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Updated: 3 hours 26 min ago

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

Funding Announcement: NLM Research Grants in Biomedical Informatics and Data Science (R01 Clinical Trial Optional)

Fri, 2018-08-10 09:27

Earliest Submission Date: September 5, 2018

Purpose: The National Library of Medicine (NLM) supports innovative research and development in biomedical informatics and data science. The scope of NLM’s interest in these research domains is broad, with emphasis on new methods and approaches to foster data driven discovery in the biomedical and clinical health sciences as well as domain-independent, reusable approaches to discovery, curation, analysis, organization and management of health-related digital objects. Biomedical informatics and data science draw upon many fields, including mathematics, statistics, information science, computer science and engineering, and social/behavioral sciences. Application domains include health care delivery, basic biomedical research, clinical and translational research, precision medicine, public health, biosurveillance, health information management in disasters, and similar areas. NLM defines biomedical informatics as the science of optimal representation, organization, management, integration and presentation of information relevant to human health and biology. NIH defines data science as the interdisciplinary field of inquiry in which quantitative and analytical approaches, processes, and systems are developed and used to extract knowledge and insights from increasingly large and/or complex sets of data.

To learn more about this grant, please visit: https://grants.nih.gov/grants/guide/pa-files/PAR-18-896.html

Categories: Data Science

Research Data Management Webinar Series: Approaching Resistance to Change in Research Data Management – August 3 2018

Wed, 2018-07-25 08:45

Guest Speaker: Amanda Rinehart, Data Management Librarian at the Ohio State University

Time: Friday, August 3rd 2 PM ET/1 PM CT / 12 PM MT/11 AM PT

To register: https://nnlm.gov/class/approaching-resistance-change-research-data-management/8790

Description: Federal funding agencies now emphasize data sharing and re-use as part of the grant review process. However, difficulties in data sharing and re-use begin with basic data management practices. If data is not appropriately documented, organized, and readily available, then sharing cannot result in re-use. Appropriate data management may be a new expectation for many researchers, and as such, may require an individual to adopt, or invent, particular innovations. Many researchers do not know what is required to prepare their data, let alone how to incorporate more time-consuming tasks into their current workflows. Thus, researcher concerns regarding these new expectations needs to be assessed in order to provide appropriate educational interventions. This webinar will cover both work using the Concerns Based Adoption Method to identify specific researcher concerns and anecdotal experiences from working with researchers who are not yet comfortable with new data management practices.

Speaker Bio: Prior to becoming a librarian, Amanda spent eleven years as a biologist with the USDA, testing alternative agricultural methods to reduce the human impact on climate change. She draws extensively on this research experience while developing the Libraries research data management program. This program includes consultation services, workshops, development of educational materials, and teaching. She also administers Ohio State’s DMPTool software, which helps researchers create high quality data management plans that meet funder requirements. Amanda received her MLIS from South Florida University, her MS in Botany and Plant Pathology from Michigan State University and her BA in Biology from Kenyon College.

For more information and to register: https://nnlm.gov/class/approaching-resistance-change-research-data-management/8790

Categories: Data Science

Data Management for Librarians CE workshop

Thu, 2018-07-05 08:37

The University of Minnesota Health Sciences Libraries is hosting a 4-hour Data Management for Librarians CE workshop in Minneapolis, MN on August 6th. Registration for the workshop is free, and there are a select number of travel stipends available for up to $1,000.  The Workshop will introduce participants to key elements of research data management in the health sciences, including best practices for documentation, metadata, backup, storage, and preservation. Participants in the CE course may also partake in an online data management skills community of practice, which will meet quarterly to take a deeper dive into data management topics. The course will also provide 4 MLA CE credits. More information about the training, stipend requirements, and registration can be found on the GMR’s Blog. Any questions related to the Workshop should be directed to Lisa McGuire at: lmcguire@umn.edu

Categories: Data Science

Moodle Class Announcement: Big Data in Healthcare: Exploring Emerging Roles – July 9 – August 31, 2018

Tue, 2018-06-12 15:45

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.

DatesJuly 9 – August 31, 2018

Register: To register for this course, please visit the class details page.

The class size for this course is limited to 40 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 RegionAnn Madhavan, Pacific Northwest RegionAimee Gogan, Southeastern/Atlantic Region, and Elaina Vitale, Mid-Atlantic Region.

Please contact Aimee Gogan with questions.

Description: Class Overview

Big Data in Healthcare: Exploring Emerging Roles

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).

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.

This is a Medical Library Association approved course that will earn students 9 contact hours.

 

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.

DatesJuly 9 – August 31, 2018

Register: To register for this course, please visit the class details page.

The class size for this course is limited to 40 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 RegionAnn Madhavan, Pacific Northwest RegionAimee Gogan, Southeastern/Atlantic Region, and Elaina Vitale, Mid-Atlantic Region.

Please contact Aimee Gogan with questions.

Description: Class Overview

Big Data in Healthcare: Exploring Emerging Roles

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).

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.

This is a Medical Library Association approved course that will earn students 9 contact hours.

 

 

Categories: Data Science