursing and Consumer Health Liaison Librarian, George A. Smathers Libraries, University of Florida, Gainesville, FL

Throughout the history of the profession, librarians have questioned the scope and breadth of their role.  With every new technology comes an opportunity for new services and a threat to old ones.  An example: thanks to the advent of electronic resources and searchable databases, librarians spend much less time retrieving materials for patrons now, and more training patrons how to retrieve materials themselves.  Each time a disruptive technology makes itself known, librarians have to collectively decide how to accommodate it.  Whether such accommodation is considered an evolution of the profession, or a mutation, depends very much on your perspective.  Faced with the disruption created by big data technologies, librarians, and medical librarians in particular, must decide how to accommodate it, and in what ways big data is both an opportunity for and a threat to our services.

Many librarians choose to view big data technologies as less of a disruptive technology and more of the same techniques/technologies currently being used, simply at a larger scale.  Data Management has always been an essential research skill, big data just makes the necessity more evident.  And while data management is a newer part of the average library’s service repertoire, it is overall well understood as a natural part of the library’s expertise, if you consider data as just another type of material that libraries can collect, organize, and preserve.  While the specific tools and techniques used to manage data require computer science skills beyond that of most public service librarians, it is not outside the realm of expertise of many technical services librarians and library information technology staff, who, in collaboration with an institution’s researchers, can create tools, repositories, and templates that ease the burden of the data management process.  The California Digital Library’s DMP Tool is perhaps the strongest example of what such collaborations can create.

However, I think that only viewing big data technologies through the lens of data management ignores entirely new potential opportunities for service and outreach.  As library data scientists like Lisa Federer demonstrate, big data is not simply the result of researchers using the same methods on a larger scale, but truly a new type of science, with new challenges.  It is similar to the revolution in evidence synthesis that occurred when systematic reviews emerged as a premier methodology – to conceive of systematic reviews as simply a more expansive kind of narrative review is to misunderstand fundamental differences in their nature.  Some examples of issues to big data approaches include: the creation and management of searchable, multi-institutional data repositories to support big data techniques; the ethics of the kind of surveillance/data gathering techniques required to create big data (this latest report on fitbit heart rate data is a prime example, particularly because it is not published in any academic journal); or whether current statistical methods are appropriate for the kinds of heterogeneous data sets common to big data.  Now, I don’t think that library science has the answer to all of these questions, or that we should be held responsible for answering even one of them.  What I am saying is that the values of librarianship – accessibility, transparency, and accuracy/rigor – give librarians an important perspective on big data initiatives that expertise in Python or R won’t necessarily bring.

Sadly, while I believe our perspective is valuable even without expertise in big data research techniques, I fear that the voice of librarians is likely to be ignored as irrelevant by researchers and administrators as repositories, tools, and analysis techniques are established, if our perspectives are the only things we have to offer.  Tangible skillsets and resources, of recognizable value to stakeholders in the big data process, may be the only way we will be given a seat at the big data decision-making table.  If nothing else, librarians must learn the language of big data, in order to be part of the conversation.

Categories: Data Science

Apply Today! Biomedical and Health Research Data Management Training for Librarians

Tue, 2018-09-11 12:03

Health sciences librarians are invited to apply for the online course, Biomedical and Health Research Data Management Training for Librarians, offered by the NNLM Training Office (NTO). The course is a free, 7-week online class with engaging lessons,  practical activities and a final project. The course runs October 15 – December 14, 2018.

The goal of this course is to provide an introduction to data issues and policies in support of developing and implementing or enhancing research data management training and services at your institution. This material is essential for decision-making and implementation of these programs, particularly instructional and reference services. Course topics include an overview of data management, choosing appropriate metadata descriptors or taxonomies for a dataset, addressing privacy and security issues with data, and creating data management plans.

Applications are due September 20, 2018.

Additional details and the online application are available here.

For questions, please contact the NNLM Training Office

Categories: Data Science

Applications Open: Biomedical and Health Research Data Management Training for Librarians – Applications Due Sep 20, 2018

Thu, 2018-08-23 13:08

Course Description
Health sciences librarians are invited to participate in a rigorous online biomedical and health research data management training course, sponsored by the National Library of Medicine (NLM) and the National Network of Libraries of Medicine Training Office (NTO). The course provides basic knowledge and skills for librarians interested in helping patrons manage their research data. Attending this course will improve your ability to initiate or extend research data management services at your institution. Familiarity with the research lifecycle is recommended but not required.

The major goal of this course is to provide an introduction to data issues and policies in support of developing and implementing or enhancing research data management training and services at your institution. This material is essential for decision-making and implementation of these programs, particularly instructional and reference services. The course topics include an overview of data management, choosing appropriate metadata descriptors or taxonomies for a dataset, addressing privacy and security issues with data, and creating data management plans.

Course Components
The online asynchronous component of the program is 7 weeks from October 15 – December 14 with a week off for the Thanksgiving holiday. There will also be a week for catch-up.  The format includes video lectures, readings, case studies, hands-on exercises, and peer discussions. There will be optional weekly office hours. Expect to spend up to 4-5 hours each week on coursework. Participants will complete a Final Project Plan/Proposal, demonstrating improved skills, knowledge, and ability to support data management services at their institution.

CE Credits
Participants who complete all modules, the Final Project Plan, and the course evaluation will receive MLA CE credit (exact number of hours to be determined). No partial CE credit is granted.

Instructor
The instructor is Tisha Mentnech, MSLIS, Research Librarian from the Spencer S. Eccles Health Sciences Library, University of Utah.

Who can apply?

  • Applications are open to health science librarians in the United States.
  • Applications from libraries currently looking to develop or enhance research data management training and services are encouraged.
  • A letter of institutional support is required. See application instructions below.
  • Enrollment is limited to 40 participants.

What does it cost?
There is no charge for participating in the program.

Important Dates

  • Application deadline: September 20, 2018
  • Notifications begin: October 1, 2018
  • Online Course: October 15 – December 14, 2018

Application Details

  • Name and Contact Information
  • Current Role/Title
  • Place of Employment
  • Briefly describe your current experience or interest in research data management.
  • Briefly describe the current status of research data management services at your library, including any barriers to implementation.
  • This training will have been worthwhile for you and your institution if…

Application Instructions
Please fill out the online Application Form, and upload a PDF of your current CV and your letter of institutional support. The letter of institutional support must be from your supervisor and address:

  1. time for participation in the online course;
  2. the library’s commitment to or plans for adding or enhancing research data management services.

Please submit your application via the online form by September 20, 2018:
https://www.surveygizmo.com/s3/4521556/Biomedical-Health-RDM-Training-Participant-Application-Fall-2018

Questions? Contact NTO at nto@utah.edu.

Categories: Data Science