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Data Science

Librarians and Research Data Management Services: Branching Out Into Big Data

MCR Data Science - Tue, 2018-09-18 10:47

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: Rose Fredrick, Digital Repository Librarian, Health Sciences Library, Creighton University

Big data has a different nature than traditional research data. It is more immediate and ephemeral which creates large, eclectic datasets that are not easily categorized or managed with traditional data science tools.  It is changing the way research is done and the health sciences in particular are discovering new possibilities for studies by aggregating multiple sources of patient data, like wearable health trackers and electronic health records. These transformative studies also give health science librarians an opportunity to support data scientists by building upon existing research data management services.  The librarian’s role in research data management is well-established and this creates a natural launching point for librarians to expand into big data research services.

Many libraries already provide a full array of data services, such as advising on data management plans, metadata and organization, public access mandates, data security, and the preservation and archival of data sets.  Although big data has different needs when it comes to storage and analysis, many of the same services apply.  Librarians have expertise in the ethical implications of data privacy, publisher and funder requirements, and in curating, organizing and preserving data.  All of these skills and services can benefit big data researchers, but librarians do need to be aware of the challenges of big data.

While the knowledge base of librarianship and research data management can clearly be used advantageously for big data services, there can be barriers to librarians implementing these new services.  Perhaps the biggest barrier is training. Depending on the services being offered, at a minimum librarians will need to become familiar with the nature of big data and how that shapes the research process, the correct terminology, and what resources are available to researchers.  Furthermore, to offer the most robust services, librarians may need data science training or advanced technical training to assist with data processing. Not all institutions are prepared to train librarians so extensively nor will they experience enough demand to require a full-time data science librarian .

Librarians can offer more basic services without intensive data science and technical training, however.  A first step could be to become familiar with the terminology, issues, and processes of using big data and be ready to refer researchers with questions to useful resources.  Another option that requires a bit more investment is to offer instruction on crafting data management plans, understanding funder/publisher requirements for data, or choosing a data preservation platform.  Librarians with more time could offer one-on-one advisory sessions on the data management plan for their research projects.  Librarians without a data science background could also take advantage of training geared towards them, like the Data and Visualization Institute for Librarians or the Data Sciences in Libraries Project.

Additionally, as a digital repository librarian, I wanted to determine whether my library would be able to offer services for archiving big data.  Currently, our institutional repository would not be able to house such large sets of data, so while we can advise researchers on preparing for preservation and selecting a platform, we will not be able to archive the data sets in-house.  In the future, it may be possible to collaborate with our information technology department and create an archival system using Apache Hadoop . Some libraries with enough technical resources may already be able to take that step. In the meantime, I think libraries can offer counseling on choosing from the available platforms and perhaps offer data preparation advice based on their experience from archiving smaller sets of research data. In summary, health sciences librarians have relevant expertise and services to offer to big data research and they should consider what combination of services will be the best fit for their institutions.

Categories: Data Science

Big Data in Healthcare: Finding Your Niche

GMR Data Science - Mon, 2018-09-17 12:39

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: Brenda Fay, Library Specialist, Aurora Libraries – Aurora St. Luke’s Medical Center

For librarians in health science libraries, big data in healthcare might be something of a stranger. Sure, we know that data is being collected about patients, but how do we librarians fit in? Depending on what type of library you work in, whether you’re a solo librarian, and perhaps even your comfort level learning new skills, knowledge and familiarity with data and data practices may or may not be something in your wheelhouse. I work in a large healthcare system within a team of fourteen librarians and library staff. Our institution has a research arm that is growing and growing, and yet none of us have really been involved in big data or data management practices at our institution. I don’t think that’s very unusual for a place that isn’t also an academic medical center. Can healthcare big data be overwhelming? Yes. Is big data in healthcare worth all the fuss? Yes.

Why should health science librarians get involved with big data in healthcare? With the ever-growing interest and use of data all around us, data isn’t going away anytime soon. Librarians are great at continually staying on top of trends and changes in our field, and I truly believe that health science librarians will become more and more involved, in one way or another, with data initiatives at their institutions. It’s better to be in front of the curve and helping guide the conversation, than trying to catch up when the ship has sailed. Learning about big data will keep librarians relevant. If we look at skills librarians already have, like organization and classification, taxonomies and metadata, those could immediately be leveraged into increasing the quality of research data management practices at our institutions by working with researchers on their data management plans, which many need to include on grant and funding applications. We should also get involved because there are so many free training opportunities available to us from MLA, NLM, and others. If MLA and NLM/NNLM think big data is worth supporting on such a large scale, I am onboard, too.

How might health science librarians get involved with big data in healthcare? This is much trickier and depends a lot on the situation you find yourself in. You might not be able to start any of these activities today or even next year, but knowing how other health science librarians work with big data in their institutions can inspire you to find a way where you are. Reference questions might lead you to big data. If you’ve ever been asked to find data, Kevin Read and his NYU librarian colleagues have created a data catalog (NYU Health Sciences Library, n.d.) for those looking for data sets to use, or for researchers to publish their own data. Assisting on systematic reviews or publications might lead you to big data. A 2018 study looked at Google Trends, an online source for accessing trends in Google’s search data, and laypeople’s searches for asthma (Mavragani, A, K, & KP., 2018). It had some methodological issues that a librarian would have likely pointed out right away. Building relationships with library users might lead you to big data. Librarians at NU Health Sciences Library had conversation with basic and clinical researchers at their institution to learn more about their data needs. These conversations allowed them to tailor library services to fill a gap in “community’s data issues including, but not limited to, the challenges they face when collecting, organizing, and sharing their research” (Read, Surkis, Larson, McCrillis, & Nicholson, 2015).

I firmly believe that working with big data in healthcare will raise the profile of health science librarians and the libraries they work in.

Bibliography

Mavragani, A., A, S., K, S., & KP., T. (2018). Integrating smart health in the US health care system: Infodemiology study of asthma monitoring in the Google era. JMIR Public Health and Surveillance, e24.

NYU Health Sciences Library. (n.d.). Data catalog. Retrieved August 29, 2018, from https://datacatalog.med.nyu.edu/

Read, K. B., Surkis, A., Larson, C., McCrillis, A. G., & Nicholson, J. X. (2015). Starting the data conversation: informing data services at an academic health sciences library. Journal of the Medical Library Association, 131-135.

Categories: Data Science

Upcoming Training for Health Sciences Library Staff

MAR Data Science - Wed, 2018-09-12 11:00

Did you know that you can get free training from the National Network of Libraries of Medicine right from your desktop? Nearly every day, there is a new webinar from NNLM or the National Library of Medicine. Other classes are available through Moodle. Since webinars are available nationally, make sure to take note of time zones. Some upcoming classes that may be of interest to health sciences library staff include:

  • Clinical Information, Librarians and the NLM: From Health Data Standards to Better Health – This interactive webinar series focuses on the roles and products of the National Library of Medicine related to applied medical informatics, particularly as applied to electronic health records systems and clinical research. Sessions are held weekly on Thursdays through October 4, from 12:00-12:40 PM ET.
  • PubMed for Librarians – PubMed for Librarians is made up of six 90-minute segments. These six segments will be presented via WebEx and recorded for archival access. Each segment is meant to be a stand-alone module designed for each user to determine how many and in what sequence they attend. Register for the next live session (part 4) coming up on September 19 from 2:00-3:30 PM ET, or watch a recording.
  • Accessible Library Customer Service – September 19, 1:00-2:00 PM ET – Gain knowledge and tools to provide accessible customer service in your library by joining us for this one-hour webinar! This presentation will give an overview of disability including appropriate terminology, creating an accessible environment, and evaluating current practices for way-finding, emergency preparedness, and web resources. Other topics include budgeting for accessibility, accessible employment, specific service needs, potential partner organizations, and a plethora of tips and resources for future use.
  • ClinicalTrials.gov – September 26, 3:00-4:00 PM ET – This presentation will help you learn how to navigate the site and understand the nuances and limitations of information available on ClinicalTrials.gov.
  • NNLM Research Data Management Webinar Series – The NNLM Research Data Management (RDM) webinar series is a collaborative, bimonthly series intended to increase awareness of RDM topics and resources. The series aims to support RDM within the library to better serve librarians and their institutional communities. The next webinar in this series, Planning, Developing, and Evaluating R Curriculum at the NIH Library, is coming up on October 12 from 2:00-3:00 PM ET.
  • LinkOut for LibrariesNovember 1, 2:00-3:00 PM ET – LinkOut for Libraries provides journal access to PubMed users. Join us for an informational webinar to learn more about this service from the National Library of Medicine. Erin Latta, from the National DOCLINE Coordination Office, will lead this webinar.

In addition to scheduled courses, NNLM has a number of “on-demand” self-paced classes via Moodle, such as:

Most webinars are recorded, so you are encouraged to register for a session of interest, even if you cannot make the live webinar. To register for classes, you just need to create an account.

You can find additional opportunities on our training schedule.

The best way to find out about upcoming trainings, NLM updates and other information from the Network is to subscribe to MAR Weekly Postings, which come out on Fridays.

Categories: Data Science

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

SEA Data Science - 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

Did you miss the first round of MAR funding? Apply now for $19,000

MAR Data Science - Thu, 2018-08-30 13:00

The National Network of Libraries of Medicine, Middle Atlantic Region, a health information outreach program funded by the National Library of Medicine, has funding for two grants of $19,000. Libraries, community-based organizations, schools, health care providers, and other organizations that provide health programming or services within PA, NY, NJ or DE are eligible to apply. Applications are due October 5, 2018, and award funds must be spent by April 30, 2019.

Applications for funding less than $15,000 will not be considered at this time.

Projects can fall under one of these categories:

  • Clinical and Public Health Outreach Award: Projects that enhance clinicians’ and public health workers’ abilities to find and use biomedical and health information in practice and for patient education.
  • Outreach to Consumers Award: Projects that improve health information literacy and increase the ability for patients, family members, students and members of the general public to find and use health information.
  • Health Sciences Library Project Award: Projects that support health sciences librarians as conduits of information management, access, and delivery within their institution and/or outreach community.
  • Health Literacy Project Award: Projects that promote a culture of health literacy within the organization.

Potential applicants are encouraged to review the above RFPs and watch a one hour recorded webinar on writing applications for NNLM MAR funding. Additional questions may be sent to nnlmmar@pitt.edu.

Stay tuned: Another round of funding opportunities will be announced soon to encourage proposals from public libraries or involving public library partnerships!

Categories: Data Science

Data Flash: Hospital or academic or data-interested librarian? 2 opportunities for data-related training, free!

PNR Data Science - Mon, 2018-08-27 08:30

Whether you’re in a hospital or academic or research center or other data-related setting, take a look at these two amazing training opportunities—there’s something for everyone!  And they’re free!

1) “Clinical Information, Librarians and the NLM: From Health Data Standards to Better Health

When we did our regional data needs assessment last year, many of you who are hospital librarians said that you wanted to be able to “speak IT”; in other words, to know more about data standards such as UMLS, SNOMED CT, and more.

Well, here’s your chance!  This interactive webinar series consists of five 30-minute Thursday sessions (each at 9 AM Pacific Time).   It “focuses on the roles and products of the National Library of Medicine related to applied medical informatics, particularly as applied to electronic health records systems and clinical research. The series is specially designed for health sciences librarians and other health information specialists seeking to serve more active roles in their health IT team and better support researchers”.  You’ll learn about not only UMLS and SNOMED CT, but also RxNorm, LOINC, Common Data Elements and the Value Set Authority Center.

Want to dazzle your IT team?  Take this class!

2) Biomedical and Health Research Data Management Training for Librarians

If research data management is more your focus, perhaps for those of you in academic or research center settings, this training could be for you.   It can be tough to “pick up” the skills needed to be a support for researchers, and so an intensive guided course with amazing teachers and assigned mentors is a wonderful chance to immerse yourself and kick start your involvement.

“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.  Note that a letter of commitment from your library is part of the application!

Additional details and the online application are available here, and for questions, please contact the NNLM’s National Teaching Office at  nto@utah.edu .

Of course, we here in the Regional Medical Library are also standing by and always happy to help!

Categories: Data Science

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

SEA Data Science - 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

Applications Open: Biomedical and Health Research Data Management Training for Librarians

NTO Data Science - Thu, 2018-08-23 12:04

Updated 29 Aug 2018

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 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.
    If you are not currently employed, you may seek a letter from 1) a previous employer who can speak to your qualifications, accomplishments, and commitment OR 2) your Regional Medical Library.

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)

SEA Data Science - 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

Public Health Department Funded to Make Data FAIR

GMR Data Science - Thu, 2018-08-02 09:01

The GMR office is excited to announce that Richland Public Health has been granted a Research Data Award to make county-level health data FAIR.

Background:

Health assessments at the county-level are resources health professionals and librarians rely on heavily to inform the development of community health programming, interventions, and grant applications to fund efforts that improve the health, well-being, and quality of life of their constituents. These health assessments include, but are not limited to, Community Health Assessments (CHA), Community Health Improvement Plans (CHIP), and Community Health Needs Assessments (CHNA). These health assessments are expected to be performed and utilized by hospitals, public health departments, and other social service agencies to identify key community health concerns every 3-5 years.

Within Richland County, the raw data collected for these assessments are often siloed.

Project Description

The Making County-Level Health Data Findable, Accessible, Interoperable, and Reusable (FAIR) Initiative will consist of three phases in order to establish and sustain an online interface for local health professionals and librarians to access and analyze county-level health assessment data, as well as educate these individuals on utilizing this resource and creating their own data management plans.

The first phase of this proposed project will be to develop and implement a database where raw data from Richland County health assessments can be accessed and analyzed by local health professionals and librarians.

The second phase will consist of the creation and hosting of a data access and management webinar to introduce Richland County health professionals and librarians to the online interface.

Finally, phase three will provide an additional webinar to 12 rural North Central Ohio Counties in an effort to educate their local health professionals and librarians about data management plans as well as how to access, analyze, and contribute to the Making County-Level Health Data FAIR Initiative database.

Outcomes

A formative and summative evaluation will be used to measure the success of this project. First, the project will use a formative evaluation using the FAIR Guiding Principles to make sure the project meets the prerequisites for proper data management and stewardship. A summative evaluation will be used to determine the success in educating health professionals and librarians about the database.

Categories: Data Science

A glance back: the Framingham Heart Study

SCR Data Science - Tue, 2018-07-31 17:19

This year marks the 70th anniversary of the landmark FrFramingham physiciansamingham Heart Study. It is named for the town of Framingham, MA from which the original cohort (there are now six groups of participants) of 5,209 men and women were recruited.

Heart disease is the number one cause of death in the United States, and it achieved that rank by the 1940s. But for many at the time, it was considered unavoidable consequence of getting older. Fortunately, in 1948, President Harry Truman signed into law the ‘National Heart Act’ which did two things:

  1. Established the National Heart Institute, better known today at the National Heart, Lung and Blood Institute (NHLBI)
  2. Allocated funds for a twenty-year epidemiological heart study

Its milestones over the years have been significant and numerous – here are just a few:

  • In 1967, it was discovered that physical activity reduced the risk of heart disease
  • In 1988, HDL or “good” cholesterol was found to reduce risk of death
  • In 2002, obesity was determined as a risk factor for heart failure

To learn more, you can read a history published in 2014 that details its origins and contributions, including the fact that this study was closely linked to the health of President Franklin D. Roosevelt.

To celebrate the anniversary, Daniel Levy, M.D., Director, Framingham Heart Study, and Chief of the Population Sciences Branch, NHLBI, gave a recorded talk earlier this year.

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Photo Credit: “Framingham Heart Study physicians” by NIH History Office via The Commons (Flickr)

Categories: Data Science

GMR to Fund UC’s 4th Annual Data Day

GMR Data Science - Mon, 2018-07-30 12:19

The GMR office is excited to announce that the University of Cincinnati (UC) has been granted a Research Data Award to host its 2019 Data Day Event!

Background:

UC Data Day is the only event on the University of Cincinnati campus that connects the libraries with researchers and community partners in a collaborative and informative medium. Data Day provides an opportunity to openly discuss opportunities and challenges related to data, and educates the research community on methods for driving discovery through data, a key area of interest for the National Library of Medicine.

Project Description

UC Data Day 2019 will build on the momentum of the three previous Data Day events, and endeavor to promote interdisciplinary learning and collaboration among the University of Cincinnati’s research community and broader Greater Midwest Region. Data Day 2019 will offer a full schedule to engage audience members, reveal solutions to data challenges and foster a community of best practices around improved data management.

The event will offer combinations of engaging keynote addresses, workshops on data analyses and visualization, graduate student poster forums, and panels that provide attendees with knowledge of data practices, usage and services. The official date of Data Day 2019 is in the process of being determined.

Outcomes

The essential goal of Data Day 2019 is to equip researchers with the knowledge and ability to effectively perform data driven research, to better manage their research data across the research lifecycle, to improve their skills in data analytics and visualization, and arm them with pertinent contacts that can address data related concerns.

Categories: Data Science

Could Your Favorite Snack be Causing Manic Episodes?

SCR Data Science - Thu, 2018-07-26 18:07

hot dogs

Baseball season is in full swing and ballparks across the country are serving up a classic ballpark favorite – hot dogs.  In fact, it is estimated that baseball fans alone will con

sume nearly 19 million hot dogs in 2018.  Could they be getting more than they bargain for with this ballpark food choice?

A recent John Hopkins Medicine study collected data between 2007 and 2017 from 1,101 people with and without psychiatric disorders.   Their study found that those who had been hospitalized for mania were more than three times as likely to have had a history of eating cured meat as those without a psychiatric disorder.

Although hot dogs are nitrate-curated, they aren’t the only food item that falls into this category.  Beej jerky, salami, and other processed meats are also included.  Curating meats with nitrates is not a new process and neither are its associated health issues.  In the past, curated meats have been linked to colorectal cancer and neurodegenerative diseases.

While the study did not address cause and effect, it could have an impact on future interventions, according to lead author Robert Yolken, M.D., the Theodore and Vada Stanley Distinguished Professor of Neurovirology in Pediatrics at the Johns Hopkins University School of Medicine.  “Future work on this association could lead to dietary interventions to help reduce the risk of manic episodes in those who have bipolar disorder or who are otherwise vulnerable to mania.”

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Categories: Data Science

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

SEA Data Science - 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

NLM Establishes a Five-Year Development Plan for MEDLINE!

PSR Data Science - Tue, 2018-07-24 14:38

In December 2016, the National Library of Medicine established the MeSH (Medical Subject Heading) Indexing Assessment Project to evaluate the impact on users of assigning MeSH terms to MEDLINE citations. The project findings confirmed the value of MEDLINE indexing and the value of applying selected non-subject metadata to MEDLINE citations. In response to the findings and as part of its Strategic Plan, NLM created the five-year development plan, MEDLINE 2022. A Working Group, comprised of members from across all NLM departments, was charged with the plan’s implementation.

MEDLINE 2022 has eight specific goals describing challenges that must be addressed to maintain the usefulness of MEDLINE as a tool for discovering and analyzing the biomedical research literature:

  1. Investigate the use of authoritative vocabularies in MEDLINE indexing in addition to, or as a partial replacement for MeSH, for some topics or types of metadata, for example, chemical names.
  2. Implement a range of indexing methods to ensure the timely assignment of MeSH or terms from other approved vocabularies to MEDLINE citations.
  3. Support the discoverability of ClinicalTrials.gov content.
  4. Support the pharmacology and toxicology research communities by sustaining and improving the discoverability of chemical information in MEDLINE/PubMed citations.
  5. Support NIH and other funding organizations by ensuring the discoverability of funding information in MEDLINE/PubMed.
  6. Support the genetics research community by adding relevant gene information to MEDLINE/PubMed citations.
  7. Support the NLM pivot to data science as described in the new NLM Strategic Plan.
  8. Update MEDLINE journal requirements to support these goals and strategies.

The goals of MEDLINE 2022 align with the goals of the NLM Strategic Plan, most importantly Goal 1: Accelerate discovery and advance health by providing the tools for data-driven research. MEDLINE has provided access to the biomedical literature for more than 45 years, evolving as publishing and information retrieval have evolved. The MEDLINE 2022 project aims to ensure that MEDLINE continues to evolve to meet the needs of users in an age of data-driven discovery. NLM will keep its many stakeholders informed of progress with the implementation of MEDLINE 2022 by publishing future NLM Technical Bulletin articles with details about different aspects of this project.

Categories: Data Science

All of Us: Imagining the Future; Pondering the Past – Health Information for Public Librarians Symposium, Atlanta 2018

PSR Data Science - Mon, 2018-07-23 16:24

by Peg Eby-Jager, A.M.L.S.
Librarian | Consumer Health Information Specialist

“All is flux; nothing is stationary.”
Heraclitus (c.535 – c.475 BC)

“Just when I discovered the meaning of life, they changed it.”
George Carlin (1937 – 2008)

CHIS Quest
When I found out about the Public Librarians Symposium, late and serendipitously, I’d been scouting for continuing education credits in light of a fast approaching deadline for renewing my Consumer Health Information Specialization (CHIS) certificate; I was a surprised to learn that travel awards were available to public librarians as well. Great news! My thoughts then quickly shifted back to the sobering present with the realization that I’d need to be in Atlanta in about three weeks. Quick work, collegiality, and good fortune were needed, and thankfully everything fell into place. I registered for the meeting, booked travel and accommodations, and leveraged a change in my work schedule. Being awarded a travel grant was, as they say, just gravy, and I was looking forward to attending the Symposium, earning CHIS credits, connecting with colleagues, and learning about the All of Us Research Program – a precision medicine initiative that I knew next to nothing about.

The Symposium

“This year’s conference also offers something special: a symposium dedicated to health information for public librarians…designed to help public librarians develop skills in providing consumer health information to enhance health and well-being and to encourage and expand health literacy throughout the communities.”

From NLM Director’s blog, Musings from the Mezzanine

All of Us

“The All of Us Research Program, is a historic effort to gather data from one million or more people living in the United States to accelerate research and improve health. By taking into account individual differences in lifestyle, environment, and biology, researchers will uncover paths toward delivering precision medicine.”

 

I was in the go-mode for Atlanta. But first, gentle reader, a brief detour through patient data history.

Interest in Consumer Health
The one constant among my professional interests since earning a library degree in 1985 is my abiding interest in consumer health information. And during those thirty-plus years, there have been seismic changes in virtually every aspect of health care – patient records included. My first job as a freshly minted librarian was with the Commission on Professional and Hospital Activities (CPHA), a think tank, whose primary data asset comprised anonymous, patient-level records supplied by over 25% of North American acute care facilities. That was a huge data set, to be sure. However, the limitations of those records compared to what I would be hearing about at the Symposium makes all the difference between planting a single seed and the bounty reaped from a worldwide harvest.

Among CPHA’s many study reports and products was an annual series of books that listed average length of hospital stay, organized by diagnoses and stratified by a few additional criteria. It would never make the NY Times best-seller list, but it was CPHA’s hot product, bringing in significant income that fueled research. And CPHA was pushing the envelope, as their public health researchers worked to develop new analytical models yielding a more precise picture of how precious medical resources were being utilized.

Finding ways to accurately measure utilization of medical resources was The Holy Grail. But in the 1980s, CPHA’s anonymous hospital discharge records offered only a static slice of patient data and were not linked to any longitudinal cohort. Further, patient medical records were typically handwritten by physicians and stored in paper files in their offices. The necessary technology and infrastructure did not yet exist.

book titled Length of Stay showing the front cover and the book opened to pages with lots of data

In 1985, the availability of patient data from longitudinal studies was greatly limited. “Length of Stay” data were derived from anonymous hospital discharge records and were not linked to patient medical records. (Photo credit: Peg Eby-Jager)

To be clear: back in the day, CPHA’s published studies and data products were a big deal. It wasn’t unusual for a client to refer to us as “the only game in town.” But the All of Us Program, as I would soon learn at the Symposium, intends to change the game entirely. Building and sustaining the largest, most diverse, markedly innovative, longitudinal patient data set is the goal. “Change” hardly describes what is in store; a better term would be “reinvention.”

And what better place than Atlanta, a city that has reinvented itself time after time, to begin learning about All of Us?

MLA & M.J.T.
Day One of the Symposium began with a beautiful buffet breakfast offering a range of choices from bacon-and-eggs to copious fresh fruits and yogurt. My body clock was still set on PDT, but a second cup of coffee fueled a speedy circumnavigation of the Hyatt’s Regency Ballroom. Tables were quickly filling, the Symposium would soon kick off, and I didn’t see a single familiar face.

Mary-Kate Finnegan presenting a poster at a symposium

Mary-Kate Finnegan from University of the Pacific in Stockton presenting a poster at the symposium

Pretty quickly, I was invited to join a table near the podium. A friendly person called me over, and introduced herself as “M.J. Tooey,” whose name that I recognized as a past president of MLA. After a warm welcome, introductions, and a little get-acquainted chat with everyone at the table, M.J. clued me in on what to expect at the kickoff.

I had closely followed MLA’s pre-conference planning instructions, and I’d studied the presentations and posters that would be available to Symposium attendees. I knew which presentations I’d attend and which posters I wanted to see. I’d familiarized myself with the Hyatt map, and I knew where to be and when to be there. I definitely had a plan. But M.J. Tooey made sure that I knew that Patti Brennan, the current director of the National Library of Medicine, would soon be joining our table prior to giving her keynote speech. And that was just so very thoughtful and considerate of her. Moments like this leave lasting impressions.

Data-Driven Discovery
Patti Brennan’s keynote focused on “data-powered health” and the critical role of the All of Us Research Program’s one million-plus cohort to the future of precision medicine. Beginning with a quick overview of NLM’s strategic plan, she invited us to consider that every research article begets its own data set, and then to imagine the biomedical discovery implications of harnessing vast quantities of data that are made widely available. She talked about the need to find new ways to get information into the hands of laypeople and how those data could be used by citizen scientists. Dr. Brennan compellingly argued that massive data resources offer a “foundational substrate” for knowledge and discovery, and that the All of Us data set will be a prime factor in data-driven biomedical discovery.

Dr. Brennan is focused on a future in which myriad data-rich resources are widely available. She spoke about radical new possibilities for understanding health rather than focusing primarily on the study of disease states. But a diverse data set is key to success, and building a representationally diverse cohort of over one million people contributing data and biosamples will not be easy. The massive scale of the project is simply mind-boggling.

Data-Data-Data!

Patti Brennan writes regularly about the value of that ambitiously imagined, data-driven future on her blog, NLM Musings from the Mezzanine. “[W]e released NLM’s strategic plan, A Platform for Biomedical Discovery and Data-Powered Health. Concurrently the National Institutes of Health announced a draft Strategic Plan for Data Science.”

Precision Medicine

“[P]recision medicine is ‘an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment, and lifestyle for each person.’ …It is in contrast to a one-size-fits-all approach, in which disease treatment and prevention strategies are developed for the average person, with less consideration for the differences between individuals.”

From Genetics Home Reference

 

All of Us and Public Librarians
Public librarians may play a role in helping to raise awareness of the All of Us Research Program, and Dr. Brennan raised the question of how that role could be fostered. Toward the end of her talk, she posed the question of what can be done to assist public libraries, and I’ll be interested to see what sort of outreach takes place. Public librarians, however, do not need to wait for direction. MLA’s Consumer Health Information Specialization (CHIS) offers an excellent starting point.

I truly enjoyed the CHIS courses I took, and after completing Level I requirements, I pushed a little harder and earned a Level II certificate. I learned a lot, and I’d encourage my public library colleagues – not just librarians, but paraprofessionals as well – to take an introductory course. Building on my public service skills and more effectively helping patrons achieve greater health literacy is the greatest benefit of CHIS coursework. There is no charge for the courses; you can pace yourself. And there’s no pressure to complete work on a certificate. The bottom line is that the benefits are well worth the effort, for us and for our patrons!

CHIS

“By earning your CHIS, you acquire skills and knowledge needed to become a confident, expert provider of health information to your community.” Learn more about CHIS at the Medical Library Association website. NNLM offers a sponsorship which covers the CHIS application fee for library personnel who take the required number of courses.

CHIS Courses

  • Beyond an Apple a Day: Providing Consumer Health Information at Your Library
  • Stand Up for Health: Health and Wellness Services for Your Community

Find more CHIS opportunities by browsing the list of all NNLM classes.

Categories: Data Science

Data Flash: “Storage Wars”

PNR Data Science - Wed, 2018-07-11 05:00

You may have seen the feature on the front page of our website, “Where in the World are the PNR Coordinators?” But, we don’t always report back on our travels!  So, here is a quick view of a conference I attended on behalf of the NNLM-PNR, that took place in Bozeman, MT last month, called “Open Repositories 2018”.  What is an open repository?  I like this definition from the “Repositories Support Project”:

“A digital repository is a mechanism for managing and storing digital content. Repositories can be subject or institutional in their focus. Putting content into an institutional repository enables staff and institutions to manage and preserve it, and therefore derive maximum value from it… Repositories use open standards to ensure that the content they contain is accessible in that it can be searched and retrieved for later use.”

I don’t work with repositories directly, so this conference was basically like drinking water from a fire hose.  The attendees were a mix of librarians/library staff and people from the IT side of running repositories, meaning that my comprehension of a given session could range from about 5% (for the very techie ones) to 100%.  And that was fine—I got a great introduction to the issues involved in starting and running repositories, and learned about some new trends, some areas of conflict and some growing pains (hence the title of this post).  For example, take a look at this presentation by Peter Sefton.  I pretty much understand the whole section above the picture of the boat, and then an average of about 65% of what’s below it; that feels worth it to me!   It was an international conference, so the perspective on how repositories are handled was global.   I would never otherwise have heard of Australian Sefton’s work, or been able to attend a session on the Digital Repository of Ireland.   I even got to spend a full day attending two workshops on Wikidata and Wikipedia editing (did I mention that the NNLM’s next Online Wikipedia Edit-a-Thon is November 7 this year?).

And, one great thing about open conferences and all things open is that you can often gather the content for yourself after the conference even if you didn’t attend it.  Here are some options if you want more information about what happened at this conference:

YouTube stream of everything held in the main session space (including the Digital Repository of Ireland presentation)

Notes from sessions

The program

— Social media: Twitter= @OR2018MT, Instagram= @openrepositories18

I leave you with three photos from the experience.  One is of me with my poster highlighting three of the National Library of Medicine’s eight data sharing repositories: ClinicalTrials.gov, PubChem and GenBank.  And the other two are from my visit to the Museum of the Rockies, which features the most amazing dinosaur exhibit I’ve ever seen, and a thing I love—a historic house which was moved to the museum site, furnished appropriately to the period in which it was built, and staffed by costumed and knowledgeable living history interpreters.

Categories: Data Science

Data Management for Librarians CE workshop

SEA Data Science - 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

DataFlash: Staying Informed

PNR Data Science - Wed, 2018-06-27 17:38

Network Big data and research data management are evolving quickly and it can be challenging to keep up with developments in the field. Social media is a great way to keep track and to ask questions of colleagues, researchers, and vendors. Below are several links worth checking out…

CANLIB-DATA is a listserv for issues related to research data in Canadian libraries, with more than 350 subscribers.

DataCure “is a Google group of librarians and information professionals whose members have significant roles or responsibilities in providing services in managing or curating research data. Datacure exists to provide a safe space for data professionals to talk frankly about their ideas, projects, successes, and struggles with their work.”1

Datalibs distribution list is intended to serve as both a bulletin board for news, upcoming events, and continuing education/job opportunities as well as a forum that librarians can use to post questions or to initiate and engage in discussions. Join via the Journal of eScience Librarianship website.

IASST-L  The International Association for Social Science Information Services and Technology (IASSIST) is an international organization of professionals working with information technology and data services to support research and teaching in the social sciences. Join IAssist ($50 USD annually) to access their organization’s email discussion list IASST-L.

MLA Data-SIG is the Medical Library Association’s data related special interest group. Membership in the MLA is required to access the SIG list serv.

@NNLM_RD3 is the NNLM RD3: Resources for Data-Driven Discovery website’s Twitter feed. When tweeting, use the #datalibs hashtag to reach out to other data librarians.

RDAP or the Research Data Access & Preservation Summit is relevant to the interests of data managers, data curators, librarians working with research data, and researchers and data scientists. RDAP is currently in transition and has moved its listserv to a new server. RDAP’s new e-mail address may be the best place to inquire about further developments.

RESEARCH-DATAMAN is an email discussion list for United Kingdom education and research communities.

The data science departments on your own campus may also host listservs, Twitter sites, Facebook pages, or blogs. The University of Washington’s eScience Institute is just one example of the data related centers available near the PNR’s home base. If you know of additional data related listservs, Google Groups, or Twitter sites, share them with your colleagues by entering them in the comments section below.

 

1  Barbrow S, Brush D and Goldman J. (2017). Research data management and services: Resources for novice data librarians; ACRL College and Research Libraries News, 78(5)

Categories: Data Science

GMR Funds Innovative Pilot Program to Teach Graduate Students Research Data Management

GMR Data Science - Tue, 2018-06-26 16:12

 

The GMR office is excited to announce that Tina Griffin at the University of Illinois at Chicago has been granted a Research Data Award to develop the Research Data Management Best Practice Implementation Program for Graduate Students in STEM and Health Sciences!

Background:

Today, data management practices by students are largely learned by conforming to the laboratory culture and adopting habits from the environment in which they work. There is no known national mandatory data management training for students. The recent NLM strategic plan (PDF) recognizes the importance of the role of libraries in advancing open science and data management, and many academic libraries are heeding the call by providing research data management education services.

Project Description

This project will pilot a flipped classroom model to present students with appropriate research data management practices in an eight-week intensive program. In this program, the students are expected to engage with the instructional content outside the classroom, while using the in-person classroom time to engage in activities that demonstrate competency and understanding of the content. The 8-week program will cover the following topics:

  1. Introduction to Data management principles;
  2. Deep Dive – discipline standards, DMP draft;
  3. Project map, project narrative starts;
  4. Folder structure develops;
  5. File naming, table of contents, indexing develop;
  6. Templates develop;
  7. DMP finalized, project narrative finalized; and
  8. Ongoing practice, personal policy developed

The classroom time will be used by the students to systematically develop and holistically integrate these practices in to their research projects. This pilot project is unique in that it addresses both education about data management practices and the integration of best practices into the research workflow in a personalized manner.

Outcomes

The outcome of this pilot may introduce a new method to serve more students in a more effective manner with better long-term adoption of data management best practices. It also begins a longitudinal study to determine how these practices may contribute to successful dissertation/thesis completion and/or how they may prepare students for the workforce.

Categories: Data Science

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