Love Data Week, set for Feb. 9 to 13, is an international celebration of all things data.

Each year, the Data and Bioinformation Services team at the Health Sciences and Human Services Library engages the university community on topics such as data management, sharing, wrangling, and visualization, as well as open and reproducible science.

This year’s theme is “Where’s the Data?,” which encourages us to think about data’s journey from collection through storage and preservation.

Join us for the events below.

Where’s the Data? Finding and Accessing Research Data at UMB

Date and time: Wednesday, Feb. 11, noon to 1:30 p.m.
Location: Zoom
Registration: Register for the session (opens in a new window)

Need to access clinical or administrative data for research but not sure where to start? After a brief overview of HSHSL-supported data resources, this virtual session will feature experts from ICTR and PRC to explain the process of requesting UMMS EPIC data and administrative claims datasets.

This session is ideal for faculty, students engaged in research, and research staff. Accessing data does not have to be a mystery.

Speakers:

• Amy Yarnell, MLS
  Head of Data and Bioinformation Services, Health Sciences and Human Services Library
• Eberechukwu Onukwugha, PhD
  Professor; Executive Director, Pharmaceutical Research Computing Center; Department of Practice, Sciences, and Health Outcomes Research; University of Maryland School of Pharmacy
• Wanda Hill, MS, BSN, RN
  Director of Operations, UMB Institute for Clinical and Translational Research

Data and Doughnuts

Date and time: Thursday, Feb. 12, 10 a.m. to noon
Location: HSHSL first floor

Stop by our table to grab a doughnut and chat with the HSHSL Data Services team. Then from 11 a.m. to noon, visit the HSHSL Positivi-tree and celebrate self-care for Valentine’s Day.

Managing Your Qualitative Data with the Qualitative Data Repository (QDR)

Date and time: Thursday, Feb.12, 1 to 2 p.m.
Location: Zoom
Registration: Register for the session (opens in a new window)

In this webinar, researchers will explore options for sharing qualitative data, with a special focus on the Qualitative Data Repository (QDR), to which the University of Maryland, Baltimore has an institutional membership. Participants will gain a clearer understanding of qualitative data sharing norms and practices across the social, health, and other human focused sciences.

The session will highlight practical steps researchers can take to keep qualitative materials organized throughout any project, which also can support future archiving and re use of the materials they collect. QDR’s Associate Director will further showcase examples of nuanced data sharing approaches from current published data projects, including sensitive data secured under different levels of access control, will demonstrate how the deposit process at the repository works, and highlight data available for pedagogical purposes as well.

This webinar is intended for faculty, students, and staff who are using qualitative or multi method techniques. It is especially useful for those preparing data management or data sharing plans (DMPs or DMSPs) for federal or private foundation funding applications.

Speaker: Dessislava Kirilova, Associate Director, Qualitative Data Repository

Caption the Chart Challenge

Dates: Feb. 9 to 13
Location: HSHSL

Find one of our chart displays around the HSHSL and try your hand at writing a creative and funny caption.

Questions? Contact: Amy Yarnell, Head of Data and Bioinformation Services ayarnell@hshsl.umaryland.edu 

The HSHSL is celebrating International Open Access (OA) Week with a five-day challenge designed to improve discovery of your scholarly work! Each day we will email you with a brief but meaningful activity, including: 

• Creating an ORCiD and connecting it to your Scopus author profile 
• Locating OA journals in your research area 
• Learning about repositories and data sharing 
• Utilizing MyNCBI 

If you complete any of the activities and fill out our evaluation survey at the end of the challenge, you will be entered to win some library swag! 

Sign up to receive daily challenges from October 20-24, 2025.

If you want to learn more about how the HSHSL supports Open Access, visit the Open Access LibGuide.

Contact publishing@hshsl.umaryland.edu with questions.

Love Data Week (Feb. 10 to 14) is an international celebration of all things data! Each year, the Data and Bioinformation Services team at the Health Sciences and Human Services Library looks forward to engaging the University on issues like data management, sharing, wrangling, and visualization, as well as open and reproducible science. 

This year’s theme is “Whose Data Is It, Anyway?” which asks us to consider “who owns data compared to who uses data” and to think about “where the data came from before using it.” 

Check out the week’s events below: 

• Join us for virtual Data Management Planning Office Hours on Tuesday, Feb. 11, from 9:30 to 11 a.m. to ask your specific data management and sharing questions. Zoom link
• Talk with librarians about data services at our pop-up table at your school during the week of Feb. 10 (schedule below).  Come and learn about data and bioinformation services at the HSHSL and grab a piece (or three) of candy! 
  • School of Pharmacy – Monday, Feb. 10, Noon to 1 p.m. (Atrium) 
  • [CANCELLED DUE TO INCLEMENT WEATHER] School of Dentistry – Tuesday, Feb. 11, Noon to 1 p.m. (Ground Floor) 
  • [CANCELLED DUE TO INCLEMENT WEATHER] School of Nursing – Tuesday, Feb. 11, 2 to 3 p.m. (1st Floor Lobby)  
  • School of Social Work – Wednesday, Feb. 12 at 11:15 a.m to 12:15 p.m. (Atrium) 
  • School of Medicine – Thursday, Feb. 13 at Noon to 1 p.m. (Bressler Lobby) 
• Gear up for Valentine’s Day by celebrating at the HSHSL on Thursday, Feb. 13, 9:30 to 11 a.m.! Join us on the 1st Floor to grab a doughnut and coffee, talk about your data needs, and participate in a special self-care activity in the Weise Gallery.

Looking for more ways to participate? 

• Visit the UMB Data Catalog. Explore the great research being done at UMB. Talk to us about cataloging your datasets! For more on the Data Catalog check out this video introduction! 
• Adopt a Dataset or attend a webinar with ICPSR, the official Love Data Week organizers and an excellent place to find data! Visit their site for more information. 
• Join our friends at the Network of the National Library of Medicine (NNLM) throughout the week for their series of workshops on topics including tools for finding and sharing data, data visualizations in Excel, and From Data to Knowledge to Equitable Health Transformation in the Age of AI. (Note: You must sign up for a free NNLM account to register).
  [THIS EVENT HAS BEEN CANCELLED]

Don’t forget to follow the HSHSL and Love Data Week on social media! #LoveData25 #UMBLovesData 

Questions? Contact Amy Yarnell, Head of Data and Bioinformation Services, and Christine Nieman Hislop, Data Services Librarian at data@hshsl.umaryland.edu. 

Every month, we will be highlighting new datasets added to the UMB Data Catalog. The UMB Data Catalog facilitates discovery of data by providing a searchable and browsable collection of records describing datasets generated by UMB researchers. Sharing a record of your data in the Catalog is also a great way to demonstrate compliance with data sharing policies!

These latest records showcase data on opioid treatment availability, COVID-19 misinformation on TikTok, and immune response in HIV-infected patients.

Congrats to our UMB researchers on these publications!

Title:  County-level factors associated with a mismatch between opioid overdose mortality and availability of opioid treatment facilities
Description: Identifies characteristics of United States (US) counties with high rates of opioid overdose mortality and low rates of opioid treatment facilities.
Authors: John G. Rizk, Jannat Saini, Kyungha Kim, Uzma Pathan, Danya M. Qato
URL: https://datacatalog.hshsl.umaryland.edu/dataset/224

Title: #Coronavirus on TikTok: user engagement with misinformation as a potential threat to public health behavior
Description: Examines factors associated with user engagement with COVID-related misinformation on the social media platform, TikTok.
Authors: Jonathan D. Baghdadi, K.C. Coffey, Rachael Belcher, James Frisbie, Naeemul Hassan, Danielle Sim, Rena D. Malik
URL: https://datacatalog.hshsl.umaryland.edu/dataset/225

Title:  IFNa induces CCR5 in CD4+ T cells of HIV patients causing pathogenic elevation
Description: Investigates whether elevated circulating interferon-alpha (IFNα) promotes widespread immune cell alterations and persists post-therapy, furthering understanding of why non-elite controller (EC) HIV patients continue to need treatment.
Authors: Hélène Le Buanec, Valérie Schiavon, Marine Merandet, Alexandre How-Kit, Hongshuo Song, David Bergerat, Céline Fombellida-Lopez, Armand Bensussan, Jean-David Bouaziz, Arsène Burny, Gilles Darcis, Mohammad M. Sajadi, Shyamasundaran Kottilil, Daniel Zagury, Robert C. Gallo
URL: https://datacatalog.hshsl.umaryland.edu/dataset/226

Thanks to Metadata Librarian, Eva Greitzer for creating and compiling these records!

Want to see your data listed in the UMB Data Catalog? Submit this form to get the process started.

Questions? Email us at data@hshsl.umaryland.edu.

R is an open-source programming language that is ideal for working with statistics and data. Here at CDABS, we love R for many reasons: It’s free, flexible, and friendly! In this series, we will focus on the Tidyverse, a collection of R packages designed for data science. The Tidyverse makes data manipulation, exploration, and visualization simple and intuitive. These packages provide excellent tools for cleaning, analyzing, and visualizing data, all while writing readable and maintainable code. Sign up for one or both sessions, but be advised that the second session will require a minimal familiarity with R.

See full session descriptions below and register here:

July 24 Data Wrangling with R — Introduction to the Tidyverse

This session will introduce participants to the basics of getting started with R and RStudio and introduce the workhorse package dplyr.  Participants will get hands-on experience wrangling real datasets.

Topics covered include:

• Navigating RStudio
• Key R concepts and terminology
• Importing data from external files
• Subsetting and filtering data
• Split-Apply-Combine analysis workflow

Prerequisites: none

July 25 Data Visualization in R with ggplot2

Learn how to use ggplot2, a robust Tidyverse package  used to create high quality graphics for exploring and communicating your data. We will go beyond basic graphs and learn how to customize and annotate our graphs for more effective storytelling. Participants will have the best experience if they attended session one in this series or have some previous experience with R and the Tidyverse.

Topics covered include:

• Visualization best practices
• Grammar of graphics – ggplot2 layers, aesthetics, and geoms
• Choosing an effective graph type for your data
• Customizing labels, axes, legends, and more
• Choosing a color palette and themes

Prerequisites: Session one in this series, or familiarity with navigating RStudio and basic concepts in R.

Questions? Contact: Amy Yarnell, data services librarian at data@hshsl.umaryland.edu.

The Center for Data and Bioinformation Services (CDABS) is the University of Maryland Health Sciences and Human Services Library hub for data and bioinformation learning, services, resources, and communication

Sign up to get DABS delivered to your email or RSS feed.

Every month, we will be highlighting new datasets added to the UMB Data Catalog. The UMB Data Catalog facilitates discovery of data by providing a searchable and browsable collection of records describing datasets generated by UMB researchers. Sharing a record of your data in the Catalog is also a great way to demonstrate compliance with data sharing policies!

The latest records showcase datasets from the fields of neuroscience and physiology, molecular biology and malaria studies, and library science and education.

Congrats to our UMB researchers on these publications!

Title: Genotyping Plasmodium falciparum gametocytes using amplicon deep sequencing
Description: A genotyping method that detects distinct gametocyte clones and estimates their relative frequencies was developed to understand the dynamics of gametocyte production in polyclonal Plasmodium falciparum infections using a specific marker and amplicon deep sequencing to genotype mature gametocytes.
Authors: Jimmy Vareta, Natalie A. Horstman, Matthew Adams, Karl B. Seydel, Robert S. McCann, Lauren M. Cohee, Miriam K. Laufer, Shannon Takala‑Harrison
URL: https://datacatalog.hshsl.umaryland.edu/dataset/221

Title: Differential nanoscale organization of excitatory synapses onto excitatory vs. inhibitory neurons
Description: Confocal and DNA-PAINT super-resolution microscopy was used to compare scaffold protein organization in excitatory principal neuron synapses and parvalbumin-expressing interneuron synapses.
Authors: Poorna A. Dharmasri, Aaron D. Levy, Thomas A. Blanpied
URL: https://datacatalog.hshsl.umaryland.edu/dataset/222

Title: Increasing student engagement using an Amazing Race-style competition
Description: Evaluations of the “Amazing Race: Drug Information Edition,” an orientation activity designed to introduce first-year pharmacy students to library and drug information resources.
Authors: Emily F. Gorman
URL: https://datacatalog.hshsl.umaryland.edu/dataset/223

Thanks to Metadata Librarian, Eva Greitzer for creating and compiling these records!

Want to see your data listed in the UMB Data Catalog? Submit this form to get the process started.

Questions? Email us at data@hshsl.umaryland.edu.

Every month, we will be highlighting new datasets added to the UMB Data Catalog. The UMB Data Catalog facilitates discovery of data by providing a searchable and browsable collection of records describing datasets generated by UMB researchers. Sharing a record of your data in the Catalog is also a great way to demonstrate compliance with data sharing policies!

The latest records showcase datasets from the fields of cardiac surgery, ophthalmology, and physical therapy.

Congrats to our UMB researchers on these publications!

Title: Development of a Reproducible Swine Model of Chronic Ischemic Mitral Regurgitation: Lessons Learned
Description: Establishes a swine model as a platform to better understand the mechanism of ischemic mitral regurgitation (IMR) and subsequently to test novel repair techniques.
Authors: Chetan Pasrija, Rachael W. Quinn, Hani Alkhatib, Douglas Tran, Daniel Bernstein, MaryJoe Rice, Ethan Koloff, David Morales, Michael N. D’Ambra, Mark R. Vesely, James S. Gammie
URL: https://datacatalog.hshsl.umaryland.edu/dataset/218

Title: The optic nerve lamina region is a neural progenitor cell niche
Description: Demonstrates that the optic nerve lamina region (ONLR) possesses an age-depletable neural progenitor cell (NPC) niche, with unique characteristics and culture requirements.
Authors: Steven L. Bernstein, Yan Guo, Rebecca Fawcett, Candace Kerr, Jeffrey Stern, Sally Temple, Zara Mehrabian
URL: https://datacatalog.hshsl.umaryland.edu/dataset/216

Title: Hip Abductor and Adductor Rate of Torque Development and Muscle Activation, but Not Muscle Size, Are Associated With Functional Performance
Description: Investigates the relationship of the hip abductor/adductors muscle strength, activation, and size with functional performance.
Authors: Marcel Bahia Lanza, Kelly Rock, Victoria Marchese, Odessa R. Addison, Vicki L. Gray
URL: https://datacatalog.hshsl.umaryland.edu/dataset/217

Thanks to Metadata Librarian, Eva Greitzer for creating and compiling these records!

Want to see your data listed in the UMB Data Catalog? Submit this form to get the process started.

Questions? Email us at data@hshsl.umaryland.edu.

Happy Love Data Week! To kick things off, we are publishing the first in a new monthly series showcasing recent submissions to the UMB Data Catalog. The UMB Data Catalog facilitates discovery of data by providing a searchable and browsable collection of records describing datasets generated by UMB researchers. Sharing a record of your data in the Catalog is also a great way to demonstrate compliance with data sharing policies!

The latest records showcase datasets focusing on the biodiversity of mosquito bacterial communities, the influence of high-performance media on extracellular vesicles, the role of the dorsal bed nucleus of the striatal terminalis in motivated behaviors, and a rapid, cost-effective protocol for single nucleus isolation. Congrats to our UMB researchers on these publications!

Title: An optimized protocol for single nuclei isolation from clinical biopsies for RNA-seq
Authors:  Thomas V. Rousselle, Jennifer M. McDaniels, Amol C. Shetty, Elissa Bardhi, Daniel G. Maluf, Valeria R. Mas
URL: https://datacatalog.hshsl.umaryland.edu/dataset/209

Title: Approaches to Potentiated Neuroprotective Treatment in the Rodent Model of Ischemic Optic Neuropathy
Authors: Zara Mehrabian, Yan Guo, Neil R. Miller, Amanda D. Henderson, Steven Roth, Steven L. Bernstein
URL:  https://datacatalog.hshsl.umaryland.edu/dataset/206

Title: Culture Condition of Bone Marrow Stromal cells Affects Quantity and Quality of the Extracellular Vesicles
Authors: Amanda L. Scheiber, Cierra A. Clark, Takashi Kaito, Masahiro Iwamoto, Edwin M Horwitz, Yuka Imamura Kawasawa, Satoru Otsuru
URL: https://datacatalog.hshsl.umaryland.edu/dataset/210

Title: Relative contributions of various endogenous and exogenous factors to the mosquito microbiota
Authors:  Haikel N. Bogale, Abdoulaye K. Kone, Matthew V. Cannon, Ogobara K. Doumbo, Kalil Keita, Mahamadou A. Thera, Denka Camara, Christopher V. Plowe, Yaya Barry, Mark Travassos, Moussa Keita, Seth Irish, Drissa Coulibaly, David Serre
URL: https://datacatalog.hshsl.umaryland.edu/dataset/211

Thanks to Metadata Librarian, Eva Greitzer for creating and compiling these records!

Want to see your data listed in the UMB Data Catalog? Submit this form to get the process started.

Questions? Email us at data@hshsl.umaryland.edu.

Love Data Week (Feb. 12 to 16) is an international celebration of all things data! Each year, the Center for Data and Bioinformation Services (CDABS) at the Health Sciences and Human Services Library (HSHSL) looks forward to engaging our community on issues like data management, sharing, wrangling, and visualization, as well as open and reproducible science.

This year’s theme is “My Kind of Data,” which is meant “to explore the personal aspect of data, focusing on equity, inclusion, and creating a kinder world through data.” Check out the week’s events below and follow the links to register:

Panel Discussion: Telling Baltimore Stories Through Data
February 15, 2024, 12:00pm to 1:30pm
Zoom
Register
Panelists:
      Cheryl Knott, Assistant Director, Baltimore Neighborhood Indicators Alliance – Jacob France Institute
      Ryan Little, Data Editor, The Baltimore Banner
      James Sadler, Director of Research, Baltimore’s Promise

Join us for an engaging virtual panel discussion that aims to introduce the UMB community to diverse datasets about Baltimore. This event will offer valuable insights into data science, analytics, and visualization. During our conversation, panelists will introduce their projects and reflect on their experience working with data for social justice, offer suggestions to achieve a fair representation of diverse communities in Baltimore, and discuss tools that aided in resolving these challenges. By bringing together experts in the field, we aim to encourage university–community partnerships and support data initiatives that positively impact the city. 

And check out these events from our friends at NNLM and ICPSR:

The Network of the National of Library of Medicine (NNLM) Region 1 presents Artificial Intelligence & Healthcare: An Overview for the Curious
February 13, 2024, 2:00 pm to 3:00 pm
Register at NNLM

AI is widely utilized in healthcare. This presentation provides a friendly introduction to the topic for librarians, health professionals, and anyone with an interest in the topic. Attendees will come away informed about the field’s history, conversant with definitions of important concepts, an understanding of how AI can become biased (and what that means for patients), and familiar with some of the many ways that AI is currently being used in healthcare.

ICPSR Love Data Week Events
As the official organizers of Love Data Week, the ICPSR (Inter-university Consortium for Political and Social Research) data repository has an exciting week of webinars planned to introduce some of their many data resources. Topics include:

• Data Sharing for Demographic Research (DSDR) – A Population Health Data Archive
• Child and Family Data Archive (CFData)
• Balancing Data Sharing and Protection
• Patient-Centered Outcomes Data Repository (PCODR)
• Metadata Documentation Portal

They are also continuing their annual Adopt-A-Dataset event! Visit the ICPSR website for more information and to register.

Questions? Reach out to Data Services Librarians Amy Yarnell and Irma Fraticelli at data@hshsl.umaryland.edu

How do I write a data management plan? Where should I share my research data? How can I make a graph like I saw in a journal article? To these and other questions, CDABS may have the answers.

The Center for Data and Bioinformation Services (CDABS) is the HSHSL’s hub for data and bioinformation learning, services, resources, and communication. We offer a comprehensive range of services for working with data at each stage of your research project, from do-it-yourself guides and tutorials to interactive workshops and personalized consultations.
CDABS offers:

• Support for writing NIH-compliant Data Management and Sharing Plans, including expert feedback on plans
• Instruction in R and Python programming
• The UMB Data Catalog, which provides descriptions of datasets from UMB researchers
• Facilitated access to special datasets, repositories, and data management tools, such as All of Us, ICPSR, and OSF
• Free and individualized consultations on a wide range of topics, such as choosing a data repository, finding secondary datasets, developing file-naming schemes, and visualizing data

Visit the CDABS web portal to quickly and easily navigate the many data and bioinformation related resources and services we provide at the HSHSL, as well as those on campus and beyond.

For questions, contact your Data Services Librarians Amy Yarnell and Irmarie Fraticelli at data@hshsl.umaryland.edu.

Love Data Week (Feb. 13 to 17) is an international celebration of all things data! Each year, the Center for Data and Bioinformation Services (CDABS) at the Health Sciences and Human Services Library (HSHSL) looks forward to engaging our community on issues like data management, sharing, wrangling, and visualization, as well as open and reproducible science.

This year for Love Data Week we are focused on the new NIH Data Management and Sharing Policy that recently came into effect January 25, 2023. If you will be submitting an NIH grant application in the near future, CDABS is here to help! Be sure to check out our new resource guide on the topic.

You may also be interested in the following Love Data Week events hosted by our friends at the Network of the National Library of Medicine (NNLM) and ICPSR:

Navigating the New NIH Data Management and Sharing Policy with ICPSR’s NIH-funded Projects: DSDR, NACDA, and NAHDAP, Mon. Feb. 13 1:00pm ET

Please join us for a webinar about ICPSR’s NIH-funded Projects: DSDR, NACDA, and NAHDAP. Data Sharing for Demographic Research (DSDR) is funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development. DSDR advances population health and human development research by offering access to data on mother and child health, health disparities, and the human lifecycle for secondary analysis. NACDA is the National Archive of Computerized Data on Aging and is funded by the National Institute on Aging. For nearly 40 years, NACDA has sought to support behavioral and social science research on healthy aging worldwide by making longitudinal data resources freely available. The National Addiction & HIV Data Archive Program (NAHDAP) is funded by the National Institute on Drug Abuse (NIDA). Since 2009, NAHDAP’s mission has been to facilitate research on drug addiction and HIV infection by acquiring, enhancing, preserving, and sharing data.  Registration link

Loving Longitudinal Data: Added Value Access to NACDA Collections Using the NACDA Colectica Portal, Tues. Feb. 14 2:00pm ET

For nearly 40 years, NACDA has been ICPSR’s archive for data on aging. NACDA hosts collections funded by the National Institute on Aging, and with NIA’s support provides preservation and access to data from the Midlife in the United States study (MIDUS), the National Social Life, Health, and Aging Project, and many more longitudinal data collections. During this webinar, we will provide an overview of NACDA and the NACDA Colectica Portal, and describe the benefits of accessing NACDA through the portal and the NACDA website.   Registration link

Creating Data Management Plans with DMPTool, Wed. Feb. 15 1:00pm ET

The DMPTool is a free tool that walks users through creating comprehensive data management plans. This webinar will guide attendees through data management plan basics, creating a DMPTool profile, and exploring available templates and planning resources.  Registration link (may need to create or log in to free NNLM account to register)

All of Us Researcher Workbench, Thurs. Feb 16 3:00pm ET

This presentation will provide a look at the NNLM All of Us Research Program’s Researcher Workbench, which is a cloud-based platform where registered researchers can access Registered and Controlled Tier data. Its powerful tools support data analysis and collaboration.  Registration link

Finally, as always, you can join the conversation on social media #LoveData23 and #UMBLovesData.

Questions? Contact Amy Yarnell, data services librarian, at data@hshsl.umaryland.edu.

The Center for Data and Bioinformation Services (CDABS) is the University of Maryland Health Sciences and Human Services Library hub for data and bioinformation learning, services, resources, and communication.

To read more of our content and stay informed please fill out the form to subscribe here: https://www2.hshsl.umaryland.edu/cdabs/communications

Understanding Algorithmic Bias

Algorithm. Machine Learning. Artificial Intelligence. We might feel like we are encountering these terms more and more every day, and yet they can remain mysterious and intimidating to those who do not work directly with them. What should we make of these tools? — Flashy buzzwords, magic bullets for solving any problem, dystopian nightmare in the making? Perhaps a mix of all three, or somewhere in between.

First – let’s unpack these related terms (definitions from NNLM Data Glossary)

• Algorithm – “a set of instructions that is designed to accomplish a task. Algorithms usually take one or more inputs, run them systematically through a series of steps, and provide one or more outputs.”
• Artificial Intelligence – “actions that mimic human intelligence displayed by machines and to the field of study focused on this type of intelligence. AI consists of computer programs that are typically built to adaptively update and enhance their own performance over time.”
• Machine Learning – “a type of Artificial Intelligence. Machine Learning involves sophisticated algorithms which can be trained to sort information, identify patterns, and make predictions within large sets of data.”

Algorithms are all around us – deciding things like which Facebook posts we see, what route our GPS takes, and which results come up first in a Google search. Algorithms are part of decision-making software in domains such as law enforcement, health care, finance, and human resources.

While algorithms and machine learning solutions can seem like magic, it is important to keep in mind that they are built by humans and based on existing and often flawed and incomplete data. What happens when the data used to build an algorithm is based on outdated racist, and/or sexist policies? What if the algorithm cannot be validated because the company that owns it either does not know how it works themselves, or does not want others to know? What if you are contributing data to an algorithm without knowing it?

Join us for a Coded Bias Virtual Discussion Event

If these issues interest you, join CDABS and the HSHSL Diversity and Inclusion Committee for a virtual discussion of the film Coded Bias. Coded Bias, directed by Shalini Kantayya, explores the fallout of MIT Media Lab researcher Joy Buolamwini´s startling discovery that facial recognition does not see dark-skinned faces and women accurately, and her journey to push for the first-ever legislation in the U.S. to govern against bias in the algorithms that impact us all.  

Register below for one of two facilitated 90-minute discussion sessions. We’ll discuss what it means to create artificial intelligence technologies and algorithms that do not encroach upon the civil liberties of people of color, and how this question ties into broader conversations around health equity and social justice. What has the field of Artificial Intelligence gotten right so far and in what direction(s) should it head in the future? Registered participants will receive a link to view the film between November 9^th and 16^th.

Space for this event is limited – sign up now!

Register for Discussion Session 1, Tues. Nov. 15 from 12:00-1:30 PM

Register for Discussion Session 2, Fri. Nov. 18 from 12:00-1:30 PM

Questions? Contact: Amy Yarnell, data services librarian, at data@hshsl.umaryland.edu.

The Center for Data and Bioinformation Services (CDABS) is the University of Maryland Health Sciences and Human Services Library hub for data and bioinformation learning, services, resources, and communication

Sign up to get DABS delivered to your email or RSS feed.

The HSHSL is celebrating International Open Access (OA) Week with a 5-day challenge designed to improve discovery of your scholarly work! Each day we will email you with a brief but meaningful activity, including:

• Creating an ORCiD and connecting it to your Scopus author profile
• Locating OA journals in your research area
• Learning about repositories and data sharing
• Utilizing MyNCBI

If you complete any of the activities and fill out our evaluation survey at the end of the challenge, you will be entered to win some library swag!

Sign up to receive daily challenges from October 24 – 28, 2022

Learn R this fall with CDABS

The Center for Data and Bioinformation Services (CDABS) will be holding an R workshop the last two Wednesday (21st & 28th) and Thursday (22nd & 29th) in September. All sessions run from 1:00pm to 4:00pm and meet online. Space is limited so register now!

R is an open-source programming language that is ideal for working with statistics and data. Here at CDABS, we love R for many reasons: It’s free, flexible, and friendly! It’s also a great tool for creating reproducible data analyses and visualizations.

In this series we’ll start with the basics of R and the RStudio environment, move to more complex data wrangling and visualization tasks, and finally look at the extended R ecosystem and tools for sharing your work with interactive reports, notebooks, and applications. Sign up for the whole series, or just the sessions that interest you most, but be advised that the later sessions will require at least a little familiarity with R.

See full session descriptions below and register here:

September 21: Introduction to R and RStudio

This session will provide a solid foundation in working with R and RStudio and lay the groundwork to enable participants to explore more advanced topics in R programming. No experience with R or programming is required.

Topics covered will include:

• Navigating the RStudio interface, installing packages, getting help
• Naming and working with objects
• Using functions
• Identifying R data types and structures
• Working with scripts

September 22: Data Wrangling with R — Introduction to the Tidyverse

This session will introduce the concept of “tidy” data, and the versatile collection of packages known as the Tidyverse.  Participants will get hands-on experience wrangling real datasets.

Topics covered include:

• Loading data from external files
• Subsetting data
• Transforming data from wide to long
• Working with dates
• Joining multiple datasets

Prerequisites: Session one in this series, or have previous experience with base R.

September 28: Data Visualization in R with ggplot2

Learn how to use the ggplot2, a robust Tidyverse package  used to create high quality graphics for exploring and communicating your data. We will go beyond basic graphs and learn how to customize and annotate our graphs for more effective storytelling. Participants will have the best experience if they attended session two in this series or have some previous experience with R and the Tidyverse.

Topics covered include:

• Visualization best practices
• Grammar of graphics – ggplot2 layers, aesthetics, and geoms
• Choosing an effective graph type for your data
• Customizing labels, axes, legends, and more
• Choosing a color palette and themes

Prerequisites: Session two in this series, or have previous experience with R.

September 29: Introduction to Reproducible Research and Interactive Data Applications in R

This session will provide a high-level overview of the vast ecosystem in R for reproducible research and creating interactive data visualizations. Users will learn about version control, packages available in R for creating reports, online books, and even blogs. There will also be an introduction to creating data applications/ dynamic dashboards using the Shiny package in R. Participants will have the best experience if they have some familiarity with R syntax and the RStudio interface.

Topics covered will include:

• Version control with Git
• Integrating RStudio and GitHub for project data and code management and version control.
• Reproducible research reports with code and prose with RMarkdown
• Sharing your work on the web with Bookdown/Blogdown
• Interact, analyze, and communicate your data with Shiny

Prerequisites: Session one in this series, or have previous experience with R.

Questions? Contact: Amy Yarnell, data services librarian and Jean-Paul Courneya, bioinformationist at data@hshsl.umaryland.edu.

The Center for Data and Bioinformation Services (CDABS) is the University of Maryland Health Sciences and Human Services Library hub for data and bioinformation learning, services, resources, and communication

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Learn R this summer with CDABS

The Center for Data and Bioinformation Services (CDABS) will be holding an R workshop every Thursday in July. All sessions run from 12:00pm to 3:00pm and meet online. Space is limited so register now!

R is an open-source programming language that is ideal for working with statistics and data. Here at CDABS, we love R for many reasons: It’s free, flexible, and friendly! It’s also a great tool for creating reproducible data analyses and visualizations.

In this series we’ll start with the basics of R and the RStudio environment, move to more complex data wrangling and visualization tasks, and finally look at the extended R ecosystem and tools for sharing your work with interactive reports, notebooks, and applications. Sign up for the whole series, or just the sessions that interest you most, but be advised that the later sessions will require at least a little familiarity with R.

See full session descriptions below and register here:

July 7: Introduction to R and RStudio

This session will provide a solid foundation in working with R and RStudio and lay the groundwork to enable participants to explore more advanced topics in R programming. No experience with R or programming is required.

Topics covered will include:

• Navigating the RStudio interface, installing packages, getting help
• Naming and working with objects
• Using functions
• Identifying R data types and structures
• Working with scripts

July 14: Data Wrangling with R — Introduction to the Tidyverse

This session will introduce the concept of “tidy” data, and the versatile collection of packages known as the Tidyverse.  Participants will get hands-on experience wrangling real datasets.

Topics covered include:

• Loading data from external files
• Subsetting data
• Transforming data from wide to long
• Working with dates
• Joining multiple datasets

Prerequisites: Session one in this series, or have previous experience with base R.

July 21: Data Visualization in R with ggplot2

Learn how to use the ggplot2, a robust Tidyverse package  used to create high quality graphics for exploring and communicating your data. We will go beyond basic graphs and learn how to customize and annotate our graphs for more effective storytelling. Participants will have the best experience if they attended session two in this series or have some previous experience with R and the Tidyverse.

Topics covered include:

• Visualization best practices
• Grammar of graphics – ggplot2 layers, aesthetics, and geoms
• Choosing an effective graph type for your data
• Customizing labels, axes, legends, and more
• Choosing a color palette and themes

Prerequisites: Session two in this series, or have previous experience with R.

July 28: Introduction to Reproducible Research and Interactive Data Applications in R

This session will provide a high-level overview of the vast ecosystem in R for reproducible research and creating interactive data visualizations. Users will learn about version control, packages available in R for creating reports, online books, and even blogs. There will also be an introduction to creating data applications/ dynamic dashboards using the Shiny package in R. Participants will have the best experience if they have some familiarity with R syntax and the RStudio interface.

Topics covered will include:

• Version control with Git
• Integrating RStudio and GitHub for project data and code management and version control.
• Reproducible research reports with code and prose with RMarkdown
• Sharing your work on the web with Bookdown/Blogdown
• Interact, analyze, and communicate your data with Shiny

Prerequisites: Session one in this series, or have previous experience with R.

Questions? Contact: Amy Yarnell, data services librarian and Jean-Paul Courneya, bioinformationist at data@hshsl.umaryland.edu.

The Center for Data and Bioinformation Services (CDABS) is the University of Maryland Health Sciences and Human Services Library hub for data and bioinformation learning, services, resources, and communication

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Register now! NHGRI Roundtable – May 25

The National Human Genome Research Institute (NHGRI) invites you to join them on Wednesday, May 25, from 1-3 p.m. ET for a conversation on the complexities surrounding historical and present-day eugenics, scientific racism and ableism in the context of genetic and genomic screening and diagnostic technologies.  

• What are the historical connections between the eugenics movement and genetic counseling, and what are their continuing legacies today? 
• How are ethical and scientific experts addressing the development of contemporary genetic counseling, reproductive choice and clinically informed decision-making?
• How can the scientific community discuss health, disease and disability in an empathetic way?  

An internationally recognized group of experts have been assembled to help answer these questions and more. NHGRI will also answer select questions from registered audience members. 

This event is free and open to the public. Sign language interpreting and CART services will be provided.

You can register here: https://nih.zoomgov.com/webinar/register/WN_ERdPQCJcTNqUJmA6WkDRTQ

The agenda for the event is available here: https://www.genome.gov/event-calendar/roundtable-discussion-does-genetic-and-genomic-screening-keep-open-the-door-to-eugenics

Questions? Contact: Jean-Paul Courneya, bioinformationist, and Amy Yarnell, data services librarian at data@hshsl.umaryland.edu.

The Center for Data and Bioinformation Services (CDABS) is the University of Maryland Health Sciences and Human Services Library hub for data and bioinformation learning, services, resources, and communication

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NIH Releases Guidance on Informed Consent Language for Data Sharing

Last month we talked about the new NIH Policy for Data Management and Sharing. Yesterday, the NIH released related documentation which provides suggested language to include in informed consent documents regarding the storage and sharing of research data for future use. As we like to say here at CDABS, it’s best to plan for sharing your data from the very start of your research project. This is why it’s so important to have a data management and sharing plan.

Some notes about the guidance:

• The use of the sample language in this document is recommended but voluntary.
• The language is intended to be incorporated in to the main informed consent document, not to replace or serve as a separate document, and its use does not obviate the need for IRB review.
• The sample language is generic, and other considerations/language may be necessary in cases where data is being collected from vulnerable populations and communities, from certain cultural groups and from Tribal Nations, and when collecting genomic data.
• The guidance and sample language generally do not distinguish between the sharing of data and of biospecimens, but participants may feel differently about the storage and sharing of each, and you might consider allowing them to consent separately to each.

The guidance recommends addressing the following topics in consent documents:

• Time frame for data and biospecimen storage
• Who will manage control of and access to data and biospecimens, or if data will be made available without restrictions
• If identifiers will be retained, and the likelihood of re-identification
• Whether sharing data and biospecimens will be optional and what happens in cases of withdrawal of consent
• Associated risks and benefits of data and biospecimens being stored and shared
• Potential commercial uses or applications that may result from stored and shared data and biospecimens

Other resources:

• HSHSL Consent Form Review Service: Staff at the HSHSL are available to help make sure your consent document is at the appropriate reading level
• UMB School of Nursing Research Consent Series: This informative seven-part series was offered as part of the School of Nursing Monthly Seminar Series. Find recordings and slides at the link provided.
• NHGRI Informed Consent Guidance: Information on consent for genomics research from the National Human Genome Research Institute.

Access the full guidance document here: https://osp.od.nih.gov/2022/05/12/nih-issues-new-resources-for-implementing-the-nih-policy-for-data-management-and-sharing-2/

Questions? Contact: Jean-Paul Courneya, bioinformationist, and Amy Yarnell, data services librarian at data@hshsl.umaryland.edu.

The Center for Data and Bioinformation Services (CDABS) is the University of Maryland Health Sciences and Human Services Library hub for data and bioinformation learning, services, resources, and communication

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NIH Policy for Data Management and Sharing 2023

You may have heard something by now about the new NIH Policy for Data Management and Sharing coming into effect January 2023. Concerned about what this policy means for you and your research? Have no fear; CDABS is here to help! We will be releasing resources and workshops over the next several months to help prepare the campus for this change. 

This post will cover some basic information about what this new policy entails:

What: A policy requiring 1) submission of a data management and sharing plan with all NIH grant applications for projects that generate scientific data, and 2) compliance with that plan. Note that the current NIH policy, which has been in effect since 2003, has this requirement only for projects requesting $500,000 or more in funds. So this is a much more expansive policy.

Importantly, this policy does not absolutely require you to share data. The policy recognizes that this may not always be possible given the sensitive nature of much health science research. However, according to the policy, “NIH expects that in drafting Plans, researchers will maximize the appropriate sharing of scientific data”, while also being mindful of ethical considerations.

When: Effective January 25, 2023

Who: Researchers seeking any funding from NIH for their research that generates scientific data.

Why: To accelerate discovery, improve rigor and reproducibility, provide access to high-value datasets, promote data reuse, and ultimately, to expedite the translation of research to knowledge. (See the NIH full statement)

Where: Visit the new NIH Data Sharing website for policy breakdown, supplemental information, and news.

For the full policy text visit: https://grants.nih.gov/grants/guide/notice-files/NOT-OD-21-013.html

How:

1. Familiarize yourself with some of the great resources for working with data available for UMB researchers.
   • DMPTool provides templates for writing plans and allows you to request feedback on your plan from the CDABS team. Use your UMID and password to authenticate.
   • OSF is a collaborative tool for keeping your project documents organized.
   • ICPSR and QDR are excellent repository options for sharing sensitive data.
   • The UMB Data Catalog can hold a record of your shared data, with metadata and access instructions.
2. Schedule a consult with us to talk more in-depth about your personalized data management needs, finding an appropriate repository, and anything else data-related!
3. Stay informed by subscribing to CDABS updates!

Questions? Contact: Jean-Paul Courneya, bioinformationist, and Amy Yarnell, data services librarian at data@hshsl.umaryland.edu.

The Center for Data and Bioinformation Services (CDABS) is the University of Maryland Health Sciences and Human Services Library hub for data and bioinformation learning, services, resources, and communication

Sign up to get DABS delivered to your email or RSS feed.

All of Us Research Program Genomic Data Release

The All of Us Research Program reached an important milestone with the release of its initial genomic dataset. Nearly 100,000 whole genome sequences (WGS) and 165,000 genotyping arrays are now available within the Researcher Workbench, less than two years after the beta launch of the platform. Nearly 50% of the data come from participants who self-identify with a racial or ethnic minority group.

Detailed genomic data are accessible through the Controlled Tier, a level of the Researcher Workbench with stricter requirements for access. This level also includes all of the data currently available in the Registered Tier, as well as additional clinical fields in EHRs, and more granular demographic data from both surveys and EHRs. For example, in the Controlled Tier, researchers can find additional International Classification of Diseases (ICD) codes for COVID-19 testing and diagnosis data, real dates of health events, and residential information (first three digits of the ZIP code).

The Controlled Tier is available to registered researchers who have completed additional training and whose institutions have an additional data use agreement in place with All of Us.

UMB’s Institutional agreement with All of Us has been expanded to allow Controlled Tier access. Registered All of Us – Research Workbench researchers can now access controlled tier genomics data!

Not a registered researcher? To create an account with All of Us and go through their required trainings, you can go to their registration page, https://www.researchallofus.org/register/.

CDABS has also put together a guide to help walk you through this registration process: https://guides.hshsl.umaryland.edu/allofusworkbench 

Questions? Contact: Jean-Paul Courneya, bioinformationist, and Amy Yarnell, data services librarian at data@hshsl.umaryland.edu.

The Center for Data and Bioinformation Services (CDABS) is the University of Maryland Health Sciences and Human Services Library hub for data and bioinformation learning, services, resources, and communication

Sign up to get DABS delivered to your email or RSS feed.

NCBI Virtual Workshop Series: Getting Started with NCBI Data in Python

The National Center for Biotechnology Information (NCBI) is pleased to announce an upcoming virtual workshop that is now accepting applications. The NCBI Education Team invites you to apply and share this opportunity with any colleagues who may be interested. The NCBI Virtual Workshops series was developed last fall to expand our reach to individuals who use NCBI resources for biological/biomedical research, science education, and clinical application efforts. Please review the workshop description to understand the intended audience. Each workshop will accept a limited number of participants to facilitate the best possible educational experience.

Title: Getting Started with NCBI Data in Python

Date and time: Tuesday, April 19, 2022, 1:00pm – 4:00pm ET

Description: Learn how to tackle bigger biomolecular datasets more reliably with the power of Python programming. This workshop is designed for biologists without programming experience. Our examples will use genomic, transcript, and protein sequence data, but the programming skills will be broadly relevant for all biologists.

In this workshop you will learn how to:

• Use Python programming to download, analyze, and visualize data.
• Use Jupyter to create data analysis ‘lab notebooks’ that make it easy to reproduce & share your work.
• Find data that is relevant to your project using the new NCBI Datasets resource. Explore metadata to learn about which datasets are available.
• Download sequence data with NCBI Datasets and manipulate it with the BioPython package.

Apply here: https://ncbiinsights.ncbi.nlm.nih.gov/event/getting-started-with-ncbi-data-in-python-04-22/

Application close date: March 29, 2022

Please note, this workshop was designed for people with a good understanding of molecular biology, but who have limited or no programming experience.

Due to curricular and technical limits, the number of spots have been capped to provide the best workshop experience. If you register to apply, you will be notified of your application status 2 weeks before the scheduled event.

They recommend having access to a stable internet connection and modern web browser on a laptop or desktop computer to be able to successfully participate in the hands-on exercises.

More information can be found on the new Outreach Events page of the NCBI Insights Blog. See also the FAQ page and if you still have questions about the NCBI Outreach Events program or this specific workshop, email NCBI Education Team at workshops@ncbi.nlm.nih.gov.

Questions? Contact: Jean-Paul Courneya, bioinformationist, and Amy Yarnell, data services librarian at data@hshsl.umaryland.edu.

The Center for Data and Bioinformation Services (CDABS) is the University of Maryland Health Sciences and Human Services Library hub for data and bioinformation learning, services, resources, and communication

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Registration Open for ICPSR Summer Program in Quantitative Methods

Improve your statistical analysis skills with ICPSR’S Summer Program!

ICPSR (Inter-university Consortium for Political and Social Research), is home to the world’s largest collection of digital social science data. Register now for ICPSR’s long-running and well-respected Summer Program in Quantitative Methods. This program offers a mix of intensive four-week sessions, shorter workshops, and lectures series throughout the summer This year’s program is hybrid with opportunities for virtual attendance or on-location attendance in Ann Arbor, MI. Courses are for beginning or advanced students of quantitative methods. The program attracts university faculty and researchers, graduate students, and nonacademic research scientists.

As members of ICPSR, the UMB community receives a significant discount on tuition. There are also a number of scholarships available to help defray costs even further. 

Example workshop topics include:

• Race, Ethnicity, and Quantitative Methodology
• Regression Analysis
• Multivariate Statistical Methods: Advanced Topics
• Machine Learning: Applications in Social Science Research
• Data Science and Text Analysis
• Panel Data and Longitudinal Analysis
• Bayesian Modeling

Important dates:

• Scholarship Deadline: March 28, 2022
• Early Registration Discount Deadline: April 30, 2022
• Registration closes for Session 1: June 12, 2022
• Registration closes for Session 2: July 10, 2022
• Session 1: June 20 – July 15, 2022
• Session 2: July 18 – August 12, 2022
• Short Workshops: Multiple dates from May through August 2022.

Questions? Contact: Amy Yarnell, data services librarian, and Jean-Paul Courneya, bioinformationist, at data@hshsl.umaryland.edu.

The Center for Data and Bioinformation Services (CDABS) is the University of Maryland Health Sciences and Human Services Library hub for data and bioinformation learning, services, resources, and communication

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One of our favorite things here at CDABS is getting to collaborate with our data colleagues at other universities, especially members of the Data Discovery Collaboration (DDC).  Recently, members of the DDC (including yours truly), produced this handy guide on making your research data more discoverable.

1. Decide what level of access you can provide – Data discovery and data access are related but distinct concepts. Data discovery is the ability to find if and where datasets exist, whereas data access refers to the processes for viewing and downloading data. It’s helpful to decide the level of access first, so you can be sure to describe your data accurately, and use appropriate tools to make data discoverable.  For example, even if you cannot openly share your data, you can still share metadata about your data through the UMB Data Catalog.
2. Comply with ethical standards – Ethics come into play in decisions and discussions throughout the life span of your research project, and will certainly be a part of decisions about data access and storage. Be especially careful about any data you collect regarding vulnerable populations, and keep in mind that advances in data and technology may outpace changes in regulations.
3. Deposit your data somewhere trusted – In some fields and for some data types there is a clear place to deposit data, but for others there are more options. Look for recommendations from journals, funding agencies, professional associations, and your friendly neighborhood data librarian to find discipline specific or appropriate generalist repositories. Your data may be more findable if stored in the same place as other data from your field.
4. Use persistent identifiers – Persistent identifiers or PIDs include things like ORCID iDs for people and DOIs for datasets, journal articles, and more. These identifiers provide a stable, unique link to data and the scholars who created it. PIDs are machine readable and thus an important building block of research data computing infrastructure.
5. Create thoughtful and rich metadata – metadata is information about your data, and includes things like title, creator, subject, description, data types. Good metadata is also structured in a way that makes it both machine and human readable. When you search for something in a repository or catalog, it is the metadata that helps you find it. The UMB Data Catalog uses a robust metadata schema, so listing your data there is a great way to make sure your data is richly and accurately described.
6. Choose your keywords carefully – not every repository or catalog will allow you to provide keywords, but this is another way you can add descriptive information to your data and potentially link it with other similar datasets that are described with the same terms (like how hashtags help you find tweets).
7. Create links to related resources – think of your data as part of a larger research ecosystem that includes authors, publications, grants, institutions, software, code, etc. Link all these things together whenever you can. Creating multiple pathways to your data makes it more findable.
8. Make supporting information discoverable too – It is often possible to submit your data along with an article to a journal. But these systems are not really designed for finding or storing data. A better bet is to submit data to a trusted repository and link to that data in your article.
9. Include an accurate Data Availability Statement with your publications – a great way to make your data findable is to tell people exactly where to find it. You may have the opportunity in a publication to explain where one can find the associated data. Take the opportunity to provide a PID to your data, which is hopefully located in a trusted repository (see? we’re pulling it all together now). Also, pro tip – PubMed Central has special filters available that facilitate finding articles with data availability statements
10. Talk to your institutional librarian – we called them “simple” rules, but we know they can actually be quite daunting! But have no fear, we at CDABS are here to help! Have questions about making your data more discoverable? Contact us for a research data consultation!

For more information, be sure to check out the full article!

This blog post has been adapted under a Creative Commons Attribution License, from Ten simple rules for improving research data discovery. PLoS Comput Biol 18(2): e1009768. https://doi.org/10.1371/journal.pcbi.1009768 by Contaxis N, Clark J, Dellureficio A, Gonzales S, Mannheimer S, Oxley PR, Ratajeski MA, Surkis A, Yarnell AM, Yee M, and Holmes K.   

Questions?

Contact: Amy Yarnell, Data Services Librarian and Jean-Paul Courneya, Bioinformationist – at data@hshsl.umaryland.edu.

The Center for Data and Bioinformation Services (CDABS) is the University of Maryland Health Sciences and Human Services Library hub for data and bioinformation learning, services, resources, and communication.

To read more of our content and stay informed please fill out the form to subscribe here: https://www2.hshsl.umaryland.edu/cdabs/communications

Love Data Week (Feb. 14 to 18) is an international celebration of all things data! Each year, the Center for Data and Bioinformation Services (CDABS) at the Health Sciences and Human Services Library (HSHSL) looks forward to engaging our community on issues like data management, sharing, wrangling, and visualization, as well as open and reproducible science.

Want to participate in Love Data Week? Here’s how:

• Join CDABS on Tuesday, Feb. 15, at noon for a virtual, interactive, introductory workshop on the Open Science Framework (OSF), a research project management and collaboration tool from the Center for Open Science. The University of Maryland, Baltimore recently became an OSF member institution. Learn more about what that means for you, and register here.
• Adopt a Dataset or attend a webinar with ICPSR, the official Love Data Week organizers and an excellent place to find data! Visit their site for more information.
• Join our friends at the National Library of Medicine throughout the week for their series of workshops on topics including Census Tools to Better Understand Your Community, the National Institutes of Health (NIH) Data Sharing and Management Plan, DMPTool Basics, and Doing No Harm with Data Viz. (Note: You must sign up for a free NLM account to register).
• Attend the Community Building Convention for NIH’s Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity (AIM-AHEAD). The goal of AIM-AHEAD is to enhance diversity in the field of artificial intelligence and machine learning (AI/ML), with emphasis on reducing health disparities and promoting health equity. Listening sessions will be held for different communities throughout the week. Find your session and register.

Finally, as always, you can join the conversation on social media #LoveData22 and #UMBLovesData.

Questions? Contact Amy Yarnell, data services librarian, at data@hshsl.umaryland.edu.

The Center for Data and Bioinformation Services (CDABS) is the University of Maryland Health Sciences and Human Services Library hub for data and bioinformation learning, services, resources, and communication.

To read more of our content and stay informed please fill out the form to subscribe here: https://www2.hshsl.umaryland.edu/cdabs/communications

OSF, a project of the Center for Open Science, is a free and open source project management and collaboration tool that supports researchers throughout the research lifecycle. It’s a great way to organize and share resources with your team and others! It also integrates easily with a number of other commonly used tools like Google Drive, Zotero, Mendeley, Figshare, and GitHub.

The University of Maryland, Baltimore is now an OSF Institution, which means you can log in to OSF with your UMID and password.  

You will also be able to affiliate your public research with UMB on OSF and discover other affiliated research through our new UMB-OSF landing page. If your research is not yet public, now might be a good time to consider sharing your existing or future work. Conducting your research through UMB’s OSFI platform is a strategic way to enhance transparency, foster collaboration, and increase the visibility of your research. 

For more information, you can view help guides on signing in with your institution and affiliating your projects. In addition, you can join CDABS for a virtual Introductory OSF workshop on Feb 15 at noon, where we will demonstrate the main features and potential use cases and get you started using OSF! Registration page. 

Questions?

Contact: Amy Yarnell, Data Services Librarian and Jean-Paul Courneya, Bioinformationist – at data@hshsl.umaryland.edu.

The Center for Data and Bioinformation Services (CDABS) is the University of Maryland Health Sciences and Human Services Library hub for data and bioinformation learning, services, resources, and communication.

To read more of our content and stay informed please fill out the form to subscribe here: https://www2.hshsl.umaryland.edu/cdabs/communications

What is the UMB Data Catalog?
The UMB Data Catalog, a service of the Health Sciences and Human Services Library’s (HSHSL) Center for Data and Bioinformation Services (CDABS), facilitates the discovery of datasets and research products created or used by UMB researchers. Each dataset record includes a description, keywords, contact information, links to associated articles, and more.  

The catalog is not a repository to store datasets; it describes them. By having a record for your dataset in the Data Catalog, you can increase the visibility of your research on campus and beyond. Datasets are discoverable through a search in the UMB Data Catalog, Google’s Dataset Search (beta), and Google. Use the link to your dataset record in articles, CVs, and your web profile.

Still need to find a repository for your data? 
There is an ever-increasing number of options out there for sharing and storing data. At CDABS, we can help you sort through these options and find an appropriate fit for your data that takes into account funding or publisher requirements, discipline, size, privacy requirements, data type, and more.

Have data, but it’s not open?
We know that many researchers here at UMB work with sensitive data that may not be appropriate for open repositories. By listing your data in the Data Catalog, you can still let the world know your data exists, provide access to valuable metadata, or set up an application process allowing for restricted access to the data. Be sure to talk to us about options for repositories that can handle sensitive data like ICPSR and QDR, or about setting up data use agreements.  

Learn more about the UMB Data Catalog in this tutorial.

Request a consultation or submit your dataset to the Data Catalog.

The Center for Data and Bioinformation Services (CDABS) is the University of Maryland Health Sciences and Human Services Library hub for data and bioinformation learning, services, resources, and communication.

Questions? Contact:  Jean-Paul Courneya, Bioinformationist and Amy Yarnell, Data Services Librarian – at data@hshsl.umaryland.edu.

To read more of our content and stay informed please visit our communications page and use the form to subscribe: https://www2.hshsl.umaryland.edu/cdabs/communications

UMB is now an OSF Member Institution

OSF, a project of the Center for Open Science, is a free and open source project management tool that supports researchers throughout their entire project lifecycle. It’s a great product to help you collaborate and share resources with your team and others!

The HSHSL has recently coordinated UMB’s membership in OSF, which means that you will soon be able to log in to OSF with your UMB credentials, and you will have the option to affiliate your project with UMB. All UMB affiliated projects will show up on a special landing page – a great way to promote all the great work we do here! Stay tuned for more information and resources on using OSF in the near future.

We here at CDABS love using OSF to share materials from our workshops. See OSF in action by checking out our workshops page here: https://osf.io/eyk4d/.

Open to All – ICPSR’s Virtual Biennial Meeting

ICPSR is the world’s largest repository of social science data. All University of Maryland Baltimore staff, students, and faculty have access to the extensive ICPSR data holdings for free! It can be a great place to find data, share data, and learn about working with data.

From October 6-8, ICPSR will be holding their biennial meeting. This meeting is free, virtual, and open to the public. The theme of the meeting is “Data Positivity: Data Doing Good”. The sessions will provide numerous opportunities to learn more about ICPSR data, including how to find and access it. Check out the meeting page to find out more and register.

NIH’s All of Us Research Program Offers Expanded COVID-19 Data in Latest Release

The All of Us Research Program, part of the National Institutes of Health, is a historic precision medicine effort to collect and study data from a diverse cohort of one million or more participants living in the United States. In the program’s latest data release, the second major update since it launched, tens of thousands of records have been added containing COVID-19 related data from the COVID-19 Participant Experience (COPE) survey, electronic health records, and wearable devices. Read more about this newest update in the official press release. 

Not sure how to get started using All of Us data? Check out our step-by-step guide on getting registered to use the All of Us Researcher Workbench, and please reach out to CDABS if you have any questions about the process or using Workbench tools!

The Center for Data and Bioinformation Services (CDABS) is the University of Maryland Health Sciences and Human Services Library hub for data and bioinformation learning, services, resources, and communication.

Questions? Contact: Amy Yarnell, Data Services Librarian and Jean-Paul Courneya, Bioinformationist – at data@hshsl.umaryland.edu.

To read more of our content and stay informed please visit our communications page and use the form to subscribe: https://www2.hshsl.umaryland.edu/cdabs/communications

We are growing! As part of our growth we are looking for a creative and collaborative Statistics and Research Data Specialist to join the Data and Bioinformation Services department, the home of CDABS. The Statistics and Research Data Specialist is a key member of a team responsible for advancing the Library’s research data support mission at UMB. This is a part-time position at 30 hours/week.

This position provides consultation services to students, postdocs, and staff, providing assistance with statistical aspects of research design, data interpretation and analysis, and on the use of software supporting this work. They serve as a vital team member of HSHSL’s CDABS.

In a strong team environment, they collaborate with other members of the Services Division, and with colleagues Library-wide to develop and deliver innovative programs and services. In addition to advancing HSHSL priorities, they engage with the University community and participate in professional and scholarly activities.

To apply for and find out more about the job go here: https://umb.taleo.net/careersection/umb_external_staff/jobdetail.ftl?job=2100016R&lang=en

Questions? Contact: Amy Yarnell, Data Services Librarian and Jean-Paul Courneya, Bioinformationist – at data@hshsl.umaryland.edu.

To read more of our content and stay informed please visit our communications page and use the form to subscribe: https://www2.hshsl.umaryland.edu/cdabs/communications

NCBI is the national resource for molecular biology information, NCBI’s mission is to develop new information technologies to aid in the understanding of fundamental molecular and genetic processes that control health and disease. More specifically, the NCBI has been charged with creating automated systems for storing and analyzing knowledge about molecular biology, biochemistry, and genetics; facilitating the use of such databases and software by the research and medical community; coordinating efforts to gather biotechnology information both nationally and internationally; and performing research into advanced methods of computer-based information processing for analyzing the structure and function of biologically important molecules.

NCBI Outreach Events

The NCBI Outreach Events page (https://ncbiinsights.ncbi.nlm.nih.gov/ncbi-outreach-events/) allows you to search and apply for upcoming NCBI webinars, workshops, codeathons, and other outreach activities.

Some exciting upcoming workshop and codeathon opportunities include: 

The Center for Data and Bioinformation Services (CDABS) is the University of Maryland Health Sciences and Human Services Library hub for data and bioinformation learning, services, resources, and communication.

Questions? Contact: Amy Yarnell, Data Services Librarian and Jean-Paul Courneya, Bioinformationist – at data@hshsl.umaryland.edu.

To read more of our content and stay informed please visit our communications page and use the form to subscribe: https://www2.hshsl.umaryland.edu/cdabs/communications

CDABS is excited to announce that UMB has recently signed a Data Use Agreement with NCATS N3C Data Enclave, making this rich source of COVID clinical data from across the country available to UMB researchers.

What is N3C?

The National COVID Cohort Collaborative (N3C) Data Enclave was launched by the National Center for Advancing Translational Sciences (NCATS) and the National Center for Data to Health (CD2H), in partnership with experts from Observational Health Data Sciences and Informatics (OHDSI), PCORnet, the Accrual to Clinical Trials (ACT) network, and TriNetX. The N3C aims to aggregate, harmonize, and make accessible vast amounts of clinical data nationwide to accelerate COVID-19 research and clinical care. With the uncertainty of the COVID-19 global pandemic, the scientific community and the Clinical and Translational Science Awards (CTSA) Program created the N3C as a partnership to overcome technical, regulatory, policy, and governance barriers to harmonizing and sharing individual-level clinical data.

What can I do with N3C data?

The N3C Data Enclave supports collaborative analytics across a broad range of clinical and translational domains, such as acute kidney injury, diabetes, pregnancy, cancer, immunosuppression, social determinants of health, and many other conditions to target treatment mechanism, drug discovery, and best care practices for COVID-19. The N3C Data Enclave opened on September 2, 2020 and now has over 5 billion rows of data on more than 4 million patient records, including over 1 million COVID positive patients.

There are three tiers of data available with different restrictions and requirements for access. From most to least restricted these are: Limited, De-identified, and Synthetic. Check out the N3C data governance page for more details on these tiers. In order to maintain adequate security, row-level data must remain in the enclave, but many tools are provided to researchers for working with the data from within the platform.

To see what others are doing with N3C data, visit the projects page.

How do I get access?

1. 1. Register for and gain access to the N3C Data Enclave here.
   2. Choose the InCommon option on the login screen to log in with your UMB credentials.

Account creation may take a few days. You will also need to complete the NIH Information Security and Information Management Training course and, if you wish to access the limited or de-identified datasets, submit evidence of having completed a Human Subjects Research Protection training course.

Once you obtain access to the Enclave, you will need to submit a Data Use Request for each specific project you intend to do. If you would like to use the limited dataset, you will need to submit a copy of your IRB determination letter as well.  For more details on requirements, please see the onboarding checklist.

Where can I get more information?

Visit the tutorials page for basics on using the N3C platform. There are additional training modules available within the Enclave. And of course, do not hesitate to reach out to your friendly, neighborhood CDABS team with any questions!

Questions? Contact: Amy Yarnell, Data Services Librarian and Jean-Paul Courneya, Bioinformationist – at data@hshsl.umaryland.edu.

To read more of our content and stay informed please visit our communications page and use the form to subscribe: https://www2.hshsl.umaryland.edu/cdabs/communications

We are wrapping up another week (Mar 08 -12) of learning and growing at CDABS. This week’s DABS focus will be on machine learning. What is machine learning? Machine learning involves using specialized computer software for automation and decisions by a person to extract knowledge from data. There are two main categories of Machine learning, supervised learning which involves making predictions using data (for example: spam filters) and unsupervised learning for finding a structure from data (Topic Modeling, in Natural Language Processing, to elucidate topics in a collection of texts). There are several resources on the web to get started doing machine learning in your research. Here are a few places to start digging in that are phenomenal. 

1. Data School is an online portal with blog posts, videos, courses, Jupyter notebooks, and webcast recordings to learn data science. Data School offers three Machine Learning courses: Introduction to Machine Learning with scikit-learn, Building an Effective Machine Learning Workflow with scikit-learn, and Machine Learning with Text in Python. Learn more here: (10 minute read) https://www.dataschool.io/ml-courses/
2. Machine Learning Mastery is a website dedicated to making you awesome at machine learning. They use a top down approach to learn modern machine learning via hands-on tutorials. (15 minute read) https://machinelearningmastery.com/start-here/
3. StatQuest provides an “An epic journey through statistics and machine learning”. Join Josh Starmer and see his unique and fun approach to breaking down the complex topics into small digestible bits via engaging YouTube videos with accompanying code. Check out the section on machine learning but also make sure to broaden your exploration to many other topics in statistics. (10 minute read) https://statquest.org/video-index/#machine 

Questions?  

Contact: Amy Yarnell, Data Services Librarian and Jean-Paul Courneya, Bioinformationist – at data@hshsl.umaryland.edu. 

To read more of our content and stay informed please visit our communications page and fill out the form to subscribe.  

Subscribe here: https://www2.hshsl.umaryland.edu/cdabs/communications